Top 100 AWS Certified Data Analytics Specialty Certification Questions and Answers Dumps
If you’re looking to take your data analytics career to the next level, then this AWS Data Analytics Specialty Certification Exam Preparation blog is a must-read! With over 100 exam questions and answers, plus data science and data analytics interview questions, cheat sheets and more, you’ll be fully prepared to ace the DAS-C01 exam.
In this blog, we talk about big data and data analytics; we also give you the last updated top 100 AWS Certified Data Analytics – Specialty Questions and Answers Dumps
The AWS Certified Data Analytics – Specialty (DAS-C01) examination is intended for individuals who perform in a data analytics-focused role. This exam validates an examinee’s comprehensive understanding of using AWS services to design, build, secure, and maintain analytics solutions that provide insight from data.
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Question1:What combination of services do you need for the following requirements: accelerate petabyte-scale data transfers, load streaming data, and the ability to create scalable, private connections. Select the correct answer order.
AWS has many options to help get data into the cloud, including secure devices like AWS Import/Export Snowball to accelerate petabyte-scale data transfers, Amazon Kinesis Firehose to load streaming data, and scalable private connections through AWS Direct Connect.
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Question 3: There is a five-day car rally race across Europe. The race coordinators are using a Kinesis stream and IoT sensors to monitor the movement of the cars. Each car has a sensor and data is getting back to the stream with the default stream settings. On the last day of the rally, data is sent to S3. When you go to interpret the data in S3, there is only data for the last day and nothing for the first 4 days. Which of the following is the most probable cause of this?
A) You did not have versioning enabled and would need to create individual buckets to prevent the data from being overwritten.
B) Data records are only accessible for a default of 24 hours from the time they are added to a stream.
C) One of the sensors failed, so there was no data to record.
D) You needed to use EMR to send the data to S3; Kinesis Streams are only compatible with DynamoDB.
ANSWER3:
B
Notes/Hint3:
Streams support changes to the data record retention period of your stream. An Amazon Kinesis stream is an ordered sequence of data records, meant to be written to and read from in real-time. Data records are therefore stored in shards in your stream temporarily. The period from when a record is added to when it is no longer accessible is called the retention period. An Amazon Kinesis stream stores records for 24 hours by default, up to 168 hours.
Question 4: A publisher website captures user activity and sends clickstream data to Amazon Kinesis Data Streams. The publisher wants to design a cost-effective solution to process the data to create a timeline of user activity within a session. The solution must be able to scale depending on the number of active sessions. Which solution meets these requirements?
A) Include a variable in the clickstream data from the publisher website to maintain a counter for the number of active user sessions. Use a timestamp for the partition key for the stream. Configure the consumer application to read the data from the stream and change the number of processor threads based upon the counter. Deploy the consumer application on Amazon EC2 instances in an EC2 Auto Scaling group.
B) Include a variable in the clickstream to maintain a counter for each user action during their session. Use the action type as the partition key for the stream. Use the Kinesis Client Library (KCL) in the consumer application to retrieve the data from the stream and perform the processing. Configure the consumer application to read the data from the stream and change the number of processor threads based upon the counter. Deploy the consumer application on AWS Lambda.
C) Include a session identifier in the clickstream data from the publisher website and use as the partition key for the stream. Use the Kinesis Client Library (KCL) in the consumer application to retrieve the data from the stream and perform the processing. Deploy the consumer application on Amazon EC2 instances in an EC2 Auto Scaling group. Use an AWS Lambda function to reshard the stream based upon Amazon CloudWatch alarms.
D) Include a variable in the clickstream data from the publisher website to maintain a counter for the number of active user sessions. Use a timestamp for the partition key for the stream. Configure the consumer application to read the data from the stream and change the number of processor threads based upon the counter. Deploy the consumer application on AWS Lambda.
ANSWER4:
C
Notes/Hint4:
Partitioning by the session ID will allow a single processor to process all the actions for a user session in order. An AWS Lambda function can call the UpdateShardCount API action to change the number of shards in the stream. The KCL will automatically manage the number of processors to match the number of shards. Amazon EC2 Auto Scaling will assure the correct number of instances are running to meet the processing load.
Question 5: Your company has two batch processing applications that consume financial data about the day’s stock transactions. Each transaction needs to be stored durably and guarantee that a record of each application is delivered so the audit and billing batch processing applications can process the data. However, the two applications run separately and several hours apart and need access to the same transaction information. After reviewing the transaction information for the day, the information no longer needs to be stored. What is the best way to architect this application?
A) Use SQS for storing the transaction messages; when the billing batch process performs first and consumes the message, write the code in a way that does not remove the message after consumed, so it is available for the audit application several hours later. The audit application can consume the SQS message and remove it from the queue when completed.
B) Use Kinesis to store the transaction information. The billing application will consume data from the stream and the audit application can consume the same data several hours later.
C) Store the transaction information in a DynamoDB table. The billing application can read the rows while the audit application will read the rows then remove the data.
D) Use SQS for storing the transaction messages. When the billing batch process consumes each message, have the application create an identical message and place it in a different SQS for the audit application to use several hours later.
SQS would make this more difficult because the data does not need to persist after a full day.
ANSWER5:
B
Notes/Hint5:
Kinesis appears to be the best solution that allows multiple consumers to easily interact with the records.
Question 6: A company is currently using Amazon DynamoDB as the database for a user support application. The company is developing a new version of the application that will store a PDF file for each support case ranging in size from 1–10 MB. The file should be retrievable whenever the case is accessed in the application. How can the company store the file in the MOST cost-effective manner?
A) Store the file in Amazon DocumentDB and the document ID as an attribute in the DynamoDB table.
B) Store the file in Amazon S3 and the object key as an attribute in the DynamoDB table.
C) Split the file into smaller parts and store the parts as multiple items in a separate DynamoDB table.
D) Store the file as an attribute in the DynamoDB table using Base64 encoding.
ANSWER6:
B
Notes/Hint6:
Use Amazon S3 to store large attribute values that cannot fit in an Amazon DynamoDB item. Store each file as an object in Amazon S3 and then store the object path in the DynamoDB item.
Question 7: Your client has a web app that emits multiple events to Amazon Kinesis Streams for reporting purposes. Critical events need to be immediately captured before processing can continue, but informational events do not need to delay processing. What solution should your client use to record these types of events without unnecessarily slowing the application?
A) Log all events using the Kinesis Producer Library.
B) Log critical events using the Kinesis Producer Library, and log informational events using the PutRecords API method.
C) Log critical events using the PutRecords API method, and log informational events using the Kinesis Producer Library.
D) Log all events using the PutRecords API method.
ANSWER2:
C
Notes/Hint7:
The PutRecords API can be used in code to be synchronous; it will wait for the API request to complete before the application continues. This means you can use it when you need to wait for the critical events to finish logging before continuing. The Kinesis Producer Library is asynchronous and can send many messages without needing to slow down your application. This makes the KPL ideal for the sending of many non-critical alerts asynchronously.
Question 8: You work for a start-up that tracks commercial delivery trucks via GPS. You receive coordinates that are transmitted from each delivery truck once every 6 seconds. You need to process these coordinates in near real-time from multiple sources and load them into Elasticsearch without significant technical overhead to maintain. Which tool should you use to digest the data?
A) Amazon SQS
B) Amazon EMR
C) AWS Data Pipeline
D) Amazon Kinesis Firehose
ANSWER8:
D
Notes/Hint8:
Amazon Kinesis Firehose is the easiest way to load streaming data into AWS. It can capture, transform, and load streaming data into Amazon S3, Amazon Redshift, and Amazon Elasticsearch Service, enabling near real-time analytics with existing business intelligence tools and dashboards.
Question 9: A company needs to implement a near-real-time fraud prevention feature for its ecommerce site. User and order details need to be delivered to an Amazon SageMaker endpoint to flag suspected fraud. The amount of input data needed for the inference could be as much as 1.5 MB. Which solution meets the requirements with the LOWEST overall latency?
A) Create an Amazon Managed Streaming for Kafka cluster and ingest the data for each order into a topic. Use a Kafka consumer running on Amazon EC2 instances to read these messages and invoke the Amazon SageMaker endpoint.
B) Create an Amazon Kinesis Data Streams stream and ingest the data for each order into the stream. Create an AWS Lambda function to read these messages and invoke the Amazon SageMaker endpoint.
C) Create an Amazon Kinesis Data Firehose delivery stream and ingest the data for each order into the stream. Configure Kinesis Data Firehose to deliver the data to an Amazon S3 bucket. Trigger an AWS Lambda function with an S3 event notification to read the data and invoke the Amazon SageMaker endpoint.
D) Create an Amazon SNS topic and publish the data for each order to the topic. Subscribe the Amazon SageMaker endpoint to the SNS topic.
ANSWER9:
A
Notes/Hint9:
An Amazon Managed Streaming for Kafka cluster can be used to deliver the messages with very low latency. It has a configurable message size that can handle the 1.5 MB payload.
Question 10: You need to filter and transform incoming messages coming from a smart sensor you have connected with AWS. Once messages are received, you need to store them as time series data in DynamoDB. Which AWS service can you use?
A) IoT Device Shadow Service
B) Redshift
C) Kinesis
D) IoT Rules Engine
ANSWER10:
D
Notes/Hint10:
The IoT rules engine will allow you to send sensor data over to AWS services like DynamoDB
Question 11: A media company is migrating its on-premises legacy Hadoop cluster with its associated data processing scripts and workflow to an Amazon EMR environment running the latest Hadoop release. The developers want to reuse the Java code that was written for data processing jobs for the on-premises cluster. Which approach meets these requirements?
A) Deploy the existing Oracle Java Archive as a custom bootstrap action and run the job on the EMR cluster.
B) Compile the Java program for the desired Hadoop version and run it using a CUSTOM_JAR step on the EMR cluster.
C) Submit the Java program as an Apache Hive or Apache Spark step for the EMR cluster.
D) Use SSH to connect the master node of the EMR cluster and submit the Java program using the AWS CLI.
ANSWER11:
B
Notes/Hint11:
A CUSTOM JAR step can be configured to download a JAR file from an Amazon S3 bucket and execute it. Since the Hadoop versions are different, the Java application has to be recompiled.
Question 12: You currently have databases running on-site and in another data center off-site. What service allows you to consolidate to one database in Amazon?
A) AWS Kinesis
B) AWS Database Migration Service
C) AWS Data Pipeline
D) AWS RDS Aurora
ANSWER12:
B
Notes/Hint12:
AWS Database Migration Service can migrate your data to and from most of the widely used commercial and open source databases. It supports homogeneous migrations such as Oracle to Oracle, as well as heterogeneous migrations between different database platforms, such as Oracle to Amazon Aurora. Migrations can be from on-premises databases to Amazon RDS or Amazon EC2, databases running on EC2 to RDS, or vice versa, as well as from one RDS database to another RDS database.
Question 13: An online retail company wants to perform analytics on data in large Amazon S3 objects using Amazon EMR. An Apache Spark job repeatedly queries the same data to populate an analytics dashboard. The analytics team wants to minimize the time to load the data and create the dashboard. Which approaches could improve the performance? (Select TWO.)
A) Copy the source data into Amazon Redshift and rewrite the Apache Spark code to create analytical reports by querying Amazon Redshift.
B) Copy the source data from Amazon S3 into Hadoop Distributed File System (HDFS) using s3distcp.
C) Load the data into Spark DataFrames.
D) Stream the data into Amazon Kinesis and use the Kinesis Connector Library (KCL) in multiple Spark jobs to perform analytical jobs.
E) Use Amazon S3 Select to retrieve the data necessary for the dashboards from the S3 objects.
ANSWER13:
C and E
Notes/Hint13:
One of the speed advantages of Apache Spark comes from loading data into immutable dataframes, which can be accessed repeatedly in memory. Spark DataFrames organizes distributed data into columns. This makes summaries and aggregates much quicker to calculate. Also, instead of loading an entire large Amazon S3 object, load only what is needed using Amazon S3 Select. Keeping the data in Amazon S3 avoids loading the large dataset into HDFS.
Question 14: You have been hired as a consultant to provide a solution to integrate a client’s on-premises data center to AWS. The customer requires a 300 Mbps dedicated, private connection to their VPC. Which AWS tool do you need?
A) VPC peering
B) Data Pipeline
C) Direct Connect
D) EMR
ANSWER14:
C
Notes/Hint14:
Direct Connect will provide a dedicated and private connection to an AWS VPC.
Question 15: Your organization has a variety of different services deployed on EC2 and needs to efficiently send application logs over to a central system for processing and analysis. They’ve determined it is best to use a managed AWS service to transfer their data from the EC2 instances into Amazon S3 and they’ve decided to use a solution that will do what?
A) Installs the AWS Direct Connect client on all EC2 instances and uses it to stream the data directly to S3.
B) Leverages the Kinesis Agent to send data to Kinesis Data Streams and output that data in S3.
C) Ingests the data directly from S3 by configuring regular Amazon Snowball transactions.
D) Leverages the Kinesis Agent to send data to Kinesis Firehose and output that data in S3.
ANSWER15:
D
Notes/Hint15:
Kinesis Firehose is a managed solution, and log files can be sent from EC2 to Firehose to S3 using the Kinesis agent.
Question 16: A data engineer needs to create a dashboard to display social media trends during the last hour of a large company event. The dashboard needs to display the associated metrics with a latency of less than 1 minute. Which solution meets these requirements?
A) Publish the raw social media data to an Amazon Kinesis Data Firehose delivery stream. Use Kinesis Data Analytics for SQL Applications to perform a sliding window analysis to compute the metrics and output the results to a Kinesis Data Streams data stream. Configure an AWS Lambda function to save the stream data to an Amazon DynamoDB table. Deploy a real-time dashboard hosted in an Amazon S3 bucket to read and display the metrics data stored in the DynamoDB table.
B) Publish the raw social media data to an Amazon Kinesis Data Firehose delivery stream. Configure the stream to deliver the data to an Amazon Elasticsearch Service cluster with a buffer interval of 0 seconds. Use Kibana to perform the analysis and display the results.
C) Publish the raw social media data to an Amazon Kinesis Data Streams data stream. Configure an AWS Lambda function to compute the metrics on the stream data and save the results in an Amazon S3 bucket. Configure a dashboard in Amazon QuickSight to query the data using Amazon Athena and display the results.
D) Publish the raw social media data to an Amazon SNS topic. Subscribe an Amazon SQS queue to the topic. Configure Amazon EC2 instances as workers to poll the queue, compute the metrics, and save the results to an Amazon Aurora MySQL database. Configure a dashboard in Amazon QuickSight to query the data in Aurora and display the results.
ANSWER16:
A
Notes/Hint16:
Amazon Kinesis Data Analytics can query data in a Kinesis Data Firehose delivery stream in near-real time using SQL. A sliding window analysis is appropriate for determining trends in the stream. Amazon S3 can host a static webpage that includes JavaScript that reads the data in Amazon DynamoDB and refreshes the dashboard.
Question 17: A real estate company is receiving new property listing data from its agents through .csv files every day and storing these files in Amazon S3. The data analytics team created an Amazon QuickSight visualization report that uses a dataset imported from the S3 files. The data analytics team wants the visualization report to reflect the current data up to the previous day. How can a data analyst meet these requirements?
A) Schedule an AWS Lambda function to drop and re-create the dataset daily.
B) Configure the visualization to query the data in Amazon S3 directly without loading the data into SPICE.
C) Schedule the dataset to refresh daily.
D) Close and open the Amazon QuickSight visualization.
ANSWER17:
B
Notes/Hint17:
Datasets created using Amazon S3 as the data source are automatically imported into SPICE. The Amazon QuickSight console allows for the refresh of SPICE data on a schedule.
Question 18: You need to migrate data to AWS. It is estimated that the data transfer will take over a month via the current AWS Direct Connect connection your company has set up. Which AWS tool should you use?
A) Establish additional Direct Connect connections.
B) Use Data Pipeline to migrate the data in bulk to S3.
C) Use Kinesis Firehose to stream all new and existing data into S3.
D) Snowball
ANSWER18:
D
Notes/Hint18:
As a general rule, if it takes more than one week to upload your data to AWS using the spare capacity of your existing Internet connection, then you should consider using Snowball. For example, if you have a 100 Mb connection that you can solely dedicate to transferring your data and need to transfer 100 TB of data, it takes more than 100 days to complete a data transfer over that connection. You can make the same transfer by using multiple Snowballs in about a week.
Question 19: You currently have an on-premises Oracle database and have decided to leverage AWS and use Aurora. You need to do this as quickly as possible. How do you achieve this?
A) It is not possible to migrate an on-premises database to AWS at this time.
B) Use AWS Data Pipeline to create a target database, migrate the database schema, set up the data replication process, initiate the full load and a subsequent change data capture and apply, and conclude with a switchover of your production environment to the new database once the target database is caught up with the source database.
C) Use AWS Database Migration Services and create a target database, migrate the database schema, set up the data replication process, initiate the full load and a subsequent change data capture and apply, and conclude with a switch-over of your production environment to the new database once the target database is caught up with the source database.
D) Use AWS Glue to crawl the on-premises database schemas and then migrate them into AWS with Data Pipeline jobs.
DMS can efficiently support this sort of migration using the steps outlined. While AWS Glue can help you crawl schemas and store metadata on them inside of Glue for later use, it isn’t the best tool for actually transitioning a database over to AWS itself. Similarly, while Data Pipeline is great for ETL and ELT jobs, it isn’t the best option to migrate a database over to AWS.
Question 20: A financial company uses Amazon EMR for its analytics workloads. During the company’s annual security audit, the security team determined that none of the EMR clusters’ root volumes are encrypted. The security team recommends the company encrypt its EMR clusters’ root volume as soon as possible. Which solution would meet these requirements?
A) Enable at-rest encryption for EMR File System (EMRFS) data in Amazon S3 in a security configuration. Re-create the cluster using the newly created security configuration.
B) Specify local disk encryption in a security configuration. Re-create the cluster using the newly created security configuration.
C) Detach the Amazon EBS volumes from the master node. Encrypt the EBS volume and attach it back to the master node.
D) Re-create the EMR cluster with LZO encryption enabled on all volumes.
ANSWER20:
B
Notes/Hint20:
Local disk encryption can be enabled as part of a security configuration to encrypt root and storage volumes.
Question 21: A company has a clickstream analytics solution using Amazon Elasticsearch Service. The solution ingests 2 TB of data from Amazon Kinesis Data Firehose and stores the latest data collected within 24 hours in an Amazon ES cluster. The cluster is running on a single index that has 12 data nodes and 3 dedicated master nodes. The cluster is configured with 3,000 shards and each node has 3 TB of EBS storage attached. The Data Analyst noticed that the query performance of Elasticsearch is sluggish, and some intermittent errors are produced by the Kinesis Data Firehose when it tries to write to the index. Upon further investigation, there were occasional JVMMemoryPressure errors found in Amazon ES logs.
What should be done to improve the performance of the Amazon Elasticsearch Service cluster?
A) Improve the cluster performance by increasing the number of master nodes of Amazon Elasticsearch.
B) Improve the cluster performance by increasing the number of shards of the Amazon Elasticsearch index.
C) Improve the cluster performance by decreasing the number of data nodes of Amazon Elasticsearch.
D) Improve the cluster performance by decreasing the number of shards of the Amazon Elasticsearch index.
ANSWER21:
D
Notes/Hint21:
“Amazon Elasticsearch Service (Amazon ES) is a managed service that makes it easy to deploy, operate, and scale Elasticsearch clusters in AWS Cloud. Elasticsearch is a popular open-source search and analytics engine for use cases such as log analytics, real-time application monitoring, and clickstream analysis. With Amazon ES, you get direct access to the Elasticsearch APIs; existing code and applications work seamlessly with the service.
Each Elasticsearch index is split into some number of shards. You should decide the shard count before indexing your first document. The overarching goal of choosing a number of shards is to distribute an index evenly across all data nodes in the cluster. However, these shards shouldn’t be too large or too numerous.
A good rule of thumb is to try to keep a shard size between 10 – 50 GiB. Large shards can make it difficult for Elasticsearch to recover from failure, but because each shard uses some amount of CPU and memory, having too many small shards can cause performance issues and out of memory errors. In other words, shards should be small enough that the underlying Amazon ES instance can handle them, but not so small that they place needless strain on the hardware. Therefore the correct answer is: Improve the cluster performance by decreasing the number of shards of Amazon Elasticsearch index.
Question 26: Which service uses continuous data replication with high availability to consolidate databases into a petabyte-scale data warehouse by streaming data to amazon Redshift and Amazon S3?
Question 29: During your data preparation stage, the raw data has been enriched to support additional insights. You need to improve query performance and reduce costs of the final analytics solution.
Which data formats meet these requirements (SELECT TWO)
Question 30: Your small start-uo company is developing a data analytics solution. You need to clean and normalize large datasets, but you do not have developers with the skill set to write custom scripts. Which tool will help efficiently design and run the data preparation activities?
ANSWER30:
B
Notes/Hint30:
AWS Glue DataBrew
To be able to run analytics, build reports, or apply machine learning, you need to be sure the data you’re using is clean and in the right format. This data preparation step requires data analysts and data scientists to write custom code and perform many manual activities. When cleaning and normalizing data, it is helpful to first review the dataset to understand which possible values are present. Simple visualizations are helpful for determining whether correlations exist between the columns.
AWS Glue DataBrew is a visual data preparation tool that helps you clean and normalize data up to 80% faster so you can focus more on the business value you can get. DataBrew provides a visual interface that quickly connects to your data stored in Amazon S3, Amazon Redshift, Amazon Relational Database Service (RDS), any JDBC-accessible data store, or data indexed by the AWS Glue Data Catalog. You can then explore the data, look for patterns, and apply transformations. For example, you can apply joins and pivots, merge different datasets, or use functions to manipulate data.
Question 30: In which scenario would you use AWS Glue jobs?
A) Analyze data in real-time as data comes into the data lake
B) Transform data in real-time as data comes into the data lake
C) Analyze data in batches on schedule or on demand
D) Transform data in batches on schedule or on demand.
ANSWER30:
D
Notes/Hint30:
An AWS Glue job encapsulates a script that connects to your source data, processes it, and then writes it out to your data target. Typically, a job runs extract, transform, and load (ETL) scripts. Jobs can also run general-purpose Python scripts (Python shell jobs.) AWS Glue triggers can start jobs based on a schedule or event, or on demand. You can monitor job runs to understand runtime metrics such as completion status, duration, and start tim
Question 31: Your data resides in multiple data stores, including Amazon S3, Amazon RDS, and Amazon DynamoDB. You need to efficiently query the combined datasets.
Which tool can achieve this, using a single query, without moving data?
A) Amazon Athena Federated Query
B) Amazon Redshift Query Editor
C) SQl Workbench
D) AWS Glue DataBrew
ANSWER31:
A
Notes/Hint31:
With Amazon Athena Federated Query, you can run SQL queries across a variety of relational, non-relational, and custom data sources. You get a unified way to run SQL queries across various data stores.
Athena uses data source connectors that run on AWS Lambda to run federated queries. A data source connector is a piece of code that can translate between your target data source and Athena. You can think of a connector as an extension of Athena’s query engine. Pre-built Athena data source connectors exist for data sources like Amazon CloudWatch Logs, Amazon DynamoDB, Amazon DocumentDB, Amazon RDS, and JDBC-compliant relational data sources such MySQL and PostgreSQL under the Apache 2.0 license. You can also use the Athena Query Federation SDK to write custom connectors. To choose, configure, and deploy a data source connector to your account, you can use the Athena and Lambda consoles or the AWS Serverless Application Repository. After you deploy data source connectors, the connector is associated with a catalog that you can specify in SQL queries. You can combine SQL statements from multiple catalogs and span multiple data sources with a single query.
Question 32: Which benefit do you achieve by using AWS Lake Formation to build data lakes?
A) Build data lakes quickly
B) Simplify security management
C) Provide self-service access to data
D) All of the above
ANSWER32:
D
Notes/Hint32:
Build data lakes quickly
With Lake Formation, you can move, store, catalog, and clean your data faster. You simply point Lake Formation at your data sources, and Lake Formation crawls those sources and moves the data into your new Amazon S3 data lake. Lake Formation organizes data in S3 around frequently used query terms and into right-sized chunks to increase efficiency. Lake Formation also changes data into formats like Apache Parquet and ORC for faster analytics. In addition, Lake Formation has built-in machine learning to deduplicate and find matching records (two entries that refer to the same thing) to increase data quality.
Simplify security management
You can use Lake Formation to centrally define security, governance, and auditing policies in one place, versus doing these tasks per service. You can then enforce those policies for your users across their analytics applications. Your policies are consistently implemented, eliminating the need to manually configure them across security services like AWS Identity and Access Management (AWS IAM) and AWS Key Management Service (AWS KMS), storage services like Amazon S3, and analytics and machine learning services like Amazon Redshift, Amazon Athena, and (in beta) Amazon EMR for Apache Spark. This reduces the effort in configuring policies across services and provides consistent enforcement and compliance.
Provide self-service access to data
With Lake Formation, you build a data catalog that describes the different available datasets along with which groups of users have access to each. This makes your users more productive by helping them find the right dataset to analyze. By providing a catalog of your data with consistent security enforcement, Lake Formation makes it easier for your analysts and data scientists to use their preferred analytics service. They can use Amazon EMR for Apache Spark (in beta), Amazon Redshift, or Amazon Athena on diverse datasets that are now housed in a single data lake. Users can also combine these services without having to move data between silos.
Question 33: What are the three stages to set up a data lake using AWS Lake Formation? (SELECT THREE)
A) Register the storage location
B) Create a database
C) Populate the database
D) Grant permissions
ANSWER33:
A B and D
Notes/Hint33:
Register the storage location
Lake Formation manages access to designated storage locations within Amazon S3. Register the storage locations that you want to be part of the data lake.
Create a database
Lake Formation organizes data into a catalog of logical databases and tables. Create one or more databases and then automatically generate tables during data ingestion for common workflows.
Grant permissions
Lake Formation manages access for IAM users, roles, and Active Directory users and groups via flexible database, table, and column permissions. Grant permissions to one or more resources for your selected users.
Question 34: Which of the following AWS Lake Formation tasks are performed by the AWS Glue service? (SELECT THREE)
A) ETL code creation and job monitoring
B) Blueprints to create workflows
C) Data catalog and serverless architecture
D) Simplify securty management
ANSWER34:
A B and C
Notes/Hint34:
Lake Formation leverages a shared infrastructure with AWS Glue, including console controls, ETL code creation and job monitoring, blueprints to create workflows for data ingest, the same data catalog, and a serverless architecture. While AWS Glue focuses on these types of functions, Lake Formation encompasses all AWS Glue features AND provides additional capabilities designed to help build, secure, and manage a data lake. See the AWS Glue features page for more de
Question 35: A digital media customer needs to quickly build a data lake solution for the data housed in a PostgreSQL database. As a solutions architect, what service and feature would meet this requirement?
A) Copy PostgreSQL data to an Amazon S3 bucket and build a data lake using AWS Lake Formation
B) Use AWS Lake Formation blueprints
C) Build a data lake manually
D) Build an analytics solution by directly accessing the database.
ANSWER35:
B
Notes/Hint35:
A blueprint is a data management template that enables you to easily ingest data into a data lake. Lake Formation provides several blueprints, each for a predefined source type, such as a relational database or AWS CloudTrail logs. From a blueprint, you can create a workflow. Workflows consist of AWS Glue crawlers, jobs, and triggers that are generated to orchestrate the loading and update of data. Blueprints take the data source, data target, and schedule as input to configure the workflow.
Question 36: AWS Lake Formation has a set of suggested personas and IAM permissions. Which is a required persona?
A) Data lake administrator
B) Data engineer
C) Data analyst
D) Business analyst
ANSWER36:
A
Notes/Hint36:
Data lake administrator (Required)
A user who can register Amazon S3 locations, access the Data Catalog, create databases, create and run workflows, grant Lake Formation permissions to other users, and view AWS CloudTrail logs. The user has fewer IAM permissions than the IAM administrator but enough to administer the data lake. Cannot add other data lake administrators.
Data engineer (Optional) A user who can create and run crawlers and workflows and grant Lake Formation permissions on the Data Catalog tables that the crawlers and workflows create.
Data analyst (Optional) A user who can run queries against the data lake using, for example, Amazon Athena. The user has only enough permissions to run queries.
Business analyst (Optional) Generally, an end-user application specific persona that would query data and resource using a workflow role.
Question 37: Which three types of blueprints does AWS Lake Formation support? (SELECT THREE)
AWS Lake Formation blueprints simplify and automate creating workflows. Lake Formation provides the following types of blueprints:
• Database snapshot – Loads or reloads data from all tables into the data lake from a JDBC source. You can exclude some data from the source based on an exclude pattern.
• Incremental database – Loads only new data into the data lake from a JDBC source, based on previously set bookmarks. You specify the individual tables in the JDBC source database to include. For each table, you choose the bookmark columns and bookmark sort order to keep track of data that has previously been loaded. The first time that you run an incremental database blueprint against a set of tables, the workflow loads all data from the tables and sets bookmarks for the next incremental database blueprint run. You can therefore use an incremental database blueprint instead of the database snapshot blueprint to load all data, provided that you specify each table in the data source as a paramete
• Log file – Bulk loads data from log file sources, including AWS CloudTrail, Elastic Load Balancing logs, and Application Load Balancer logs.
Question 38: Which one of the following is the best description of the capabilities of Amazon QuickSight?
A) Automated configuration service build on AWS Glue
B) Fast, serverless, business intelligence service
C) Fast, simple, cost-effective data warehousing
D) Simple, scalable, and serverless data integration
ANSWER38:
B C and D
Notes/Hint38:
B. Scalable, serverless business intelligence service is the correct choice.
See the brief descriptions of several AWS Analytics services below:
AWS Lake Formation Build a secure data lake in days using Glue blueprints and workflows
Amazon QuickSight Scalable, serverless, embeddable, ML-powered BI Service built for the cloud
Amazon Redshift Analyze all of your data with the fastest and most widely used cloud data warehouse
AWS Glue Simple, scalable, and serverless data integration
Question 39: Which benefits are provided by Amazon Redshift? (Select TWO)
A) Analyze Data stored in your data lake
B) Maintain performance at scale
C) Focus effort on Data warehouse administration
D) Store all the data to meet analytics need
E) Amazon Redshift includes enterprise-level security and compliance features.
ANSWER38:
A and B
Notes/Hint38:
A is correct – With Amazon Redshift, you can analyze all your data, including exabytes of data stored in your Amazon S3 data lake.
B is correct – Amazon Redshift provides consistent performance at scale.
• C is incorrect – Amazon Redshift is a fully managed data warehouse solution. It includes automations to reduce the administrative overhead traditionally associated with data warehouses. When using Amazon Redshift, you can focus your development effort on strategic data analytics solutions.
• D is incorrect – With Amazon Redshift features—such as Amazon Redshift Spectrum, materialized views, and federated query—you can analyze data where it is stored in your data lake or AWS databases. This capability provides flexibility to meet new analytics requirements without the cost, time, or complexity of moving large volumes of data between solutions.
• Answer E is incorrect – Amazon Redshift includes enterprise-level security and compliance features.
Djamga Data Sciences Big Data – Data Analytics Youtube Playlist
Data Scientist (n.): Person who is better at statistics than any software engineer and better at software engineering than any statistician. – Josh Wills
Data scientists apply sophisticated quantitative and computer science skills to both structure and analyze massive stores or continuous streams of unstructured data, with the intent to derive insights and prescribe action. – Burtch Works Data Science Salary Survey, May 2018
More than anything, what data scientists do is make discoveries while swimming in data… In a competitive landscape where challenges keep changing and data never stop flowing, data scientists help decision makers shift from ad hoc analysis to an ongoing conversation with data. – Data Scientist: The Sexiest Job of the 21st Century, Harvard Business Review
Do All Data Scientists Hold Graduate Degrees?
Data scientists are highly educated. With exceedingly rare exception, every data scientist holds at least an undergraduate degree. 91% of data scientists in 2018 held advanced degrees. The remaining 9% all held undergraduate degrees. Furthermore,
25% of data scientists hold a degree in statistics or mathematics,
20% have a computer science degree,
an additional 20% hold a degree in the natural sciences, and
18% hold an engineering degree.
The remaining 17% of surveyed data scientists held degrees in business, social science, or economics.
How Are Data Scientists Different From Data Analysts?
Broadly speaking, the roles differ in scope: data analysts build reports with narrow, well-defined KPIs. Data scientists often to work on broader business problems without clear solutions. Data scientists live on the edge of the known and unknown.
We’ll leave you with a concrete example: A data analyst cares about profit margins. A data scientist at the same company cares about market share.
How Is Data Science Used in Medicine?
Data science in healthcare best translates to biostatistics. It can be quite different from data science in other industries as it usually focuses on small samples with several confounding variables.
How Is Data Science Used in Manufacturing?
Data science in manufacturing is vast; it includes everything from supply chain optimization to the assembly line.
What are data scientists paid?
Most people are attracted to data science for the salary. It’s true that data scientists garner high salaries compares to their peers. There is data to support this: The May 2018 edition of the BurtchWorks Data Science Salary Survey, annual salary statistics were
Note the above numbers do not reflect total compensation which often includes standard benefits and may include company ownership at high levels.
How will data science evolve in the next 5 years?
Will AI replace data scientists?
What is the workday like for a data scientist?
It’s common for data scientists across the US to work 40 hours weekly. While company culture does dictate different levels of work life balance, it’s rare to see data scientists who work more than they want. That’s the virtue of being an expensive resource in a competitive job market.
How do I become a Data Scientist?
The roadmap given to aspiring data scientists can be boiled down to three steps:
Earning an undergraduate and/or advanced degree in computer science, statistics, or mathematics,
Building their portfolio of SQL, Python, and R skills, and
Getting related work experience through technical internships.
All three require a significant time and financial commitment.
There used to be a saying around datascience: The road into a data science starts with two years of university-level math.
What Should I Learn? What Order Do I Learn Them?
This answer assumes your academic background ends with a HS diploma in the US.
Python
Differential Calculus
Integral Calculus
Multivariable Calculus
Linear Algebra
Probability
Statistics
Some follow up questions and answers:
Why Python first?
Python is a general purpose language. R is used primarily by statisticians. In the likely scenario that you decide data science requires too much time, effort, and money, Python will be more valuable than your R skills. It’s preparing you to fail, sure, but in the same way a savings account is preparing you to fail.
When do I start working with data?
You’ll start working with data when you’ve learned enough Python to do so. Whether you’ll have the tools to have any fun is a much more open-ended question.
How long will this take me?
Assuming self-study and average intelligence, 3-5 years from start to finish.
How Do I Learn Python?
If you don’t know the first thing about programming, start with MIT’s course in the curated list.
These modules are the standard tools for data analysis in Python:
Data Scientist with Python Career Track | DataCamp The first courses are free, but unlimited access costs $29/month. Users usually report a positive experience, and it’s one of the better hands-on ways to learn Python.
Data Scientist with R Career Track | DataCamp The first courses are free, but unlimited access costs $29/month. Users usually report a positive experience, and it’s one of the few hands-on ways to learn R.
R Inferno Learners with a CS background will appreciate this free handbook explaining how and why R behaves the way that it does.
How Do I Learn SQL?
Prioritize the basics of SQL. i.e. when to use functions like POW, SUM, RANK; the computational complexity of the different kinds of joins.
Concepts like relational algebra, when to use clustered/non-clustered indexes, etc. are useful, but (almost) never come up in interviews.
You absolutely do not need to understand administrative concepts like managing permissions.
Finally, there are numerous query engines and therefore numerous dialects of SQL. Use whichever dialect is supported in your chosen resource. There’s not much difference between them, so it’s easy to learn another dialect after you’ve learned one.
Fortunately (or unfortunately), calculus is the lament of many students, and so resources for it are plentiful. Khan Academy mimics lectures very well, and Paul’s Online Math Notes are a terrific reference full of practice problems and solutions.
Calculus, however, is not just calculus. For those unfamiliar with US terminology,
Calculus I is differential calculus.
Calculus II is integral calculus.
Calculus III is multivariable calculus.
Calculus IV is differential equations.
Differential and integral calculus are both necessary for probability and statistics, and should be completed first.
Multivariable calculus can be paired with linear algebra, but is also required.
Differential equations is where consensus falls apart. The short it is, they’re all but necessary for mathematical modeling, but not everyone does mathematical modeling. It’s another tool in the toolbox.
Curated Threads & Resources about Data Science and Data Analytics
Probability is not friendly to beginners. Definitions are rooted in higher mathematics, notation varies from source to source, and solutions are frequently unintuitive. Probability may present the biggest barrier to entry in data science.
It’s best to pick a single primary source and a community for help. If you can spend the money, register for a university or community college course and attend in person.
Practice questions on Leetcode which has both SQL and traditional data structures/algorithm questions
Review Brilliant for math and statistics questions.
SQL Zoo and Mode Analytics both offer various SQL exercises you can solve in your browser.
Tips:
Before you start coding, read through all the questions. This allows your unconscious mind to start working on problems in the background.
Start with the hardest problem first, when you hit a snag, move to the simpler problem before returning to the harder one.
Focus on passing all the test cases first, then worry about improving complexity and readability.
If you’re done and have a few minutes left, go get a drink and try to clear your head. Read through your solutions one last time, then submit.
It’s okay to not finish a coding challenge. Sometimes companies will create unreasonably tedious coding challenges with one-week time limits that require 5–10 hours to complete. Unless you’re desperate, you can always walk away and spend your time preparing for the next interview.
Remember, interviewing is a skill that can be learned, just like anything else. Hopefully, this article has given you some insight on what to expect in a data science interview loop.
The process also isn’t perfect and there will be times that you fail to impress an interviewer because you don’t possess some obscure piece of knowledge. However, with repeated persistence and adequate preparation, you’ll be able to land a data science job in no time!
What does the Airbnb data science interview process look like? [Coming soon]
What does the Facebook data science interview process look like? [Coming soon]
What does the Uber data science interview process look like? [Coming soon]
What does the Microsoft data science interview process look like? [Coming soon]
What does the Google data science interview process look like? [Coming soon]
What does the Netflix data science interview process look like? [Coming soon]
What does the Apple data science interview process look like? [Coming soon]
Real life enterprise databases are orders of magnitude more complex than the “customers, products, orders” examples used as teaching tools. SQL as a language is actually, IMO, a relatively simple language (the db administration component can get complex, but mostly data scientists aren’t doing that anyways). SQL is an incredibly important skill though for any DS role. I think when people emphasize SQL, what they really are talking about is the ability to write queries that interrogate the data and discover the nuances behind how it is collected and/or manipulated by an application before it is written to the dB. For example, is the employee’s phone number their current phone number or does the database store a history of all previous phone numbers? Critically important questions for understanding the nature of your data, and it doesn’t necessarily deal with statistics! The level of syntax required to do this is not that sophisticated, you can get pretty damn far with knowledge of all the joins, group by/analytical functions, filtering and nesting queries. In many cases, the data is too large to just select * and dump into a csv to load into pandas, so you start with SQL against the source. In my mind it’s more important for “SQL skills” to know how to generate hypotheses (that will build up to answering your business question) that can be investigated via a query than it is to be a master of SQL’s syntax. Just my two cents though!
Data Source: Made in Google Sheets using data from this USA Today article (for the number of arrests by arrestee’s home state) and this spreadsheet of the results of the 2020 Census (for the population of each state and DC in 2020, which was used as the denominator in calculating arrests/million people).
A data warehouse is specially designed for data analytics, which identifies relationships and trends across large amounts of data. A database is used to capture and store data, such as the details of a transaction. Unlike a data warehouse, a data lake is a centralized repository for structured, semi-structured, and unstructured data. A data warehouse organizes data in a tabular format (or schema) that enables SQL queries on the data. But not all applications require data to be in tabular format. Some applications can access data in the data lake even if it is “semi-structured” or unstructured. These include big data analytics, full-text search, and machine learning.
An AWS data lake only has a storage charge for the data. No servers are necessary for the data to be stored and accessed. In the case of Amazon Athena, also, there are no additional charges for processing. Data warehouse enable fast queries of structured data from transactional systems for batch reports, business intelligence, and visualization use cases. A data lake stores data without regard to its structure. Data scientists, data analysts, and business analysts use the data lake. They support use cases such as machine learning, predictive analytics, and data discovery and profiling.
Data definition language (DDL) refers to the subset of SQL commands that define data structures and objects such as databases, tables, and views. DDL commands include the following:
• CREATE: used to create a new object.
• DROP: used to delete an object.
• ALTER: used to modify an object.
• RENAME: used to rename an object.
• TRUNCATE: used to remove all rows from a table without deleting the table itself.
Businesses are responsible to identify and limit disclosure of sensitive data such as personally identifiable information (PII) or proprietary information. Identifying and masking sensitive information is time consuming, and becomes more complex in data lakes with various data sources and formats and broad user access to published data sets.
Amazon Macie is a fully managed data security and privacy service that uses machine learning and pattern matching to discover sensitive data in AWS. Macie includes a set of managed data identifiers which automatically detect common types of sensitive data. Examples of managed data identifiers include keywords, credentials, financial information, health information, and PII. You can also configure custom data identifiers using keywords or regular expressions to highlight organizational proprietary data, intellectual property, and other specific scenarios. You can develop security controls that operate at scale to monitor and remediate risk automatically when Macie detects sensitive data. You can use AWS Lambda functions to automatically turn on encryption for an Amazon S3 bucket where Macie detects sensitive data. Or automatically tag datasets containing sensitive data, for inclusion in orchestrated data transformations or audit reports.
Amazon Macie can be integrated into the data ingestion and processing steps of your data pipeline. This approach avoids inadvertent disclosures in published data sets by detecting and addressing the sensitive data as it is ingested and processed. Building the automated detection and processing of sensitive data into your ETL pipelines simplifies and standardizes handling of sensitive data at scale.
AWS Glue DataBrew is a visual data preparation tool that simplifies cleaning and normalizing datasets in preparation for use in analytics and machine learning.
• Profile data quality, identifying patterns and automatically detecting anomalies.
• Clean and normalize data using over 250 pre-built transformations, without writing code.
• Visually map the lineage of your data to understand data sources and transformation history.
• Save data cleaning and normalization workflows for automatic application to new data.
Data processed in AWS Glue DataBrew is immediately available for use in analytics and machine learning projects.
Learn more about the built-in transformations available in AWS Glue DataBrew in the Recipe actions reference: https://docs.aws.amazon.com/databrew/latest/dg/recipe-actions-reference.html
AWS Glue is a fully managed ETL (extract, transform, and load) service that makes it simple and cost-effective to categorize your data, clean it, enrich it, and move it reliably between various data stores and data streams. AWS Glue consists of a central metadata repository known as the AWS Glue Data Catalog, an ETL engine that automatically generates Python or Scala code, and a flexible scheduler that handles dependency resolution, job monitoring, and retries. AWS Glue can run your ETL jobs as new data arrives. For example, you can use an AWS Lambda function to trigger your ETL jobs to run as soon as new data becomes available in Amazon S3. You can also register this new dataset in the
AWS Glue Data Catalog as part of your ETL jobs.
AWS Glue is serverless, so there’s no infrastructure to set up or manage.
AWS Glue Data Catalog The AWS Glue Data Catalog provides a uniform repository where disparate systems can store and find metadata to keep track of data in data silos, and use that metadata to query and transform the data. Once the data is cataloged, it is immediately available for search and query using Amazon Athena, Amazon EMR, and Amazon Redshift Spectrum.
You can use AWS Identity and Access Management (IAM) policies to control access to the data sources managed by the AWS Glue Data Catalog. The Data Catalog also provides comprehensive audit and governance capabilities, with schema-change tracking and data access controls.
AWS Glue crawler
AWS Glue crawlers can scan data in all kinds of repositories, classify it, extract schema information from it, and store the metadata automatically in the AWS Glue Data Catalog.
AWS Glue ETL
AWS Glue can run your ETL jobs as new data arrives. For example, you can use an AWS Lambda function to trigger your ETL jobs to run as soon as new data becomes available in Amazon S3. You can also register this new dataset in the AWS Glue Data Catalog as part of your ETL jobs.
AWS Glue Studio
AWS Glue Studio provides a graphical interface to create, run, and monitor extract, transform, and load (ETL) jobs in AWS Glue. You can visually compose data transformation workflows and seamlessly run them on AWS Glue’s Apache Spark-based serverless ETL engine. AWS Glue Studio also offers tools to monitor ETL workflows and validate that they are operating as intended.
Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to set up or manage, and you can start analyzing data immediately. You don’t even need to load your data into Athena, it works directly with data stored in S3. To get started, just log into the Amazon Athena console, define your schema, and start querying. Athena uses Presto with full standard SQL support. It works with a variety of standard data formats, including CSV, JSON, ORC, Apache Parquet and Avro. While Athena is ideal for quick, ad-hoc querying, it can also handle complex analysis, including large joins, window functions, and arrays.
Amazon Athena helps you analyze data stored in Amazon S3. You can use Athena to run ad-hoc queries using ANSI SQL, without the need to aggregate or load the data into Athena. It can process unstructured, semi-structured, and structured datasets. Examples include CSV, JSON, Avro or columnar data formats such as Apache Parquet and Apache ORC. Athena integrates with Amazon QuickSight for easy visualization. You can also use Athena to generate reports or to explore data with business intelligence tools or SQL clients, connected via an ODBC or JDBC driver.
The tables and databases that you work with in Athena to run queries are based on metadata. Metadata is data about the underlying data in your dataset. How that metadata describes your dataset is called the schema. For example, a table name, the column names in the table, and the data type of each column are schema, saved as metadata, that describe an underlying dataset. In Athena, we call a system for organizing metadata a data catalog or a metastore. The combination of a dataset and the data catalog that describes it is called a data source.
The relationship of metadata to an underlying dataset depends on the type of data source that you work with. Relational data sources like MySQL, PostgreSQL, and SQL Server tightly integrate the metadata with the dataset. In these systems, the metadata is most often written when the data is written. Other data sources, like those built using Hive, allow you to define metadata on-the-fly when you read the dataset. The dataset can be in a variety of formats; for example, CSV, JSON, Parquet, or Avro.
Lake Formation is a fully managed service that enables data engineers, security officers, and data analysts to build, secure, manage, and use your data lake
To build your data lake in AWS Lake Formation, you must register an Amazon S3 location as a data lake. The Lake Formation service must have permission to write to the AWS Glue Data Catalog and to Amazon S3 locations in the data lake.
Next, identify the data sources to be ingested. AWS Lake formation can move data into your data lake from existing Amazon S3 data stores. Lake Formation can collect and organize datasets, such as logs from AWS CloudTrail, AWS CloudFront, detailed billing reports, or Elastic Load Balancing. You can ingest bulk or incremental datasets from relational, NoSQL, or non-relational databases. Lake Formation can ingest data from databases running in Amazon RDS or hosted in Amazon EC2. You can also ingest data from on-premises databases using Java Database Connectivity JDBC connectors. You can use custom AWS Glue jobs to load data from other databases or to ingest streaming data using Amazon Kinesis or Amazon DynamoDB.
AWS Lake Formation manages AWS Glue crawlers, AWS Glue ETL jobs, the AWS Glue Data Catalog, security settings, and access control:
• Lake Formation is an automated build environment based on AWS Glue.
• Lake Formation coordinates AWS Glue crawlers to identify datasets within the specified data stores and collect metadata for each dataset
• Lake Formation can perform transformations on your data, such as rewriting and organizing data into a consistent, analytics-friendly format. Lake Formation creates transformation templates and schedules AWS Glue jobs to prepare and optimize your data for analytics. Lake Formation also helps clean your data using FindMatches, an ML-based deduplication transform. AWS Glue jobs encapsulate scripts, such as ETL scripts, which connect to source data, process it, and write it out to a data target. AWS Glue triggers can start jobs based on a schedule or event, or on demand. AWS Glue workflows orchestrate AWS ETL jobs, crawlers, and triggers. You can define a workflow manually or use a blueprint based on commonly ingested data source types.
• The AWS Glue Data Catalog within the data lake persistently stores the metadata from raw and processed datasets. Metadata about data sources and targets is in the form of databases and tables. Tables store information about the underlying data, including schema information, partition information, and data location. Databases are collections of tables. Each AWS account has one data catalog per AWS Region.
• Lake Formation provides centralized access controls for your data lake, including security policy-based rules for users and applications by role. You can authenticate the users and roles using AWS IAM. Once the rules are defined, Lake Formation enforces them with table-and column-level granularity for users of Amazon Redshift Spectrum and Amazon Athena. Rules are enforced at the table-level in AWS Glue, which is normally accessed for administrators.
• Lake Formation leverages the encryption capabilities of Amazon S3 for data in the data lake. This approach provides automatic server-side encryption with keys managed by the AWS Key Management Service (KMS). S3 encrypts data in transit when replicating across Regions. You can separate accounts for source and destination Regions to further protect your data
Amazon QuickSight is a cloud-scale business intelligence (BI) service. In a single data dashboard, QuickSight gives decision-makers the opportunity to explore and interpret information in an interactive visual environment. QuickSight can include AWS data, third-party data, big data, spreadsheet data, SaaS data, B2B data, and more. QuickSight delivers fast and responsive query performance by using a robust in-memory engine (SPICE).
Scale from tens to tens of thousands of users
Amazon QuickSight has a serverless architecture that automatically scales to tens of thousands of users without the need to setup, configure, or manage your own servers.
Embed BI dashboards in your applications
With QuickSight, you can quickly embed interactive dashboards into your applications, websites, and portals.
Access deeper insights with Machine Learning
QuickSight leverages the proven machine learning (ML) capabilities of AWS. BI teams can perform advanced analytics without prior data science experience.
Ask questions of your data, receive answers
With QuickSight, you can quickly get answers to business questions asked in natural language with QuickSight’s new ML-powered natural language query capability, Q.
SPICE is the Super-fast, Parallel, In-memory Calculation Engine in QuickSight. SPICE is engineered to rapidly perform advanced calculations and serve data. The storage and processing capacity available in SPICE speeds up the analytical queries that you run against your imported data. By using SPICE, you save time because you don’t need to retrieve the data every time that you change an analysis or update a visual.
When you import data into a dataset rather than using a direct SQL query, it becomes SPICE data because of how it’s stored. SPICE is the Amazon QuickSight Super-fast, Parallel, In-memory Calculation Engine. It’s engineered to rapidly perform advanced calculations and serve data. In Enterprise edition, data stored in SPICE is encrypted at rest.
When you create or edit a dataset, you choose to use either SPICE or a direct query, unless the dataset contains uploaded files. Importing (also called ingesting) your data into SPICE can save time and money:
• Your analytical queries process faster.
• You don’t need to wait for a direct query to process.
• Data stored in SPICE can be reused multiple times without incurring additional costs. If you use a data source that charges per query, you’re charged for querying the data when you first create the dataset and later when you refresh the dataset.
You can use AWS services as building blocks to build serverless data lakes and analytics pipelines. You can apply best practices on how to ingest, store, transform, and analyze structured and unstructured data at scale. Achieve the scale without needing to manage any storage or compute infrastructure. A decoupled, component-driven architecture allows you to start small and scale out slowly. You can quickly add new purpose-built components to one of six architecture layers to address new requirements and data sources.
This data lake-centric architecture can support business intelligence (BI) dashboarding, interactive SQL queries, big data processing, predictive analytics, and machine learning use cases.
• The ingestion layer includes protocols to support ingestion of structured, unstructured, or streaming data from a variety of sources.
• The storage layer provides durable, scalable, secure, and cost-effective storage of datasets across ingestion and processing.
• The landing zone stores data as ingested.
• Data engineers run initial quality checks to validate and cleanse data in the landing zone, producing the raw dataset.
• The processing layer creates curated datasets by further cleansing, normalizing, standardizing, and enriching data from the raw zone. The curated dataset is typically stored in formats that support performant and cost-effective access by the consumption layer.
• The catalog layer stores business and technical metadata about the datasets hosted in the storage layer.
• The consumption layer contains functionality for Search, Analytics, and Visualization. It integrates with the data lake storage, cataloging, and security layers. This integration supports analysis methods such as SQL, batch analytics, BI dashboards, reporting, and ML.
• The security and monitoring layer protects data within the storage layer and other resources in the data lake. This layer includes access control, encryption, network protection, usage monitoring, and auditing.
The main challenge with a data lake architecture is that raw data is stored with no oversight of the contents. To make the data usable, you must have defined mechanisms to catalog and secure the data. Without these mechanisms, data cannot be found or trusted, resulting in a “data swamp.” Meeting the needs of diverse stakeholders requires data lakes to have governance, semantic consistency, and access controls.
The Analytics Lens for the AWS Well-Architected Framework covers common analytics applications scenarios, including data lakes. It identifies key elements to help you architect your data lake according to best practices, including the following configuration notes:
• Decide on a location for data lake ingestion (that is, an S3 bucket). Select a frequency and isolation mechanism that meets your business needs.
• For Tier 2 Data, partition the data with keys that align to common query filter
. This enables pruning by common analytics tools that work on raw data files and increases performance
• Choose optimal file sizes to reduce Amazon S3 round trips during compute environment ingestion. Recommended: 512 MB – 1 GB in a columnar format (ORC/Parquet) per partition.
• Perform frequent scheduled compactions that align to the optimal file sizes noted previously. For example, compact into daily partitions if hourly files are too small.
• For data with frequent updates or deletes (that is, mutable data), either: o Temporarily store replicated data to a database like Amazon Redshift, Apache Hive, or Amazon RDS. Once the data becomes static, and then offload it to Amazon S3. Or, o Append the data to delta files per partition and compact it on a scheduled basis. You can use AWS Glue or Apache Spark on Amazon EMR for this processing.
With Tier 2 and Tier 3 Data being stored in Amazon S3, partition data using a high cardinality key. This is honored by Presto, Apache Hive, and Apache Spark and improves the query filter performance on that key
• Sort data in each partition with a secondary key that aligns to common filter queries. This allows query engines to skip files and get to requested data faster. For more information on the Analytics Lens for the AWS Well-Architected Framework, visit https://docs.aws.amazon.com/wellarchitected/latest/analytics-lens/data-lake.html
References:
For additional information on AWS data lakes and data analytics architectures, visit:
• AWS Well-Architected: Learn, measure, and build using architectural best practices: https://aws.amazon.com/architecture/well-architected
• AWS Lake Formation: Build a secure data lake in days: https://aws.amazon.com/lake-formation
• Getting Started with Amazon S3: https://aws.amazon.com/s3/getting-started
• Security in AWS Lake Formation: https://docs.aws.amazon.com/lake-formation/latest/dg/security.html
AWS Lake Formation: How It Works: https://docs.aws.amazon.com/lake-formation/latest/dg/how-it-works.html
• AWS Lake Formation Dashboard: https://us-west-2.console.aws.amazon.com/lakeformation
• Data Lake Storage on AWS: https://aws.amazon.com/products/storage/data-lake-storage/
• Building Big Data Storage Solutions (Data Lakes) for Maximum Flexibility: https://docs.aws.amazon.com/whitepapers/latest/building-data-lakes/building-data-lake-aws.html
• Data Ingestion Methods: https://docs.aws.amazon.com/whitepapers/latest/building-data-lakes/data-ingestion-methods.html
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The AWS Certified Cloud Practitioner Exam (CLF-C02) is an introduction to AWS services and the intention is to examine the candidates ability to define what the AWS cloud is and its global infrastructure. It provides an overview of AWS core services security aspects, pricing and support services. The main objective is to provide an overall understanding about the Amazon Web Services Cloud platform. The course helps you get the conceptual understanding of the AWS and can help you know about the basics of AWS and cloud computing, including the services, cases and benefits [Get AWS CCP Practice Exam PDF Dumps here]
To succeed with the real exam, do not memorize the answers below. It is very important that you understand why a question is right or wrong and the concepts behind it by carefully reading the reference documents in the answers.
aws cloud practitioner practice questions and answers
aws cloud practitioner practice exam questions and references
Q1:For auditing purposes, your company now wants to monitor all API activity for all regions in your AWS environment. What can you use to fulfill this new requirement?
A. For each region, enable CloudTrail and send all logs to a bucket in each region.
B. Enable CloudTrail for all regions.
C. Ensure one CloudTrail is enabled for all regions.
D. Use AWS Config to enable the trail for all regions.
Ensure one CloudTrail is enabled for all regions. Turn on CloudTrail for all regions in your environment and CloudTrail will deliver log files from all regions to one S3 bucket. AWS CloudTrail is a service that enables governance, compliance, operational auditing, and risk auditing of your AWS account. With CloudTrail, you can log, continuously monitor, and retain account activity related to actions across your AWS infrastructure. CloudTrail provides event history of your AWS account activity, including actions taken through the AWS Management Console, AWS SDKs, command line tools, and other AWS services. This event history simplifies security analysis, resource change tracking, and troubleshooting.
Use a VPC Endpoint to access S3. A VPC endpoint enables you to privately connect your VPC to supported AWS services and VPC endpoint services powered by PrivateLink without requiring an internet gateway, NAT device, VPN connection, or AWS Direct Connect connection. Instances in your VPC do not require public IP addresses to communicate with resources in the service. Traffic between your VPC and the other service does not leave the Amazon network.
AWS PrivateLink simplifies the security of data shared with cloud-based applications by eliminating the exposure of data to the public Internet.
[Get AWS CCP Practice Exam PDF Dumps here] It is AWS responsibility to secure Edge locations and decommission the data. AWS responsibility “Security of the Cloud” – AWS is responsible for protecting the infrastructure that runs all of the services offered in the AWS Cloud. This infrastructure is composed of the hardware, software, networking, and facilities that run AWS Cloud services.
Q4:You have EC2 instances running at 90% utilization and you expect this to continue for at least a year. What type of EC2 instance would you choose to ensure your cost stay at a minimum?
[Get AWS CCP Practice Exam PDF Dumps here] Reserved instances are the best choice for instances with continuous usage and offer a reduced cost because you purchase the instance for the entire year. Amazon EC2 Reserved Instances (RI) provide a significant discount (up to 75%) compared to On-Demand pricing and provide a capacity reservation when used in a specific Availability Zone.
The AWS Simple Monthly Calculator helps customers and prospects estimate their monthly AWS bill more efficiently. Using this tool, they can add, modify and remove services from their ‘bill’ and it will recalculate their estimated monthly charges automatically.
A. Sign up for the free alert under filing preferences in the AWS Management Console.
B. Set a schedule to regularly review the Billing an Cost Management dashboard each month.
C. Create an email alert in AWS Budget
D. In CloudWatch, create an alarm that triggers each time the limit is exceeded.
Answer:
Answer: iOS – Android (C) [Get AWS CCP Practice Exam PDF Dumps here] AWS Budgets gives you the ability to set custom budgets that alert you when your costs or usage exceed (or are forecasted to exceed) your budgeted amount. You can also use AWS Budgets to set reservation utilization or coverage targets and receive alerts when your utilization drops below the threshold you define. Reservation alerts are supported for Amazon EC2, Amazon RDS, Amazon Redshift, Amazon ElastiCache, and Amazon Elasticsearch reservations.
Q7:An Edge Location is a specialization AWS data centre that works with which services?
A. Lambda
B. CloudWatch
C. CloudFront
D. Route 53
Answer:
Answer: Get AWS Certified Cloud Practitioner Practice Exam CCP CLF-C02 eBook Print Book here Lambda@Edge lets you run Lambda functions to customize the content that CloudFront delivers, executing the functions in AWS locations closer to the viewer. Amazon CloudFront is a web service that speeds up distribution of your static and dynamic web content, such as .html, .css, .js, and image files, to your users. CloudFront delivers your content through a worldwide network of data centers called edge locations. When a user requests content that you’re serving with CloudFront, the user is routed to the edge location that provides the lowest latency (time delay), so that content is delivered with the best possible performance.
CloudFront speeds up the distribution of your content by routing each user request through the AWS backbone network to the edge location that can best serve your content. Typically, this is a CloudFront edge server that provides the fastest delivery to the viewer. Using the AWS network dramatically reduces the number of networks that your users’ requests must pass through, which improves performance. Users get lower latency—the time it takes to load the first byte of the file—and higher data transfer rates.
You also get increased reliability and availability because copies of your files (also known as objects) are now held (or cached) in multiple edge locations around the world.
Anser: A. Route 53 is a domain name system service by AWS. When a Disaster does occur , it can be easy to switch to secondary sites using the Route53 service. Amazon Route 53 is a highly available and scalable cloud Domain Name System (DNS) web service. It is designed to give developers and businesses an extremely reliable and cost effective way to route end users to Internet applications by translating names like www.example.com into the numeric IP addresses like 192.0.2.1 that computers use to connect to each other. Amazon Route 53 is fully compliant with IPv6 as well.
Answer: D. The below snapshot from the AWS Documentation shows the spectrum of the Disaster recovery methods. If you go to the further end of the spectrum you have the least time for downtime for the users.
Q11:Your company is planning to host resources in the AWS Cloud. They want to use services which can be used to decouple resources hosted on the cloud. Which of the following services can help fulfil this requirement?
A. AWS EBS Volumes
B. AWS EBS Snapshots
C. AWS Glacier
D. AWS SQS
Answer:
D. AWS SQS: Amazon Simple Queue Service (Amazon SQS) offers a reliable, highly-scalable hosted queue for storing messages as they travel between applications or microservices. It moves data between distributed application components and helps you decouple these components.
A. 99.999999999% Durability and 99.99% Availability S3 Standard Storage class has a rating of 99.999999999% durability (referred to as 11 nines) and 99.99% availability.
A. Redshift is a database offering that is fully-managed and used for data warehousing and analytics, including compatibility with existing business intelligence tools.
B. and C. CENTRALLY MANAGE POLICIES ACROSS MULTIPLE AWS ACCOUNTS AUTOMATE AWS ACCOUNT CREATION AND MANAGEMENT CONTROL ACCESS TO AWS SERVICES CONSOLIDATE BILLING ACROSS MULTIPLE AWS ACCOUNTS
Q17:There is a requirement hosting a set of servers in the Cloud for a short period of 3 months. Which of the following types of instances should be chosen to be cost effective.
A. Spot Instances
B. On-Demand
C. No Upfront costs Reserved
D. Partial Upfront costs Reserved
Answer:
B. Since the requirement is just for 3 months, then the best cost effective option is to use On-Demand Instances.
You can use Amazon CloudWatch Logs to monitor, store, and access your log files from Amazon Elastic Compute Cloud (Amazon EC2) instances, AWS CloudTrail, and other sources. You can then retrieve the associated log data from CloudWatch Log.
Q22:A company is deploying a new two-tier web application in AWS. The company wants to store their most frequently used data so that the response time for the application is improved. Which AWS service provides the solution for the company’s requirements?
A. MySQL Installed on two Amazon EC2 Instances in a single Availability Zone
Amazon ElastiCache is a web service that makes it easy to deploy, operate, and scale an in-memory data store or cache in the cloud. The service improves the performance of web applications by allowing you to retrieve information from fast, managed, in-memory data stores, instead of relying entirely on slower disk-based databases.
Q23:You have a distributed application that periodically processes large volumes of data across multiple Amazon EC2 Instances. The application is designed to recover gracefully from Amazon EC2 instance failures. You are required to accomplish this task in the most cost-effective way. Which of the following will meetyour requirements?
When you think of cost effectiveness, you can either have to choose Spot or Reserved instances. Now when you have a regular processing job, the best is to use spot instances and since your application is designed recover gracefully from Amazon EC2 instance failures, then even if you lose the Spot instance , there is no issue because your application can recover.
A network access control list (ACL) is an optional layer of security for your VPC that acts as a firewall for controlling traffic in and out of one or more subnets. You might set up network ACLs with rules similar to your security groups in order to add an additional layer of security to your VPC.
Q25:A company is deploying a two-tier, highly available web application to AWS. Which service provides durable storage for static content while utilizing Overall CPU resources for the web tier?
A. Amazon EBC volume.
B. Amazon S3
C. Amazon EC2 instance store
D. Amazon RDS instance
Answer:
B. Amazon S3 is the default storage service that should be considered for companies. It provides durable storage for all static content.
Q26:When working on the costing for on-demand EC2 instances , which are the following are attributes which determine the costing of the EC2 Instance. Choose 3 answers from the options given below
Q27:You have a mission-critical application which must be globally available at all times. If this is the case, which of the below deployment mechanisms would you employ
Always build components which are loosely coupled. This is so that even if one component does fail, the entire system does not fail. Also if you build with the assumption that everything will fail, then you will ensure that the right measures are taken to build a highly available and fault tolerant system.
Q29: You have 2 accounts in your AWS account. One for the Dev and the other for QA. All are part ofconsolidated billing. The master account has purchase 3 reserved instances. The Dev department is currently using 2 reserved instances. The QA team is planning on using 3 instances which of the same instance type. What is the pricing tier of the instances that can be used by the QA Team?
Since all are a part of consolidating billing, the pricing of reserved instances can be shared by All. And since 2 are already used by the Dev team , another one can be used by the QA team. The rest of the instances can be on-demand instances.
Amazon Simple Queue Service (Amazon SQS) offers a reliable, highly-scalable hosted queue for storing messages as they travel between applications or microservices. It moves data between distributed application components and helps you decouple these components.
Q32:You are exploring what services AWS has off-hand. You have a large number of data sets that need to be processed. Which of the following services can help fulfil this requirement.
A. EMR
B. S3
C. Glacier
D. Storage Gateway
Answer:
A. Amazon EMR helps you analyze and process vast amounts of data by distributing the computational work across a cluster of virtual servers running in the AWS Cloud. The cluster is managed using an open-source framework called Hadoop. Amazon EMR lets you focus on crunching or analyzing your data without having to worry about time-consuming setup, management, and tuning of Hadoop clusters or the compute capacity they rely on.
Amazon Inspector enables you to analyze the behaviour of your AWS resources and helps you to identify potential security issues. Using Amazon Inspector, you can define a collection of AWS resources that you want to include in an assessment target. You can then create an assessment template and launch a security assessment run of this target.
Q34:Your company is planning to offload some of the batch processing workloads on to AWS. These jobs can be interrupted and resumed at any time. Which of the following instance types would be the most cost effective to use for this purpose.
A. On-Demand
B. Spot
C. Full Upfront Reserved
D. Partial Upfront Reserved
Answer:
B. Spot Instances are a cost-effective choice if you can be flexible about when your applications run and if your applications can be interrupted. For example, Spot Instances are well-suited for data analysis, batch jobs, background processing, and optional tasks
Note that the AWS Console cannot be used to upload data onto Glacier. The console can only be used to create a Glacier vault which can be used to upload the data.
Snowball is a petabyte-scale data transport solution that uses secure appliances to transfer large amounts of data& into and out of the AWS cloud. Using Snowball addresses common challenges with large-scale data transfers including high network costs, long transfer times, and security concerns. Transferring data with Snowball is simple, fast, secure, and can be as little as one-fifth the cost of high-speed Internet.
Amazon Inspector enables you to analyze the behavior of your AWS resources and helps you to identify potential security issues. Using Amazon Inspector, you can define a collection of AWS resources that you want to include in an assessment target. You can then create an assessment template and launch a security assessment run of this target.
AWS Database Migration Service helps you migrate databases to AWS quickly and securely. The source database remains fully operational during the migration, minimizing downtime to applications that rely on the database. The AWS Database Migration Service can migrate your data to and from most widely used commercial and open source databases.
You can reduce the load on your source DB Instance by routing read queries from your applications to the read replica. Read replicas allow you to elastically scale out beyond the capacity constraints of a single DB instance for read-heavy database workloads.
When you create an EBS volume in an Availability Zone, it is automatically replicated within that zone to prevent data loss due to failure of any single hardware component
Q42:Your company is planning to host a large e-commerce application on the AWS Cloud. One of their major concerns is Internet attacks such as DDos attacks.
Which of the following services can help mitigate this concern. Choose 2 answers from the options given below
One of the first techniques to mitigate DDoS attacks is to minimize the surface area that can be attacked thereby limiting the options for attackers and allowing you to build protections in a single place. We want to ensure that we do not expose our application or resources to ports, protocols or applications from where they do not expect any communication. Thus, minimizing the possible points of attack and letting us concentrate our mitigation efforts. In some cases, you can do this by placing your computation resources behind Content Distribution Networks (CDNs), Load Balancers and restricting direct Internet traffic to certain parts of your infrastructure like your database servers. In other cases, you can use firewalls or Access Control Lists (ACLs) to control what traffic reaches your applications.
You can use the consolidated billing feature in AWS Organizations to consolidate payment for multiple AWS accounts or multiple AISPL accounts. With consolidated billing, you can see a combined view of AWS charges incurred by all of your accounts. You also can get a cost report for each member account that is associated with your master account. Consolidated billing is offered at no additional charge.
One of the first techniques to mitigate DDoS attacks is to minimize the surface area that can be attacked thereby limiting the options for attackers and allowing you to build protections in a single place. We want to ensure that we do not expose our application or resources to ports, protocols or applications from where they do not expect any communication. Thus, minimizing the possible points of attack and letting us concentrate our mitigation efforts. In some cases, you can do this by placing your computation resources behind; Content Distribution Networks (CDNs), Load Balancers and restricting direct Internet traffic to certain parts of your infrastructure like your database servers. In other cases, you can use firewalls or Access Control Lists (ACLs) to control what traffic reaches your applications.
If you want a self-managed database, that means you want complete control over the database engine and the underlying infrastructure. In such a case you need to host the database on an EC2 Instance
If the database is going to be used for a minimum of one year at least , then it is better to get Reserved Instances. You can save on costs , and if you use a partial upfront options , you can get a better discount
The AWS Console cannot be used to upload data onto Glacier. The console can only be used to create a Glacier vault which can be used to upload the data.
Security groups acts as a virtual firewall for your instance to control inbound and outbound traffic. Network access control list (ACL) is an optional layer of security for your VPC that acts as a firewall for controlling traffic in and out of one or more subnets.
Q52:You plan to deploy an application on AWS. This application needs to be PCI Compliant. Which of the below steps are needed to ensure the compliance? Choose 2 answers from the below list:
A. Choose AWS services which are PCI Compliant
B. Ensure the right steps are taken during application development for PCI Compliance
C. Encure the AWS Services are made PCI Compliant
D. Do an audit after the deployment of the application for PCI Compliance.
Q57:Which of the following is a factor when calculating Total Cost of Ownership (TCO) for the AWS Cloud?
A. The number of servers migrated to AWS
B. The number of users migrated to AWS
C. The number of passwords migrated to AWS
D. The number of keys migrated to AWS
Answer:
A. Running servers will incur costs. The number of running servers is one factor of Server Costs; a key component of AWS’s Total Cost of Ownership (TCO). Reference: AWS cost calculator
Q58:Which AWS Services can be used to store files? Choose 2 answers from the options given below:
A. Amazon CloudWatch
B. Amazon Simple Storage Service (Amazon S3)
C. Amazon Elastic Block Store (Amazon EBS)
D. AWS COnfig
D. AWS Amazon Athena
B. and C. Amazon S3 is a Object storage built to store and retrieve any amount of data from anywhere. Amazon Elastic Block Store is a Persistent block storage for Amazon EC2.
C: AWS is defined as a cloud services provider. They provide hundreds of services of which compute and storage are included (not not limited to). Reference: AWS
Q60: Which AWS service can be used as a global content delivery network (CDN) service?
A. Amazon SES
B. Amazon CouldTrail
C. Amazon CloudFront
D. Amazon S3
Answer:
C: Amazon CloudFront is a web service that gives businesses and web application developers an easy and cost effective way to distribute content with low latency and high data transfer speeds. Like other AWS services, Amazon CloudFront is a self-service, pay-per-use offering, requiring no long term commitments or minimum fees. With CloudFront, your files are delivered to end-users using a global network of edge locations.Reference: AWS cloudfront
Q61:What best describes the concept of fault tolerance?
Choose the correct answer:
A. The ability for a system to withstand a certain amount of failure and still remain functional.
B. The ability for a system to grow in size, capacity, and/or scope.
C. The ability for a system to be accessible when you attempt to access it.
D. The ability for a system to grow and shrink based on demand.
Answer:
A: Fault tolerance describes the concept of a system (in our case a web application) to have failure in some of its components and still remain accessible (highly available). Fault tolerant web applications will have at least two web servers (in case one fails).
Q62: The firm you work for is considering migrating to AWS. They are concerned about cost and the initial investment needed. Which of the following features of AWS pricing helps lower the initial investment amount needed?
Choose 2 answers from the options given below:
A. The ability to choose the lowest cost vendor.
B. The ability to pay as you go
C. No upfront costs
D. Discounts for upfront payments
Answer:
B and C: The best features of moving to the AWS Cloud is: No upfront cost and The ability to pay as you go where the customer only pays for the resources needed. Reference: AWS pricing
Q64: Your company has started using AWS. Your IT Security team is concerned with the security of hosting resources in the Cloud. Which AWS service provides security optimization recommendations that could help the IT Security team secure resources using AWS?
An online resource to help you reduce cost, increase performance, and improve security by optimizing your AWS environment, Trusted Advisor provides real time guidance to help you provision your resources following AWS best practices. Reference: AWS trusted advisor
Q65:What is the relationship between AWS global infrastructure and the concept of high availability?
Choose the correct answer:
A. AWS is centrally located in one location and is subject to widespread outages if something happens at that one location.
B. AWS regions and Availability Zones allow for redundant architecture to be placed in isolated parts of the world.
C. Each AWS region handles a different AWS services, and you must use all regions to fully use AWS.
As an AWS user, you can create your applications infrastructure and duplicate it. By placing duplicate infrastructure in multiple regions, high availability is created because if one region fails you have a backup (in a another region) to use.
Q66: You are hosting a number of EC2 Instances on AWS. You are looking to monitor CPU Utilization on the Instance. Which service would you use to collect and track performance metrics for AWS services?
Answer: iOS – Android C: Amazon CloudWatch is a monitoring service for AWS cloud resources and the applications you run on AWS. You can use Amazon CloudWatch to collect and track metrics, collect and monitor log files, set alarms, and automatically react to changes in your AWS resources. Reference: AWS cloudwatch
Q67: Which of the following support plans give access to all the checks in the Trusted Advisor service.
Q68: Which of the following in AWS maps to a separate geographic location?
A. AWS Region B. AWS Data Centers C. AWS Availability Zone
Answer:
Answer: iOS – Android A: Amazon cloud computing resources are hosted in multiple locations world-wide. These locations are composed of AWS Regions and Availability Zones. Each AWS Region is a separate geographic area. Reference: AWS Regions And Availability Zone
Q69:What best describes the concept of scalability?
Choose the correct answer:
A. The ability for a system to grow and shrink based on demand.
B. The ability for a system to grow in size, capacity, and/or scope.
C. The ability for a system be be accessible when you attempt to access it.
D. The ability for a system to withstand a certain amount of failure and still remain functional.
Answer
Answer: iOS – Android B: Scalability refers to the concept of a system being able to easily (and cost-effectively) scale UP. For web applications, this means the ability to easily add server capacity when demand requires.
Q70: If you wanted to monitor all events in your AWS account, which of the below services would you use?
A. AWS CloudWatch
B. AWS CloudWatch logs
C. AWS Config
D. AWS CloudTrail
Answer:
D: AWS CloudTrail is a service that enables governance, compliance, operational auditing, and risk auditing of your AWS account. With CloudTrail, you can log, continuously monitor, and retain account activity related to actions across your AWS infrastructure. CloudTrail provides event history of your AWS account activity, including actions taken through the AWS Management Console, AWS SDKs, command line tools, and other AWS services. This event history simplifies security analysis, resource change tracking, and troubleshooting. Reference: Cloudtrail
Q71:What are the four primary benefits of using the cloud/AWS?
Choose the correct answer:
A. Fault tolerance, scalability, elasticity, and high availability.
B. Elasticity, scalability, easy access, limited storage.
C. Fault tolerance, scalability, sometimes available, unlimited storage
D. Unlimited storage, limited compute capacity, fault tolerance, and high availability.
Answer:
Answer: iOS – Android Fault tolerance, scalability, elasticity, and high availability are the four primary benefits of AWS/the cloud.
Q72:What best describes a simplified definition of the “cloud”?
Choose the correct answer:
A. All the computers in your local home network.
B. Your internet service provider
C. A computer located somewhere else that you are utilizing in some capacity.
D. An on-premise data center that your company owns.
Answer
Answer: iOS – Android (D) The simplest definition of the cloud is a computer that is located somewhere else that you are utilizing in some capacity. AWS is a cloud services provider, as the provide access to computers they own (located at AWS data centers), that you use for various purposes.
Q73: Your development team is planning to host a development environment on the cloud. This consists of EC2 and RDS instances. This environment will probably only be required for 2 months.
Which types of instances would you use for this purpose?
A. On-Demand
B. Spot
C. Reserved
D. Dedicated
Answer:
Answer: iOS – Android (A) The best and cost effective option would be to use On-Demand Instances. The AWS documentation gives the following additional information on On-Demand EC2 Instances. With On-Demand instances you only pay for EC2 instances you use. The use of On-Demand instances frees you from the costs and complexities of planning, purchasing, and maintaining hardware and transforms what are commonly large fixed costs into much smaller variable costs. Reference: AWS ec2 pricing on-demand
Q74: Which of the following can be used to secure EC2 Instances?
Answer: iOS – Android security groups acts as a virtual firewall for your instance to control inbound and outbound traffic. When you launch an instance in a VPC, you can assign up to five security groups to the instance. Security groups act at the instance level, not the subnet level. Therefore, each instance in a subnet in your VPC could be assigned to a different set of security groups. If you don’t specify a particular group at launch time, the instance is automatically assigned to the default security group for the VPC. Reference: VPC Security Groups
Q75: What is the purpose of a DNS server?
Choose the correct answer:
A. To act as an internet search engine.
B. To protect you from hacking attacks.
C. To convert common language domain names to IP addresses.
Domain name system servers act as a “third party” that provides the service of converting common language domain names to IP addresses (which are required for a web browser to properly make a request for web content).
High availability refers to the concept that something will be accessible when you try to access it. An object or web application is “highly available” when it is accessible a vast majority of the time.
RDS is a SQL database service (that offers several database engine options), and DynamoDB is a NoSQL database option that only offers one NoSQL engine.
Reference:
Q78: What are two open source in-memory engines supported by ElastiCache?
Q85:If you want to have SMS or email notifications sent to various members of your department with status updates on resources in your AWS account, what service should you choose?
Choose the correct answer:
A. SNS
B. GetSMS
C. RDS
D. STS
Answer:
Answer: iOS – Android (A) Simple Notification Service (SNS) is what publishes messages to SMS and/or email endpoints.
Amazon WorkSpaces is a managed, secure Desktop-as-a-Service (DaaS) solution. You can use Amazon WorkSpaces to provision either Windows or Linux desktops in just a few minutes and quickly scale to provide thousands of desktops to workers across the globe
Q87: Your company has recently migrated large amounts of data to the AWS cloud in S3 buckets. But it is necessary to discover and protect the sensitive data in these buckets. Which AWS service can do that?
Notes:Amazon Macie is a fully managed data security and data privacy service that uses machine learning and pattern matching to discover and protect your sensitive data in AWS.
Q88: Your Finance Department has instructed you to save costs wherever possible when using the AWS Cloud. You notice that using reserved EC2 instances on a 1year contract will save money. What payment method will save the most money?
A: Deferred
B: Partial Upfront
C: All Upfront
D: No Upfront
Answer: C
Notes: With the All Upfront option, you pay for the entire Reserved Instance term with one upfront payment. This option provides you with the largest discount compared to On Demand Instance pricing.
Q89: A fantasy sports company needs to run an application for the length of a football season (5 months). They will run the application on an EC2 instance and there can be no interruption. Which purchasing option best suits this use case?
Notes: This is not a long enough term to make reserved instances the better option. Plus, the application can’t be interrupted, which rules out spot instances. Dedicated instances provide the option to bring along existing software licenses.
The scenario does not indicate a need to do this.
Q90:Your company is considering migrating its data center to the cloud. What are the advantages of the AWS cloud over an on-premises data center?
A. Replace upfront operational expenses with low variable operational expenses.
B. Maintain physical access to the new data center, but share responsibility with AWS.
C. Replace low variable costs with upfront capital expenses.
D. Replace upfront capital expenses with low variable costs.
Q91:You are leading a pilot program to try the AWS Cloud for one of your applications. You have been instructed to provide an estimate of your AWS bill. Which service will allow you to do this by manually entering your planned resources by service?
Notes: With the AWS Pricing Calculator, you can input the services you will use, and the configuration of those services, and get an estimate of the costs these services will accrue. AWS Pricing Calculator lets you explore AWS services, and create an estimate for the cost of your use cases on AWS.
Q92:Which AWS service would enable you to view the spending distribution in one of your AWS accounts?
Notes: AWS Cost Explorer is a free tool that you can use to view your costs and usage. You can view data up to the last 13 months, forecast how much you are likely to spend for the next three months, and get recommendations for what Reserved Instances to purchase. You can use AWS Cost Explorer to see patterns in how much you spend on AWS resources over time, identify areas that need further inquiry, and see trends that you can use to understand your costs. You can also specify time ranges for the data, and view time data by day or by month.
Q93:You are managing the company’s AWS account. The current support plan is Basic, but you would like to begin using Infrastructure Event Management. What support plan (that already includes Infrastructure Event Management without an additional fee) should you upgrade to?
A. Upgrade to Enterprise plan.
B. Do nothing. It is included in the Basic plan.
C. Upgrade to Developer plan.
D. Upgrade to the Business plan. No other steps are necessary.
Notes:AWS Infrastructure Event Management is a structured program available to Enterprise support customers (and Business Support customers for an additional fee) that helps you plan for large-scale events, such as product or application launches, infrastructure migrations, and marketing events.
With Infrastructure Event Management, you get strategic planning assistance before your event, as well as real-time support during these moments that matter most for your business.
Q94:You have decided to use the AWS Cost and Usage Report to track your EC2 Reserved Instance costs. To where can these reports be published?
A. Trusted Advisor
B. An S3 Bucket that you own.
C. CloudWatch
D. An AWS owned S3 Bucket.
Answer: B
Notes: The AWS Cost and Usage Reports (AWS CUR) contains the most comprehensive set of cost and usage data available. You can use Cost and Usage Reports to publish your AWS billing reports to an Amazon Simple Storage Service (Amazon S3) bucket that you own. You can receive reports that break down your costs by the hour or day, by product or product resource, or by tags that you define yourself. AWS updates the report in your bucket once a day in comma-separated value (CSV) format. You can view the reports using spreadsheet software such as Microsoft Excel or Apache OpenOffice Calc, or access them from an application using the Amazon S3 API.
Q95:What can we do in AWS to receive the benefits of volume pricing for your multiple AWS accounts?
A. Use consolidated billing in AWS Organizations.
B. Purchase services in bulk from AWS Marketplace.
Notes: You can use the consolidated billing feature in AWS Organizations to consolidate billing and payment for multiple AWS accounts or multiple Amazon Internet Services Pvt. Ltd (AISPL) accounts. You can combine the usage across all accounts in the organization to share the volume pricing discounts, Reserved Instance discounts, and Savings Plans. This can result in a lower charge for your project, department, or company than with individual standalone accounts.
Q96:A gaming company is using the AWS Developer Tool Suite to develop, build, and deploy their applications. Which AWS service can be used to trace user requests from end-to-end through the application?
Notes:AWS X-Ray helps developers analyze and debug production, distributed applications, such as those built using a microservices architecture. With X-Ray, you can understand how your application and its underlying services are performing to identify and troubleshoot the root cause of performance issues and errors. X-Ray provides an end-to-end view of requests as they travel through your application, and shows a map of your application’s underlying components.
Q97:A company needs to use a Load Balancer which can serve traffic at the TCP, and UDP layers. Additionally, it needs to handle millions of requests per second at very low latencies. Which Load Balancer should they use?
Notes:Network Load Balancer is best suited for load balancing of Transmission Control Protocol (TCP), User Datagram Protocol (UDP) and Transport Layer Security (TLS) traffic where extreme performance is required. Operating at the connection level (Layer 4), Network Load Balancer routes traffic to targets within Amazon Virtual Private Cloud (Amazon VPC) and is capable of handling millions of requests per second while maintaining ultra-low latencies.
Q98:Your company is migrating its services to the AWS cloud. The DevOps team has heard about infrastructure as code, and wants to investigate this concept. Which AWS service would they investigate?
Notes:AWS CloudFormation is a service that helps you model and set up your Amazon Web Services resources so that you can spend less time managing those resources and more time focusing on your applications that run in AWS.
Q99:You have a MySQL database that you want to migrate to the cloud, and you need it to be significantly faster there. You are looking for a speed increase up to 5 times the current performance. Which AWS offering could you use?
Notes:Amazon Aurora is a MySQL and PostgreSQL-compatible relational database built for the cloud, that combines the performance and availability of traditional enterprise databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora is up to five times faster than standard MySQL databases and three times faster than standard PostgreSQL databases.
Q100:A developer is trying to programmatically retrieve information from an EC2 instance such as public keys, ip address, and instance id. From where can this information be retrieved?
Notes: This type of data is stored in Instance metadata. Instance userdata does not retrieve the information mentioned, but can be used to help configure a new instance.
Q101: Why is AWS more economical than traditional data centers for applications with varying compute workloads?
A) Amazon EC2 costs are billed on a monthly basis. B) Users retain full administrative access to their Amazon EC2 instances. C) Amazon EC2 instances can be launched on demand when needed. D) Users can permanently run enough instances to handle peak workloads.
Answer: C Notes: The ability to launch instances on demand when needed allows users to launch and terminate instances in response to a varying workload. This is a more economical practice than purchasing enough on-premises servers to handle the peak load. Reference: Advantage of cloud computing
Q102: Which AWS service would simplify the migration of a database to AWS?
A) AWS Storage Gateway B) AWS Database Migration Service (AWS DMS) C) Amazon EC2 D) Amazon AppStream 2.0
Answer: B Notes: AWS DMS helps users migrate databases to AWS quickly and securely. The source database remains fully operational during the migration, minimizing downtime to applications that rely on the database. AWS DMS can migrate data to and from most widely used commercial and open-source databases. Reference: AWS DMS
Q103: Which AWS offering enables users to find, buy, and immediately start using software solutions in their AWS environment?
A) AWS Config B) AWS OpsWorks C) AWS SDK D) AWS Marketplace
Answer: D Notes: AWS Marketplace is a digital catalog with thousands of software listings from independent software vendors that makes it easy to find, test, buy, and deploy software that runs on AWS. Reference: AWS Markerplace
Q104: Which AWS networking service enables a company to create a virtual network within AWS?
A) AWS Config B) Amazon Route 53 C) AWS Direct Connect D) Amazon Virtual Private Cloud (Amazon VPC)
Answer: D Notes: Amazon VPC lets users provision a logically isolated section of the AWS Cloud where users can launch AWS resources in a virtual network that they define. Reference: VPC https://aws.amazon.com/vpc/
Q105: Which component of the AWS global infrastructure does Amazon CloudFront use to ensure low-latency delivery?
A) AWS Regions B) Edge locations C) Availability Zones D) Virtual Private Cloud (VPC)
Answer: B Notes: – To deliver content to users with lower latency, Amazon CloudFront uses a global network of points of presence (edge locations and regional edge caches) worldwide. Reference: Cloudfront – https://aws.amazon.com/cloudfront/
Q106: How would a system administrator add an additional layer of login security to a user’s AWS Management Console?
A) Use Amazon Cloud Directory B) Audit AWS Identity and Access Management (IAM) roles C) Enable multi-factor authentication D) Enable AWS CloudTrail
Answer: C Notes: – Multi-factor authentication (MFA) is a simple best practice that adds an extra layer of protection on top of a username and password. With MFA enabled, when a user signs in to an AWS Management Console, they will be prompted for their username and password (the first factor—what they know), as well as for an authentication code from their MFA device (the second factor—what they have). Taken together, these multiple factors provide increased security for AWS account settings and resources. Reference: MFA – https://aws.amazon.com/iam/features/mfa/
Q107: Which service can identify the user that made the API call when an Amazon EC2 instance is terminated?
A) AWS Trusted Advisor B) AWS CloudTrail C) AWS X-Ray D) AWS Identity and Access Management (AWS IAM)
Answer: B Notes: – AWS CloudTrail helps users enable governance, compliance, and operational and risk auditing of their AWS accounts. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. Events include actions taken in the AWS Management Console, AWS Command Line Interface (CLI), and AWS SDKs and APIs. Reference: AWS CloudTrail https://docs.aws.amazon.com/awscloudtrail/latest/userguide/cloudtrail-user-guide.html
Q108: Which service would be used to send alerts based on Amazon CloudWatch alarms?
A) Amazon Simple Notification Service (Amazon SNS) B) AWS CloudTrail C) AWS Trusted Advisor D) Amazon Route 53
Answer: A Notes: Amazon SNS and Amazon CloudWatch are integrated so users can collect, view, and analyze metrics for every active SNS. Once users have configured CloudWatch for Amazon SNS, they can gain better insight into the performance of their Amazon SNS topics, push notifications, and SMS deliveries. Reference: CloudWatch for Amazon SNS https://docs.aws.amazon.com/sns/latest/dg/sns-monitoring-using-cloudwatch.html
Q109: Where can a user find information about prohibited actions on the AWS infrastructure?
A) AWS Trusted Advisor B) AWS Identity and Access Management (IAM) C) AWS Billing Console D) AWS Acceptable Use Policy
Answer: D Notes: – The AWS Acceptable Use Policy provides information regarding prohibited actions on the AWS infrastructure. Reference: AWS Acceptable Use Policy – https://aws.amazon.com/aup/
Q110: Which of the following is an AWS responsibility under the AWS shared responsibility model?
A) Configuring third-party applications B) Maintaining physical hardware C) Securing application access and data D) Managing guest operating systems
Answer: B Notes: – Maintaining physical hardware is an AWS responsibility under the AWS shared responsibility model. Reference: AWS shared responsibility model https://aws.amazon.com/compliance/shared-responsibility-model/
Q111: Which recommendations are included in the AWS Trusted Advisor checks? (Select TWO.)
A) Amazon S3 bucket permissions
B) AWS service outages for services
C) Multi-factor authentication (MFA) use on the AWS account root user
D) Available software patches for Amazon EC2 instances
Answer: A and C
Notes: Trusted Advisor checks for S3 bucket permissions in Amazon S3 with open access permissions. Bucket permissions that grant list access to everyone can result in higher than expected charges if objects in the bucket are listed by unintended users at a high frequency. Bucket permissions that grant upload and delete access to all users create potential security vulnerabilities by allowing anyone to add, modify, or remove items in a bucket. This Trusted Advisor check examines explicit bucket permissions and associated bucket policies that might override the bucket permissions.
Trusted Advisor does not provide notifications for service outages. You can use the AWS Personal Health Dashboard to learn about AWS Health events that can affect your AWS services or account.
Trusted Advisor checks the root account and warns if MFA is not enabled.
Trusted Advisor does not provide information about the number of users in an AWS account.
What is the difference between Amazon EC2 Savings Plans and Spot Instances?
Amazon EC2 Savings Plans are ideal for workloads that involve a consistent amount of compute usage over a 1-year or 3-year term. With Amazon EC2 Savings Plans, you can reduce your compute costs by up to 72% over On-Demand costs.
Spot Instances are ideal for workloads with flexible start and end times, or that can withstand interruptions. With Spot Instances, you can reduce your compute costs by up to 90% over On-Demand costs. Unlike Amazon EC2 Savings Plans, Spot Instances do not require contracts or a commitment to a consistent amount of compute usage.
Amazon EBS vs Amazon EFS
An Amazon EBS volume stores data in a single Availability Zone. To attach an Amazon EC2 instance to an EBS volume, both the Amazon EC2 instance and the EBS volume must reside within the same Availability Zone.
Amazon EFS is a regional service. It stores data in and across multiple Availability Zones. The duplicate storage enables you to access data concurrently from all the Availability Zones in the Region where a file system is located. Additionally, on-premises servers can access Amazon EFS using AWS Direct Connect.
Which cloud deployment model allows you to connect public cloud resources to on-premises infrastructure?
Applications made available through hybrid deployments connect cloud resources to on-premises infrastructure and applications. For example, you might have an application that runs in the cloud but accesses data stored in your on-premises data center.
What is the difference between Amazon EC2 Savings Plans and Spot Instances?
Amazon EC2 Savings Plans are ideal for workloads that involve a consistent amount of compute usage over a 1-year or 3-year term. With Amazon EC2 Savings Plans, you can reduce your compute costs by up to 72% over On-Demand costs.
Spot Instances are ideal for workloads with flexible start and end times, or that can withstand interruptions. With Spot Instances, you can reduce your compute costs by up to 90% over On-Demand costs. Unlike Amazon EC2 Savings Plans, Spot Instances do not require contracts or a commitment to a consistent amount of compute usage.
Which benefit of cloud computing helps you innovate and build faster?
Agility: The cloud gives you quick access to resources and services that help you build and deploy your applications faster.
Which developer tool allows you to write code within your web browser?
Cloud9 is an integrated development environment (IDE) that allows you to write code within your web browser.
Which method of accessing an EC2 instance requires both a private key and a public key?
SSH allows you to access an EC2 instance from your local laptop using a key pair, which consists of a private key and a public key.
Which service allows you to track the name of the user making changes in your AWS account?
CloudTrail tracks user activity and API calls in your account, which includes identity information (the user’s name, source IP address, etc.) about the API caller.
Which analytics service allows you to query data in Amazon S3 using Structured Query Language (SQL)?
Athena is a query service that makes it easy to analyze data in Amazon S3 using SQL.
Which machine learning service helps you build, train, and deploy models quickly?
SageMaker helps you build, train, and deploy machine learning models quickly.
Which EC2 storage mechanism is recommended when running a database on an EC2 instance?
EBS is a storage device you can attach to your instances and is a recommended storage option when you run databases on an instance.
Which storage service is a scalable file system that only works with Linux-based workloads?
EFS is an elastic file system for Linux-based workloads.
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Which AWS service provides a secure and resizable compute platform with choice of processor, storage, networking, operating system, and purchase model?
Amazon Elastic Compute Cloud (Amazon EC2) is a web service that provides secure, resizable compute capacity in the cloud. Amazon EC2 offers the broadest and deepest compute platform with choice of processor, storage, networking, operating system, and purchase model. Amazon EC2.
Which services allow you to build hybrid environments by connecting on-premises infrastructure to AWS?
Site-to-site VPN allows you to establish a secure connection between your on-premises equipment and the VPCs in your AWS account.
Direct Connect allows you to establish a dedicated network connection between your on-premises network and AWS.
What service could you recommend to a developer to automate the software release process?
CodePipeline is a developer tool that allows you to continuously automate the software release process.
Which service allows you to practice infrastructure as code by provisioning your AWS resources via scripted templates?
CloudFormation allows you to provision your AWS resources via scripted templates.
Which machine learning service allows you to add image analysis to your applications?
Rekognition is a service that makes it easy to add image analysis to your applications.
Which services allow you to run containerized applications without having to manage servers or clusters?
Fargate removes the need for you to interact with servers or clusters as it provisions, configures, and scales clusters of virtual machines to run containers for you.
ECS lets you run your containerized Docker applications on both Amazon EC2 and AWS Fargate.
EKS lets you run your containerized Kubernetes applications on both Amazon EC2 and AWS Fargate.
Amazon S3 offers multiple storage classes. Which storage class is best for archiving data when you want the cheapest cost and don’t mind long retrieval times?
S3 Glacier Deep Archive offers the lowest cost and is used to archive data. You can retrieve objects within 12 hours.
In the shared responsibility model, what is the customer responsible for?
You are responsible for patching the guest OS, including updates and security patches.
You are responsible for firewall configuration and securing your application.
A company needs phone, email, and chat access 24 hours a day, 7 days a week. The response time must be less than 1 hour if a production system has a service interruption. Which AWS Support plan meets these requirements at the LOWEST cost?
The Business Support plan provides phone, email, and chat access 24 hours a day, 7 days a week. The Business Support plan has a response time of less than 1 hour if a production system has a service interruption.
Which of the following is an advantage of consolidated billing on AWS?
Consolidated billing is a feature of AWS Organizations. You can combine the usage across all accounts in your organization to share volume pricing discounts, Reserved Instance discounts, and Savings Plans. This solution can result in a lower charge compared to the use of individual standalone accounts.
A company requires physical isolation of its Amazon EC2 instances from the instances of other customers. Which instance purchasing option meets this requirement?
With Dedicated Hosts, a physical server is dedicated for your use. Dedicated Hosts provide visibility and the option to control how you place your instances on an isolated, physical server. For more information about Dedicated Hosts, see Amazon EC2 Dedicated Hosts.
A company is hosting a static website from a single Amazon S3 bucket. Which AWS service will achieve lower latency and high transfer speeds?
CloudFront is a web service that speeds up the distribution of your static and dynamic web content, such as .html, .css, .js, and image files, to your users. Content is cached in edge locations. Content that is repeatedly accessed can be served from the edge locations instead of the source S3 bucket. For more information about CloudFront, see Accelerate static website content delivery.
Which AWS service provides a simple and scalable shared file storage solution for use with Linux-based Amazon EC2 instances and on-premises servers?
Amazon EFS provides an elastic file system that lets you share file data without the need to provision and manage storage. It can be used with AWS Cloud services and on-premises resources, and is built to scale on demand to petabytes without disrupting applications. With Amazon EFS, you can grow and shrink your file systems automatically as you add and remove files, eliminating the need to provision and manage capacity to accommodate growth.
Which service allows you to generate encryption keys managed by AWS?
KMS allows you to generate and manage encryption keys. The keys generated by KMS are managed by AWS.
Which service can integrate with a Lambda function to automatically take remediation steps when it uncovers suspicious network activity when monitoring logs in your AWS account?
GuardDuty can perform automated remediation actions by leveraging Amazon CloudWatch Events and AWS Lambda. GuardDuty continuously monitors for threats and unauthorized behavior to protect your AWS accounts, workloads, and data stored in Amazon S3. GuardDuty analyzes multiple AWS data sources, such as AWS CloudTrail event logs, Amazon VPC Flow Logs, and DNS logs.
Which service allows you to create access keys for someone needing to access AWS via the command line interface (CLI)?
IAM allows you to create users and generate access keys for users needing to access AWS via the CLI.
Which service allows you to record software configuration changes within your Amazon EC2 instances over time?
Config helps with recording compliance and configuration changes over time for your AWS resources.
Which service assists with compliance and auditing by offering a downloadable report that provides the status of passwords and MFA devices in your account?
IAM provides a downloadable credential report that lists all users in your account and the status of their various credentials, including passwords, access keys, and MFA devices.
Which service allows you to locate credit card numbers stored in Amazon S3?
Macie is a data privacy service that helps you uncover and protect your sensitive data, such as personally identifiable information (PII) like credit card numbers, passport numbers, social security numbers, and more.
How do you manage permissions for multiple users at once using AWS Identity and Access Management (IAM)?
An IAM group is a collection of IAM users. When you assign an IAM policy to a group, all users in the group are granted permissions specified by the policy.
Which service protects your web application from cross-site scripting attacks?
WAF helps protect your web applications from common web attacks, like SQL injection or cross-site scripting.
Which AWS Trusted Advisor real-time guidance recommendations are available for AWS Basic Support and AWS Developer Support customers?
Basic and Developer Support customers get 50 service limit checks.
Basic and Developer Support customers get security checks for “Specific Ports Unrestricted” on Security Groups.
Basic and Developer Support customers get security checks on S3 Bucket Permissions.
Which service allows you to simplify billing by using a single payment method for all your accounts?
Organizations offers consolidated billing that provides 1 bill for all your AWS accounts. This also gives you access to volume discounts.
Which AWS service usage will always be free even after the 12-month free tier plan has expired?
One million Lambda requests are always free each month.
What is the easiest way for a customer on the AWS Basic Support plan to increase service limits?
The Basic Support plan allows 24/7 access to Customer Service via email and the ability to open service limit increase support cases.
Which types of issues are covered by AWS Support?
“How to” questions about AWS service and features
Problems detected by health checks
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Which features of AWS reduce your total cost of ownership (TCO)?
Sharing servers with others allows you to save money.
Elastic computing allows you to trade capital expense for variable expense.
You pay only for the computing resources you use with no long-term commitments.
Which service allows you to select and deploy operating system and software patches automatically across large groups of Amazon EC2 instances?
Systems Manager allows you to automate operational tasks across your AWS resources.
Which service provides the easiest way to set up and govern a secure, multi-account AWS environment?
Control Tower allows you to centrally govern and enforce the best use of AWS services across your accounts.
Which cost management tool gives you the ability to be alerted when the actual or forecasted cost and usage exceed your desired threshold?
Budgets allow you to improve planning and cost control with flexible budgeting and forecasting. You can choose to be alerted when your budget threshold is exceeded.
Which tool allows you to compare your estimated service costs per Region?
The Pricing Calculator allows you to get an estimate for the cost of AWS services. Comparing service costs per Region is a common use case.
Who can assist with accelerating the migration of legacy contact center infrastructure to AWS?
Professional Services is a global team of experts that can help you realize your desired business outcomes with AWS.
The AWS Partner Network (APN) is a global community of partners that helps companies build successful solutions with AWS.
Which cost management tool allows you to view costs from the past 12 months, current detailed costs, and forecasts costs for up to 3 months?
Cost Explorer allows you to visualize, understand, and manage your AWS costs and usage over time.
Which service reduces the operational overhead of your IT organization?
Managed Services implements best practices to maintain your infrastructure and helps reduce your operational overhead and risk.
I assume it is your subscription where the VPCs are located, otherwise you can’t really discover the information you are looking for. On the EC2 server you could use AWS CLI or Powershell based scripts that query the IP information. Based on IP you can find out what instance uses the network interface, what security groups are tied to it and in which VPC the instance is hosted. Read more here…
When using AWS Lambda inside your VPC, your Lambda function will be allocated private IP addresses, and only private IP addresses, from your specified subnets. This means that you must ensure that your specified subnets have enough free address space for your Lambda function to scale up to. Each simultaneous invocation needs its own IP. Read more here…
When a Lambda “is in a VPC”, it really means that its attached Elastic Network Interface is the customer’s VPC and not the hidden VPC that AWS manages for Lambda.
The ENI is not related to the AWS Lambda management system that does the invocation (the data plane mentioned here). The AWS Step Function system can go ahead and invoke the Lambda through the API, and the network request for that can pass through the underlying VPC and host infrastructure.
Those Lambdas in turn can invoke other Lambda directly through the API, or more commonly by decoupling them, such as through Amazon SQS used as a trigger. Read more ….
How do I invoke an AWS Lambda function programmatically?
Invokes a Lambda function. You can invoke a function synchronously (and wait for the response), or asynchronously. To invoke a function asynchronously, set InvocationType to Event.
For synchronous invocation, details about the function response, including errors, are included in the response body and headers. For either invocation type, you can find more information in the execution log and trace.
When an error occurs, your function may be invoked multiple times. Retry behavior varies by error type, client, event source, and invocation type. For example, if you invoke a function asynchronously and it returns an error, Lambda executes the function up to two more times. For more information, see Retry Behavior.
For asynchronous invocation, Lambda adds events to a queue before sending them to your function. If your function does not have enough capacity to keep up with the queue, events may be lost. Occasionally, your function may receive the same event multiple times, even if no error occurs. To retain events that were not processed, configure your function with a dead-letter queue.
The status code in the API response doesn’t reflect function errors. Error codes are reserved for errors that prevent your function from executing, such as permissions errors, limit errors, or issues with your function’s code and configuration. For example, Lambda returns TooManyRequestsException if executing the function would cause you to exceed a concurrency limit at either the account level ( Concurrent Invocation Limit Exceeded) or function level ( Reserved Function Concurrent Invocation LimitExceeded).
For functions with a long timeout, your client might be disconnected during synchronous invocation while it waits for a response. Configure your HTTP client, SDK, firewall, proxy, or operating system to allow for long connections with timeout or keep-alive settings.
The subnet mask determines how many bits of the network address are relevant (and thus indirectly the size of the network block in terms of how many host addresses are available) –
192.0.2.0, subnet mask 255.255.255.0 means that 192.0.2 is the significant portion of the network number, and that there 8 bits left for host addresses (i.e. 192.0.2.0 thru 192.0.2.255)
192.0.2.0, subnet mask 255.255.255.128 means that 192.0.2.0 is the significant portion of the network number (first three octets and the most significant bit of the last octet), and that there 7 bits left for host addresses (i.e. 192.0.2.0 thru 192.0.2.127)
When in doubt, envision the network number and subnet mask in base 2 (i.e. binary) and it will become much clearer. Read more here…
Separate out the roles needed to do each job. (Assuming this is a corporate environment)
Have a role for EC2, another for Networking, another for IAM.
Everyone should not be admin. Everyone should not be able to add/remove IGW’s, NAT gateways, alter security groups and NACLS, or setup peering connections.
Also, another thing… lock down full internet access. Limit to what is needed and that’s it. Read more here….
How can we setup AWS public-private subnet in VPC without NAT server?
Within a single VPC, the subnets’ route tables need to point to each other. This will already work without additional routes because VPC sets up the local target to point to the VPC subnet.
Security groups are not used here since they are attached to instances, and not networks.
The NAT EC2 instance (server), or AWS-provided NAT gateway is necessary only if the private subnet internal addresses need to make outbound connections. The NAT will translate the private subnet internal addresses to the public subnet internal addresses, and the AWS VPC Internet Gateway will translate these to external IP addresses, which can then go out to the Internet. Read more here ….
What are the applications (or workloads) that cannot be migrated on to cloud (AWS or Azure or GCP)?
A good example of workloads that currently are not in public clouds are mobile and fixed core telecom networks for tier 1 service providers. This is despite the fact that these core networks are increasingly software based and have largely been decoupled from the hardware. There are a number of reasons for this such as the public cloud providers such as Azure and AWS do not offer the guaranteed availability required by telecom networks. These networks require 99.999% availability and is typically referred to as telecom grade.
The regulatory environment frequently restricts hosting of subscriber data outside the of the operators data centers or in another country and key network functions such as lawful interception cannot contractually be hosted off-prem. Read more here….
How many CIDRs can we add to my own created VPC?
You can add up to 5 IPv4 CIDR blocks, or 1 IPv6 block per VPC. You can further segment the network by utilizing up to 200 subnets per VPC. Amazon VPC Limits. Read more …
Why can’t a subnet’s CIDR be changed once it has been assigned?
Sure it can, but you’ll need to coordinate with the neighbors. You can merge two /25’s into a single /24 quite effortlessly if you control the entire range it covers. In practice you’ll see many tiny allocations in public IPv4 space, like /29’s and even smaller. Those are all assigned to different people. If you want to do a big shuffle there, you have a lot of coordinating to do.. or accept the fallout from the breakage you cause. Read more…
Can one VPC talk to another VPC?
Yes, but a Virtual Private Cloud is usually built for the express purpose of being isolated from unwanted external traffic. I can think of several good reasons to encourage that sort of communication, so the idea is not without merit. Read more..
Good knowledge about the AWS services, and how to leverage them to solve simple to complex problems.
As your question is related to the deployment Pod, you will probably be asked about deployment methods (A/B testing like blue-green deployment) as well as pipelining strategies. You might be asked during this interview to reason about a simple task and to code it (like parsing a log file). Also review the TCP/IP stack in-depth as well as the tools to troubleshoot it for the networking round. You will eventually have some Linux questions, the range of questions can vary from common CLI tools to Linux internals like signals / syscalls / file descriptors and so on.
Last but not least the Leadership principles, I can only suggest you to prepare a story for each of them. You will quickly find what LP they are looking for and would be able to give the right signal to your interviewer.
Finally, remember that theres a debrief after the (usually 5) stages of your on site interview, and more senior and convincing interviewers tend to defend their vote so don’t screw up with them.
Be natural, focus on the question details and ask for confirmation, be cool but not too much. At the end of the day, remember that your job will be to understand customer issues and provide a solution, so treat your interviewers as if they were customers and they will see a successful CSE in you, be reassured and give you the job.
Expect questions on cloudformations, Teraform, Aws ec2/rds and stack related questions.
It also depends on the support team you are being hired for. Networking or compute teams (Ec2) have different interview patterns vs database or big data support.
In any case, basics of OS, networking are critical to the interview. If you have a phone screen, we will be looking for basic/semi advance skills of these and your speciality. For example if you mention Oracle in your resume and you are interviewing for the database team, expect a flurry of those questions.
Other important aspect is the Amazon leadership principles. Half of your interview is based on LPs. If you fail to have scenarios where you do not demonstrate our LPs, you cannot expect to work here even though your technical skills are above average (Having extraordinary skills is a different thing).
The overall interview itself will have 1 phone screen if you are interviewing in the US and 1–2 if outside US. The onsite loop will be 4 rounds , 2 of which are technical (again divided into OS and networking and the specific speciality of the team you are interviewing for ) and 2 of them are leadership principles where we test your soft skills and management skills as they are very important in this job. You need to have a strong view point, disagree if it seems valid to do so, empathy and be a team player while showing the ability to pull off things individually as well. These skills will be critical for cracking LP interviews.
You will NOT be asked to code or write queries as its not part of the job, so you can concentrate on the theoretical part of the subject and also your resume. We will grill you on topics mentioned on your resume to start with.
Monolithic architecture is something that build from single piece of material, historically from rock. Monolith term normally use for object made from single large piece of material.” – Non-Technical Definition. “Monolithic application has single code base with multiple modules.
Large Monolithic code-base (often spaghetti code) puts immense cognitive complexity on the developer’s head. As a result, the development velocity is poor. Granular scaling (i.e., scaling part of the application) is not possible. Polyglot programming or polyglot database is challenging.
Drawbacks of Monolithic Architecture
This simple approach has a limitation in size and complexity. Application is too large and complex to fully understand and made changes fast and correctly. The size of the application can slow down the start-up time. You must redeploy the entire application on each update.
Sticky sessions, also known as session affinity, allow you to route a site user to the particular web server that is managing that individual user’s session. The session’s validity can be determined by a number of methods, including a client-side cookies or via configurable duration parameters that can be set at the load balancer which routes requests to the web servers.
Some advantages with utilizing sticky sessions are that it’s cost effective due to the fact you are storing sessions on the same web servers running your applications and that retrieval of those sessions is generally fast because it eliminates network latency. A drawback for using storing sessions on an individual node is that in the event of a failure, you are likely to lose the sessions that were resident on the failed node. In addition, in the event the number of your web servers change, for example a scale-up scenario, it’s possible that the traffic may be unequally spread across the web servers as active sessions may exist on particular servers. If not mitigated properly, this can hinder the scalability of your applications. Read more here …
After you terminate an instance, it remains visible in the console for a short while, and then the entry is automatically deleted. You cannot delete the terminated instance entry yourself. After an instance is terminated, resources such as tags and volumes are gradually disassociated from the instance, therefore may no longer be visible on the terminated instance after a short while.
When an instance terminates, the data on any instance store volumes associated with that instance is deleted.
By default, Amazon EBS root device volumes are automatically deleted when the instance terminates. However, by default, any additional EBS volumes that you attach at launch, or any EBS volumes that you attach to an existing instance persist even after the instance terminates. This behavior is controlled by the volume’s DeleteOnTermination attribute, which you can modify
When you first launch an instance with gp2 volumes attached, you get an initial burst credit allowing for up to 30 minutes of 3,000 iops/sec.
After the first 30 minutes, your volume will accrue credits as follows (taken directly from AWS documentation):
Within the General Purpose (SSD) implementation is a Token Bucket model that works as follows
Each token represents an “I/O credit” that pays for one read or one write.
A bucket is associated with each General Purpose (SSD) volume, and can hold up to 5.4 million tokens.
Tokens accumulate at a rate of 3 per configured GB per second, up to the capacity of the bucket.
Tokens can be spent at up to 3000 per second per volume.
The baseline performance of the volume is equal to the rate at which tokens are accumulated — 3 IOPS per GB per second.
In addition to this, gp2 volumes provide baseline performance of 3 iops per Gb, up to 1Tb (3000 iops). Volumes larger than 1Tb no longer work on the credit system, as they already provide a baseline of 3000 iops. Gp2 volumes have a cap of 10,000 iops regardless of the volume size (so the iops max out for volumes larger than 3.3Tb)
Elastic IP addresses are free when you have them assigned to an instance, feel free to use one! Elastic IPs get disassociated when you stop an instance, so you will get charged in the mean time. The benefit is that you get to keep that IP allocated to your account though, instead of losing it like any other. Once you start the instance you just re-associate it back and you have your old IP again.
Here are the changes associated with the use of Elastic IP addresses
No cost for Elastic IP addresses while in use
* $0.01 per non-attached Elastic IP address per complete hour
* $0.00 per Elastic IP address remap – first 100 remaps / month
* $0.10 per Elastic IP address remap – additional remap / month over 100
If you require any additional information about pricing please reference the link below
The short answer to reducing your AWS EC2 costs – turn off your instances when you don’t need them.
Your AWS bill is just like any other utility bill, you get charged for however much you used that month. Don’t make the mistake of leaving your instances on 24/7 if you’re only using them during certain days and times (ex. Monday – Friday, 9 to 5).
To automatically start and stop your instances, AWS offers an “EC2 scheduler” solution. A better option would be a cloud cost management tool that not only stops and starts your instances automatically, but also tracks your usage and makes sizing recommendations to optimize your cloud costs and maximize your time and savings.
You could potentially save money using Reserved Instances. But, in non-production environments such as dev, test, QA, and training, Reserved Instances are not your best bet. Why is this the case? These environments are less predictable; you may not know how many instances you need and when you will need them, so it’s better to not waste spend on these usage charges. Instead, schedule such instances (preferably using ParkMyCloud). Scheduling instances to be only up 12 hours per day on weekdays will save you 65% – better than all but the most restrictive 3-year RIs!
Well AWS is a web service provider which offers a set of services related to compute, storage, database, network and more to help the business scale and grow
All your concerns are related to AWS EC2 instance, so let me start with an instance
Instance:
An EC2 instance is similar to a server where you can host your websites or applications to make it available Globally
It is highly scalable and works on the pay-as-you-go model
You can increase or decrease the capacity of these instances as per the requirement
AMI:
AMI provides the information required to launch the EC2 instance
AMI includes the pre-configured templates of the operating system that runs on the AWS
Users can launch multiple instances with the same configuration from a single AMI
Snapshot:
Snapshots are the incremental backups for the Amazon EBS
Data in the EBS are stored in S3 by taking point-to-time snapshots
Unique data are only deleted when a snapshot is deleted
They are definitely all chalk and cheese to one another.
A VPN (Virtual Private Network) is essentially an encrypted “channel” connecting two networks, or a machine to a network, generally over the public internet.
A VPS (Virtual Private Server) is a rented virtual machine running on someone else’s hardware. AWS EC2 can be thought of as a VPS, but the term is usually used to describe low-cost products offered by lots of other hosting companies.
A VPC (Virtual Private Cloud) is a virtual network in AWS (Amazon Web Services). It can be divided into private and public subnets, have custom routing rules, have internal connections to other VPCs, etc. EC2 instances and other resources are placed in VPCs similarly to how physical data centers have operated for a very long time.
Elastic IP address is basically the static IP (IPv4) address that you can allocate to your resources.
Now, in case that you allocate IP to the resource (and the resource is running), you are not charged anything. On the other hand, if you create Elastic IP, but you do not allocate it to the resource (or the resource is not running), then you are charged some amount (should be around $0.005 per hour if I remember correctly)
Additional info about these:
You are limited to 5 Elastic IP addresses per region. If you require more than that, you can contact AWS support with a request for additional addresses. You need to have a good reason in order to be approved because IPv4 addresses are becoming a scarce resource.
In general, you should be good without Elastic IPs for most of the use-cases (as every EC2 instance has its own public IP, and you can use load balancers, as well as map most of the resources via Route 53).
One of the use-cases that I’ve seen where my client is using Elastic IP is to make it easier for him to access specific EC2 instance via RDP, as well as do deployment through Visual Studio, as he targets the Elastic IP, and thus does not have to watch for any changes in public IP (in case of stopping or rebooting).
At this time, AWS Transit Gateway does not support inter region attachments. The transit gateway and the attached VPCs must be in the same region. VPC peering supports inter region peering.
The EC2 instance is server instance whilst a Workspace is windows desktop instance
Both Windows Server and Windows workstation editions have desktops. Windows Server Core doesn’t not (and AWS doesn’t have an AMI for Windows Server Core that I could find).
It is possible to SSH into a Windows instance – this is done on port 22. You would not see a desktop when using SSH if you had enabled it. It is not enabled by default.
If you are seeing a desktop, I believe you’re “RDPing” to the Windows instance. This is done with the RDP protocol on port 3389.
Two different protocols and two different ports.
Workspaces doesn’t allow terminal or ssh services by default. You need to use Workspace client. You still can enable RDP or/and SSH but this is not recommended.
Workspaces is a managed desktop service. AWS is taking care of pre-build AMIs, software licenses, joining to domain, scaling etc.
What is Amazon EC2?Scalable, pay-as-you-go compute capacity in the cloud. Amazon Elastic Compute Cloud (Amazon EC2) is a web service that provides resizable compute capacity in the cloud. It is designed to make web-scale computing easier for developers.
What is Amazon WorkSpaces?Easily provision cloud-based desktops that allow end-users to access applications and resources. With a few clicks in the AWS Management Console, customers can provision a high-quality desktop experience for any number of users at a cost that is highly competitive with traditional desktops and half the cost of most virtual desktop infrastructure (VDI) solutions. End-users can access the documents, applications and resources they need with the device of their choice, including laptops, iPad, Kindle Fire, or Android tablets.
Elastic – Amazon EC2 enables you to increase or decrease capacity within minutes, not hours or days. You can commission one, hundreds or even thousands of server instances simultaneously.
Completely Controlled – You have complete control of your instances. You have root access to each one, and you can interact with them as you would any machine.
Flexible – You have the choice of multiple instance types, operating systems, and software packages. Amazon EC2 allows you to select a configuration of memory, CPU, instance storage, and the boot partition size that is optimal for your choice of operating system and application.
On the other hand, Amazon WorkSpaces provides the following key features:
Support Multiple Devices- Users can access their Amazon WorkSpaces using their choice of device, such as a laptop computer (Mac OS or Windows), iPad, Kindle Fire, or Android tablet.
Keep Your Data Secure and Available- Amazon WorkSpaces provides each user with access to persistent storage in the AWS cloud. When users access their desktops using Amazon WorkSpaces, you control whether your corporate data is stored on multiple client devices, helping you keep your data secure.
Choose the Hardware and Software you need- Amazon WorkSpaces offers a choice of bundles providing different amounts of CPU, memory, and storage so you can match your Amazon WorkSpaces to your requirements. Amazon WorkSpaces offers preinstalled applications (including Microsoft Office) or you can bring your own licensed software.
Amazon EBS vs Amazon EFS
An Amazon EBS volume stores data in a single Availability Zone. To attach an Amazon EC2 instance to an EBS volume, both the Amazon EC2 instance and the EBS volume must reside within the same Availability Zone.
Amazon EFS is a regional service. It stores data in and across multiple Availability Zones. The duplicate storage enables you to access data concurrently from all the Availability Zones in the Region where a file system is located. Additionally, on-premises servers can access Amazon EFS using AWS Direct Connect.
Provides secure, resizable compute capacity in the cloud. It makes web-scale cloud computing easier for developers. EC2
EC2 Spot
Run fault-tolerant workloads for up to 90% off. EC2Spot
EC2 Autoscaling
Automatically add or remove compute capacity to meet changes in demand. EC2_AustoScaling
Lightsail
Designed to be the easiest way to launch & manage a virtual private server with AWS. An easy-to-use cloud platform that offers everything need to build an application or website. Lightsail
Batch
Enables developers, scientists, & engineers to easily & efficiently run hundreds of thousands of batch computing jobs on AWS. Fully managed batch processing at any scale. Batch
Containers
Elastic Container Service (ECS)
Highly secure, reliable, & scalable way to run containers. ECS
Run code without thinking about servers. Pay only for the compute time you consume. Lamda
Edge and hybrid
Outposts
Run AWS infrastructure & services on premises for a truly consistent hybrid experience. Outposts
Snow Family
Collect and process data in rugged or disconnected edge environments. SnowFamily
Wavelength
Deliver ultra-low latency application for 5G devices. Wavelenth
VMware Cloud on AWS
Innovate faster, rapidly transition to the cloud, & work securely from any location. VMware_On_AWS
Local Zones
Run latency sensitive applications closer to end-users. LocalZones
Networking and Content Delivery
Use cases
Functionality
Service
Description
Build a cloud network
Define and provision a logically isolated network for your AWS resources
VPC
VPC lets you provision a logically isolated section of the AWS Cloud where you can launch AWS resources in a virtual network that you define. VPC
Connect VPCs and on-premises networks through a central hub
Transit Gateway
Transit Gateway connects VPCs & on-premises networks through a central hub. This simplifies network & puts an end to complex peering relationships. TransitGateway
Provide private connectivity between VPCs, services, and on-premises applications
PrivateLink
PrivateLink provides private connectivity between VPCs & services hosted on AWS or on-premises, securely on the Amazon network. PrivateLink
Route users to Internet applications with a managed DNS service
Route 53
Route 53 is a highly available & scalable cloud DNS web service. Route53
Scale your network design
Automatically distribute traffic across a pool of resources, such as instances, containers, IP addresses, and Lambda functions
Elastic Load Balancing
Elastic Load Balancing automatically distributes incoming application traffic across multiple targets, such as EC2’s, containers, IP addresses, & Lambda functions. ElasticLoadBalancing
Direct traffic through the AWS Global network to improve global application performance
Global Accelerator
Global Accelerator is a networking service that sends user’s traffic through AWS’s global network infrastructure, improving internet user performance by up to 60%. GlobalAccelerator
Secure your network traffic
Safeguard applications running on AWS against DDoS attacks
Shield
Shield is a managed Distributed Denial of Service (DDoS) protection service that safeguards applications running on AWS. Shield
Protect your web applications from common web exploits
WAF
WAF is a web application firewall that helps protect your web applications or APIs against common web exploits that may affect availability, compromise security, or consume excessive resources. WAF
Centrally configure and manage firewall rules
Firewall Manager
Firewall Manager is a security management service which allows to centrally configure & manage firewall rules across accounts & apps in AWS Organization. link text
Build a hybrid IT network
Connect your users to AWS or on-premises resources using a Virtual Private Network
(VPN) – Client
VPN solutions establish secure connections between on-premises networks, remote offices, client devices, & the AWS global network. VPN
Create an encrypted connection between your network and your Amazon VPCs or AWS Transit Gateways
(VPN) – Site to Site
Site-to-Site VPN creates a secure connection between data center or branch office & AWS cloud resources. site_to_site
Establish a private, dedicated connection between AWS and your datacenter, office, or colocation environment
Direct Connect
Direct Connect is a cloud service solution that makes it easy to establish a dedicated network connection from your premises to AWS. DirectConnect
Content delivery networks
Securely deliver data, videos, applications, and APIs to customers globally with low latency, and high transfer speeds
CloudFront
CloudFront expedites distribution of static & dynamic web content. CloudFront
Build a network for microservices architectures
Provide application-level networking for containers and microservices
App Mesh
App Mesh makes it accessible to guide & control microservices operating on AWS. AppMesh
Create, maintain, and secure APIs at any scale
API Gateway
API Gateway allows the user to design & expand their own REST and WebSocket APIs at any scale. APIGateway
Discover AWS services connected to your applications
Cloud Map
Cloud Map permits the name & handles the cloud resources. CloudMap
S3 is the storehouse for the internet i.e. object storage built to store & retrieve any amount of data from anywhere S3
AWS Backup
AWS Backup is an externally-accessible backup provider that makes it easier to align & optimize the backup of data across AWS services in the cloud. AWS_Backup
Amazon EBS
Amazon Elastic Block Store is a web service that provides block-level storage volumes. EBS
Amazon EFS Storage
EFS offers file storage for the user’s Amazon EC2 instances. It’s kind of blob Storage. EFS
Amazon FSx
FSx supply fully managed 3rd-party file systems with the native compatibility & characteristic sets for workloads. It’s available as FSx for Windows server (Fully managed file storage built on Windows Server) & Lustre (Fully managed high-performance file system integrated with S3). FSx_WindowsFSx_Lustre
AWS Storage Gateway
Storage Gateway is a service which connects an on-premises software appliance with cloud-based storage. Storage_Gateway
AWS DataSync
DataSync makes it simple & fast to move large amounts of data online between on-premises storage & S3, EFS, or FSx for Windows File Server. DataSync
AWS Transfer Family
The Transfer Family provides fully managed support for file transfers directly into & out of S3. Transfer_Family
AWS Snow Family
Highly-secure, portable devices to collect & process data at the edge, and migrate data into and out of AWS. Snow_Family
Classification: Object storage: S3 File storage services: Elastic File System, FSx for Windows Servers & FSx for Lustre Block storage: EBS Backup: AWS Backup Data transfer: Storage gateway –> 3 types: Tape, File, Volume. Transfer Family –> SFTP, FTPS, FTP. Edge computing and storage and Snow Family –> Snowcone, Snowball, Snowmobile
Databases
Database type
Use cases
Service
Description
Relational
Traditional applications, ERP, CRM, e-commerce
Aurora, RDS, Redshift
RDS is a web service that makes it easier to set up, control, and scale a relational database in the cloud. AuroraRDSRedshift
Key-value
High-traffic web apps, e-commerce systems, gaming applications
DynamoDB
DynamoDB is a fully administered NoSQL database service that offers quick and reliable performance with integrated scalability. DynamoDB
ElastiCache helps in setting up, managing, and scaling in-memory cache conditions. MemcachedRedis
Document
Content management, catalogs, user profiles
DocumentDB
DocumentDB (with MongoDB compatibility) is a quick, dependable, and fully-managed database service that makes it easy for you to set up, operate, and scale MongoDB-compatible databases.DocumentDB
Wide column
High scale industrial apps for equipment maintenance, fleet management, and route optimization
Keyspaces (for Apache Cassandra)
Keyspaces is a scalable, highly available, and managed Apache Cassandra–compatible database service. Keyspaces
Graph
Fraud detection, social networking, recommendation engines
Neptune
Neptune is a fast, reliable, fully managed graph database service that makes it easy to build and run applications that work with highly connected datasets. Neptune
Time series
IoT applications, DevOps, industrial telemetry
Timestream
Timestream is a fast, scalable, and serverless time series database service for IoT and operational applications that makes it easy to store and analyze trillions of events per day. Timestream
Ledger
Systems of record, supply chain, registrations, banking transactions
Quantum Ledger Database (QLDB)
QLDB is a fully managed ledger database that provides a transparent, immutable, and cryptographically verifiable transaction log owned by a central trusted authority. QLDB
Developer Tools
Service
Description
Cloud9
Cloud9 is a cloud-based IDE that enables the user to write, run, and debug code. Cloud9
CodeArtifact
CodeArtifact is a fully managed artifact repository service that makes it easy for organizations of any size to securely store, publish, & share software packages used in their software development process. CodeArtifact
CodeBuild
CodeBuild is a fully managed service that assembles source code, runs unit tests, & also generates artefacts ready to deploy. CodeBuild
CodeGuru
CodeGuru is a developer tool powered by machine learning that provides intelligent recommendations for improving code quality & identifying an application’s most expensive lines of code. CodeGuru
Cloud Development Kit
Cloud Development Kit (AWS CDK) is an open source software development framework to define cloud application resources using familiar programming languages. CDK
CodeCommit
CodeCommit is a version control service that enables the user to personally store & manage Git archives in the AWS cloud. CodeCommit
CodeDeploy
CodeDeploy is a fully managed deployment service that automates software deployments to a variety of compute services such as EC2, Fargate, Lambda, & on-premises servers. CodeDeploy
CodePipeline
CodePipeline is a fully managed continuous delivery service that helps automate release pipelines for fast & reliable app & infra updates. CodePipeline
CodeStar
CodeStar enables to quickly develop, build, & deploy applications on AWS. CodeStar
CLI
AWS CLI is a unified tool to manage AWS services & control multiple services from the command line & automate them through scripts. CLI
X-Ray
X-Ray helps developers analyze & debug production, distributed applications, such as those built using a microservices architecture. X-Ray
CDK uses the familiarity & expressive power of programming languages for modeling apps. CDK
Corretto
Corretto is a no-cost, multiplatform, production-ready distribution of the OpenJDK. Corretto
Crypto Tools
Cryptography is hard to do safely & correctly. The AWS Crypto Tools libraries are designed to help everyone do cryptography right, even without special expertise. Crypto Tools
Serverless Application Model (SAM)
SAM is an open-source framework for building serverless applications. It provides shorthand syntax to express functions, APIs, databases, & event source mappings. SAM
Tools for developing and managing applications on AWS
Security, Identity, & Compliance
Category
Use cases
Service
Description
Identity & access management
Securely manage access to services and resources
Identity & Access Management (IAM)
IAM is a web service for safely controlling access to AWS services. IAM
Securely manage access to services and resources
Single Sign-On
SSO helps in simplifying, managing SSO access to AWS accounts & business applications. SSO
Identity management for apps
Cognito
Cognito lets you add user sign-up, sign-in, & access control to web & mobile apps quickly and easily. Cognito
Managed Microsoft Active Directory
Directory Service
AWS Managed Microsoft Active Directory (AD) enables your directory-aware workloads & AWS resources to use managed Active Directory (AD) in AWS. DirectoryService
Simple, secure service to share AWS resources
Resource Access Manager
Resource Access Manager (RAM) is a service that enables you to easily & securely share AWS resources with any AWS account or within AWS Organization. RAM
Central governance and management across AWS accounts
Organizations
Organizations helps you centrally govern your environment as you grow and scale your workloads on AWS. Orgs
Detection
Unified security and compliance center
Security Hub
Security Hub gives a comprehensive view of security alerts & security posture across AWS accounts. SecurityHub
Managed threat detection service
GuardDuty
GuardDuty is a threat detection service that continuously monitors for malicious activity & unauthorized behavior to protect AWS accounts, workloads, & data stored in S3. GuardDuty
Analyze application security
Inspector
Inspector is a security vulnerability assessment service improves the security & compliance of the AWS resources. Inspector
Record and evaluate configurations of your AWS resources
Config
Config is a service that enables to assess, audit, & evaluate the configurations of AWS resources. Config
Track user activity and API usage
CloudTrail
CloudTrail is a service that enables governance, compliance, operational auditing, & risk auditing of AWS account. CloudTrail
Security management for IoT devices
IoT Device Defender
IoT Device Defender is a fully managed service that helps secure fleet of IoT devices. IoTDD
Infrastructure protection
DDoS protection
Shield
Shield is a managed DDoS protection service that safeguards apps running. It provides always-on detection & automatic inline mitigations that minimize application downtime & latency. Shield
Filter malicious web traffic
Web Application Firewall (WAF)
WAF is a web application firewall that helps protect web apps or APIs against common web exploits that may affect availability, compromise security, or consume excessive resources. WAF
Central management of firewall rules
Firewall Manager
Firewall Manager eases the user AWS WAF administration & maintenance activities over multiple accounts & resources. FirewallManager
Data protection
Discover and protect your sensitive data at scale
Macie
Macie is a fully managed data (security & privacy) service that uses ML & pattern matching to discover & protect sensitive data. Macie
Key storage and management
Key Management Service (KMS)
KMS makes it easy for to create & manage cryptographic keys & control their use across a wide range of AWS services & in your applications. KMS
Hardware based key storage for regulatory compliance
CloudHSM
CloudHSM is a cloud-based hardware security module (HSM) that enables you to easily generate & use your own encryption keys. CloudHSM
Provision, manage, and deploy public and private SSL/TLS certificates
Certificate Manager
Certificate Manager is a service that easily provision, manage, & deploy public and private SSL/TLS certs for use with AWS services & internal connected resources. ACM
Rotate, manage, and retrieve secrets
Secrets Manager
Secrets Manager assist the user to safely encode, store, & recover credentials for any user’s database & other services. SecretsManager
Incident response
Investigate potential security issues
Detective
Detective makes it easy to analyze, investigate, & quickly identify the root cause of potential security issues or suspicious activities. Detective
Provides scalable, cost-effective business continuity for physical, virtual, & cloud servers. CloudEndure
Compliance
No cost, self-service portal for on-demand access to AWS’ compliance reports
Artifact
Artifact is a web service that enables the user to download AWS security & compliance records. Artifact
Data Lakes & Analytics
Category
Use cases
Service
Description
Analytics
Interactive analytics
Athena
Athena is an interactive query service that makes it easy to analyze data in S3 using standard SQL. Athena
Big data processing
EMR
EMR is the industry-leading cloud big data platform for processing vast amounts of data using open source tools such as Apache Spark, Hive, HBase,Flink, Hudi, & Presto. EMR
Data warehousing
Redshift
The most popular & fastest cloud data warehouse. Redshift
Real-time analytics
Kinesis
Kinesis makes it easy to collect, process, & analyze real-time, streaming data so one can get timely insights. Kinesis
Operational analytics
Elasticsearch Service
Elasticsearch Service is a fully managed service that makes it easy to deploy, secure, & run Elasticsearch cost effectively at scale. ES
Dashboards & visualizations
Quicksight
QuickSight is a fast, cloud-powered business intelligence service that makes it easy to deliver insights to everyone in organization. QuickSight
Data movement
Real-time data movement
1) Amazon Managed Streaming for Apache Kafka (MSK) 2) Kinesis Data Streams 3) Kinesis Data Firehose 4) Kinesis Data Analytics 5) Kinesis Video Streams 6) Glue
MSK is a fully managed service that makes it easy to build & run applications that use Apache Kafka to process streaming data. MSKKDSKDFKDAKVSGlue
Data lake
Object storage
1) S3 2) Lake Formation
Lake Formation is a service that makes it easy to set up a secure data lake in days. A data lake is a centralized, curated, & secured repository that stores all data, both in its original form & prepared for analysis. S3LakeFormation
Backup & archive
1) S3 Glacier 2) Backup
S3 Glacier & S3 Glacier Deep Archive are a secure, durable, & extremely low-cost S3 cloud storage classes for data archiving & long-term backup. S3Glacier
Data catalog
1) Glue 2)) Lake Formation
Refer as above.
Third-party data
Data Exchange
Data Exchange makes it easy to find, subscribe to, & use third-party data in the cloud. DataExchange
Predictive analytics && machine learning
Frameworks & interfaces
Deep Learning AMIs
Deep Learning AMIs provide machine learning practitioners & researchers with the infrastructure & tools to accelerate deep learning in the cloud, at any scale. DeepLearningAMIs
Platform services
SageMaker
SageMaker is a fully managed service that provides every developer & data scientist with the ability to build, train, & deploy machine learning (ML) models quickly. SageMaker
Containers
Use cases
Service
Description
Store, encrypt, and manage container images
ECR
Refer compute section
Run containerized applications or build microservices
ECS
Refer compute section
Manage containers with Kubernetes
EKS
Refer compute section
Run containers without managing servers
Fargate
Fargate is a serverless compute engine for containers that works with both ECS & EKS. Fargate
Run containers with server-level control
EC2
Refer compute section
Containerize and migrate existing applications
App2Container
App2Container (A2C) is a command-line tool for modernizing .NET & Java applications into containerized applications. App2Container
Quickly launch and manage containerized applications
Copilot
Copilot is a command line interface (CLI) that enables customers to quickly launch & easily manage containerized applications on AWS. Copilot
Lambda@Edge is a feature of Amazon CloudFront that lets you run code closer to users of your application, which improves performance & reduces latency.
Aurora Serverless is an on-demand, auto-scaling configuration for Amazon Aurora (MySQL & PostgreSQL-compatible editions), where the database will automatically start up, shut down, & scale capacity up or down based on your application’s needs.
RDS Proxy is a fully managed, highly available database proxy for RDS that makes applications more scalable, resilient to database failures, & more secure.
AppSync is a fully managed service that makes it easy to develop GraphQL APIs by handling the heavy lifting of securely connecting to data sources like AWS DynamoDB, Lambda.
EventBridge is a serverless event bus that makes it easy to connect applications together using data from apps, integrated SaaS apps, & AWS services.
Step Functions is a serverless function orchestrator that makes it easy to sequence Lambda functions & multiple AWS services into business-critical applications.
The easiest way to set up and govern a new, secure multi-account AWS environment. ControlTower
Organizations
Organizations helps centrally govern environment as you grow & scale workloads on AWS Organizations
Well-Architected Tool
Well-Architected Tool helps review the state of workloads & compares them to the latest AWS architectural best practices. WATool
Budgets
Budgets allows to set custom budgets to track cost & usage from the simplest to the most complex use cases. Budgets
License Manager
License Manager makes it easier to manage software licenses from software vendors such as Microsoft, SAP, Oracle, & IBM across AWS & on-premises environments. LicenseManager
Provision
CloudFormation
CloudFormation enables the user to design & provision AWS infrastructure deployments predictably & repeatedly. CloudFormation
Service Catalog
Service Catalog allows organizations to create & manage catalogs of IT services that are approved for use on AWS. ServiceCatalog
OpsWorks
OpsWorks presents a simple and flexible way to create and maintain stacks and applications. OpsWorks
Marketplace
Marketplace is a digital catalog with thousands of software listings from independent software vendors that make it easy to find, test, buy, & deploy software that runs on AWS. Marketplace
Operate
CloudWatch
CloudWatch offers a reliable, scalable, & flexible monitoring solution that can easily start. CloudWatch
CloudTrail
CloudTrail is a service that enables governance, compliance, operational auditing, & risk auditing of AWS account. CloudTrail
Read For Me launched at the 2021 AWS re:Invent Builders’ Fair in Las Vegas. A web application which helps the visually impaired ‘hear documents. With the help of AI services such as Amazon Textract, Amazon Comprehend, Amazon Translate and Amazon Polly utilizing an event-driven architecture and serverless technology, users upload a picture of a document, or anything with text, and within a few seconds “hear” that document in their chosen language.
AWS read for me
2- Delivering code and architectures through AWS Proton and Git
Infrastructure operators are looking for ways to centrally define and manage the architecture of their services, while developers need to find a way to quickly and safely deploy their code. In this session, learn how to use AWS Proton to define architectural templates and make them available to development teams in a collaborative manner. Also, learn how to enable development teams to customize their templates so that they fit the needs of their services.
3- Accelerate front-end web and mobile development with AWS Amplify
User-facing web and mobile applications are the primary touchpoint between organizations and their customers. To meet the ever-rising bar for customer experience, developers must deliver high-quality apps with both foundational and differentiating features. AWS Amplify helps front-end web and mobile developers build faster front to back. In this session, review Amplify’s core capabilities like authentication, data, and file storage and explore new capabilities, such as Amplify Geo and extensibility features for easier app customization with AWS services and better integration with existing deployment pipelines. Also learn how customers have been successful using Amplify to innovate in their businesses.
3- Train ML models at scale with Amazon SageMaker, featuring Aurora
Today, AWS customers use Amazon SageMaker to train and tune millions of machine learning (ML) models with billions of parameters. In this session, learn about advanced SageMaker capabilities that can help you manage large-scale model training and tuning, such as distributed training, automatic model tuning, optimizations for deep learning algorithms, debugging, profiling, and model checkpointing, so that even the largest ML models can be trained in record time for the lowest cost. Then, hear from Aurora, a self-driving vehicle technology company, on how they use SageMaker training capabilities to train large perception models for autonomous driving using massive amounts of images, video, and 3D point cloud data.
AWS RE:INVENT 2020 – LATEST PRODUCTS AND SERVICES ANNOUNCED:
Amazon Elasticsearch Service is uniquely positioned to handle log analytics workloads. With a multitude of open-source and AWS-native service options, users can assemble effective log data ingestion pipelines and couple these with Amazon Elasticsearch Service to build a robust, cost-effective log analytics solution. This session reviews patterns and frameworks leveraged by companies such as Capital One to build an end-to-end log analytics solution using Amazon Elasticsearch Service.
Many companies in regulated industries have achieved compliance requirements using AWS Config. They also need a record of the incidents generated by AWS Config in tools such as ServiceNow for audits and remediation. In this session, learn how you can achieve compliance as code using AWS Config. Through the creation of a noncompliant Amazon EC2 machine, this demo shows how AWS Config triggers an incident into a governance, risk, and compliance system for audit recording and remediation. The session also covers best practices for how to automate the setup process with AWS CloudFormation to support many teams.
3- Cost-optimize your enterprise workloads with Amazon EBS – Compute
Recent times have underscored the need to enable agility while maintaining the lowest total cost of ownership (TCO). In this session, learn about the latest volume types that further optimize your performance and cost, while enabling you to run newer applications on AWS with high availability. Dive deep into the latest AWS volume launches and cost-optimization strategies for workloads such as databases, virtual desktop infrastructure, and low-latency interactive applications.
Location data is a vital ingredient in today’s applications, enabling use cases from asset tracking to geomarketing. Now, developers can use the new Amazon Location Service to add maps, tracking, places, geocoding, and geofences to applications, easily, securely, and affordably. Join this session to see how to get started with the service and integrate high-quality location data from geospatial data providers Esri and HERE. Learn how to move from experimentation to production quickly with location capabilities. This session can help developers who require simple location data and those building sophisticated asset tracking, customer engagement, fleet management, and delivery applications.
In this session, learn how Amazon Connect Tasks makes it easy for you to prioritize, assign, and track all the tasks that agents need to complete, including work in external applications needed to resolve customer issues (such as emails, cases, and social posts). Tasks provides a single place for agents to be assigned calls, chats, and tasks, ensuring agents are focused on the highest-priority work. Also, learn how you can also use Tasks with Amazon Connect’s workflow capabilities to automate task-related actions that don’t require agent interaction. Come see how you can use Amazon Connect Tasks to increase customer satisfaction while improving agent productivity.
New agent-assist capabilities from Amazon Connect Wisdom make it easier and faster for agents to find the information they need to solve customer issues in real time. In this session, see how agents can use simple ML-powered search to find information stored across knowledge bases, wikis, and FAQs, like Salesforce and ServiceNow. Join the session to hear Traeger Pellet Grills discuss how it’s using these new features, along with Contact Lens for Amazon Connect, to deliver real-time recommendations to agents based on issues automatically detected during calls.
Grafana is a popular, open-source data visualization tool that enables you to centrally query and analyze observability data across multiple data sources. Learn how the new Amazon Managed Service for Grafana, announced with Grafana’s parent company Grafana Labs, solves common observability challenges. With the new fully managed service, you can monitor, analyze, and alarm on metrics, logs, and traces while offloading the operational management of security patching, upgrading, and resource scaling to AWS. This session also covers new Grafana capabilities such as advanced security features and native AWS service integrations to simplify configuration and onboarding of data sources.
Prometheus is a popular open-source monitoring and alerting solution optimized for container environments. Customers love Prometheus for its active open-source community and flexible query language, using it to monitor containers across AWS and on-premises environments. Amazon Managed Service for Prometheus is a fully managed Prometheus-compatible monitoring service. In this session, learn how you can use the same open-source Prometheus data model, existing instrumentation, and query language to monitor performance with improved scalability, availability, and security without having to manage the underlying infrastructure.
Today, enterprises use low-power, long-range wide-area network (LoRaWAN) connectivity to transmit data over long ranges, through walls and floors of buildings, and in commercial and industrial use cases. However, this requires companies to operate their own LoRa network server (LNS). In this session, learn how you can use LoRaWAN for AWS IoT Core to avoid time-consuming and undifferentiated development work, operational overhead of managing infrastructure, or commitment to costly subscription-based pricing from third-party service providers.
10-AWS CloudShell: The fastest way to get started with AWS CLI
AWS CloudShell is a free, browser-based shell available from the AWS console that provides a simple way to interact with AWS resources through the AWS command-line interface (CLI). In this session, see an overview of both AWS CloudShell and the AWS CLI, which when used together are the fastest and easiest ways to automate tasks, write scripts, and explore new AWS services. Also, see a demo of both services and how to quickly and easily get started with each.
Industrial organizations use AWS IoT SiteWise to liberate their industrial equipment data in order to make data-driven decisions. Now with AWS IoT SiteWise Edge, you can collect, organize, process, and monitor your equipment data on premises before sending it to local or AWS Cloud destinations—all while using the same asset models, APIs, and functionality. Learn how you can extend the capabilities of AWS IoT SiteWise to the edge with AWS IoT SiteWise Edge.
AWS Fault Injection Simulator is a fully managed chaos engineering service that helps you improve application resiliency by making it easy and safe to perform controlled chaos engineering experiments on AWS. In this session, see an overview of chaos engineering and AWS Fault Injection Simulator, and then see a demo of how to use AWS Fault Injection Simulator to make applications more resilient to failure.
Organizations are breaking down data silos and building petabyte-scale data lakes on AWS to democratize access to thousands of end users. Since its launch, AWS Lake Formation has accelerated data lake adoption by making it easy to build and secure data lakes. In this session, AWS Lake Formation GM Mehul A. Shah showcases recent innovations enabling modern data lake use cases. He also introduces a new capability of AWS Lake Formation that enables fine-grained, row-level security and near-real-time analytics in data lakes.
Machine learning (ML) models may generate predictions that are not fair, whether because of biased data, a model that contains bias, or bias that emerges over time as real-world conditions change. Likewise, closed-box ML models are opaque, making it difficult to explain to internal stakeholders, auditors, external regulators, and customers alike why models make predictions both overall and for individual inferences. In this session, learn how Amazon SageMaker Clarify is providing built-in tools to detect bias across the ML workflow including during data prep, after training, and over time in your deployed model.
Amazon EMR on Amazon EKS introduces a new deployment option in Amazon EMR that allows you to run open-source big data frameworks on Amazon EKS. This session digs into the technical details of Amazon EMR on Amazon EKS, helps you understand benefits for customers using Amazon EMR or running open-source Spark on Amazon EKS, and discusses performance considerations.
Finding unexpected anomalies in metrics can be challenging. Some organizations look for data that falls outside of arbitrary ranges; if the range is too narrow, they miss important alerts, and if it is too broad, they receive too many false alerts. In this session, learn about Amazon Lookout for Metrics, a fully managed anomaly detection service that is powered by machine learning and over 20 years of anomaly detection expertise at Amazon to quickly help organizations detect anomalies and understand what caused them. This session guides you through setting up your own solution to monitor for anomalies and showcases how to deliver notifications via various integrations with the service.
17- Improve application availability with ML-powered insights using Amazon DevOps Guru
As applications become increasingly distributed and complex, developers and IT operations teams need more automated practices to maintain application availability and reduce the time and effort spent detecting, debugging, and resolving operational issues manually. In this session, discover Amazon DevOps Guru, an ML-powered cloud operations service, informed by years of Amazon.com and AWS operational excellence, that provides an easy and automated way to improve an application’s operational performance and availability. See how you can transform your IT operations and reduce mean time to recovery (MTTR) with contextual insights.
Amazon Connect Voice ID provides real-time caller authentication that makes voice interactions in contact centers more secure and efficient. Voice ID uses machine learning to verify the identity of genuine customers by analyzing a caller’s unique voice characteristics. This allows contact centers to use an additional security layer that doesn’t rely on the caller answering multiple security questions, and it makes it easy to enroll and verify customers without disrupting the natural flow of the conversation. Join this session to see how fast and secure ML-based voice authentication can power your contact center.
G4ad instances feature the latest AMD Radeon Pro V520 GPUs and second-generation AMD EPYC processors. These new instances deliver the best price performance in Amazon EC2 for graphics-intensive applications such as virtual workstations, game streaming, and graphics rendering. This session dives deep into these instances, ideal use cases, and performance benchmarks, and it provides a demo.
new capability that enables deployment of Amazon ECS tasks on customer-managed infrastructure. This session covers the evolution of Amazon ECS over time, including new on-premises capabilities to manage your hybrid footprint using a common fully managed control plane and API. You learn some foundational technical details and important tenets that AWS is using to design these capabilities, and the session ends with a short demo of Amazon ECS Anywhere.
Amazon Aurora Serverless is an on-demand, auto scaling configuration of Amazon Aurora that automatically adjusts database capacity based on application demand. With Amazon Aurora Serverless v2, you can now scale database workloads instantly from hundreds to hundreds of thousands of transactions per second and adjust capacity in fine-grained increments to provide just the right amount of database resources. This session dives deep into Aurora Serverless v2 and shows how it can help you operate even the most demanding database workloads worry-free.
Apple delights its customers with stunning devices like iPhones, iPads, MacBooks, Apple Watches, and Apple TVs, and developers want to create applications that run on iOS, macOS, iPadOS, tvOS, watchOS, and Safari. In this session, learn how Amazon is innovating to improve the development experience for Apple applications. Come learn how AWS now enables you to develop, build, test, and sign Apple applications with the flexibility, scalability, reliability, and cost benefits of Amazon EC2.
When industrial equipment breaks down, this means costly downtime. To avoid this, you perform maintenance at regular intervals, which is inefficient and increases your maintenance costs. Predictive maintenance allows you to plan the required repair at an optimal time before a breakdown occurs. However, predictive maintenance solutions can be challenging and costly to implement given the high costs and complexity of sensors and infrastructure. You also have to deal with the challenges of interpreting sensor data and accurately detecting faults in order to send alerts. Come learn how Amazon Monitron helps you solve these challenges by offering an out-of-the-box, end-to-end, cost-effective system.
As data grows, we need innovative approaches to get insight from all the information at scale and speed. AQUA is a new hardware-accelerated cache that uses purpose-built analytics processors to deliver up to 10 times better query performance than other cloud data warehouses by automatically boosting certain types of queries. It’s available in preview on Amazon Redshift RA3 nodes in select regions at no extra cost and without any code changes. Attend this session to understand how AQUA works and which analytic workloads will benefit the most from AQUA.
Figuring out if a part has been manufactured correctly, or if machine part is damaged, is vitally important. Making this determination usually requires people to inspect objects, which can be slow and error-prone. Some companies have applied automated image analysis—machine vision—to detect anomalies. While useful, these systems can be very difficult and expensive to maintain. In this session, learn how Amazon Lookout for Vision can automate visual inspection across your production lines in few days. Get started in minutes, and perform visual inspection and identify product defects using as few as 30 images, with no machine learning (ML) expertise required.
AWS Proton is a new service that enables infrastructure operators to create and manage common container-based and serverless application stacks and automate provisioning and code deployments through a self-service interface for their developers. Learn how infrastructure teams can empower their developers to use serverless and container technologies without them first having to learn, configure, and maintain the underlying resources.
Migrating applications from SQL Server to an open-source compatible database can be time-consuming and resource-intensive. Solutions such as the AWS Database Migration Service (AWS DMS) automate data and database schema migration, but there is often more work to do to migrate application code. This session introduces Babelfish for Aurora PostgreSQL, a new translation layer for Amazon Aurora PostgreSQL that enables Amazon Aurora to understand commands from applications designed to run on Microsoft SQL Server. Learn how Babelfish for Aurora PostgreSQL works to reduce the time, risk, and effort of migrating Microsoft SQL Server-based applications to Aurora, and see some of the capabilities that make this possible.
Over the past decade, we’ve witnessed a digital transformation in healthcare, with organizations capturing huge volumes of patient information. But this data is often unstructured and difficult to extract, with information trapped in clinical notes, insurance claims, recorded conversations, and more. In this session, explore how the new Amazon HealthLake service removes the heavy lifting of organizing, indexing, and structuring patient information to provide a complete view of each patient’s health record in the FHIR standard format. Come learn how to use prebuilt machine learning models to analyze and understand relationships in the data, identify trends, and make predictions, ultimately delivering better care for patients.
When business users want to ask new data questions that are not answered by existing business intelligence (BI) dashboards, they rely on BI teams to create or update data models and dashboards, which can take several weeks to complete. In this session, learn how Merlin lets users simply enter their questions on the Merlin search bar and get answers in seconds. Merlin uses natural language processing and semantic data understanding to make sense of the data. It extracts business terminologies and intent from users’ questions, retrieves the corresponding data from the source, and returns the answer in the form of a number, chart, or table in Amazon QuickSight.
When developers publish images publicly for anyone to find and use—whether for free or under license—they must make copies of common images and upload them to public websites and registries that do not offer the same availability commitment as Amazon ECR. This session explores a new Amazon public registry, Amazon ECR Public, built with AWS experience operating Amazon ECR. Here, developers can share georeplicated container software worldwide for anyone to discover and download. Developers can quickly publish public container images with a single command. Learn how anyone can browse and pull container software for use in their own applications.
Industrial companies are constantly working to avoid unplanned downtime due to equipment failure and to improve operational efficiency. Over the years, they have invested in physical sensors, data connectivity, data storage, and dashboarding to monitor equipment and get real-time alerts. Current data analytics methods include single-variable thresholds and physics-based modeling approaches, which are not effective at detecting certain failure types and operating conditions. In this session, learn how Amazon Lookout for Equipment uses data from your sensors to detect abnormal equipment behavior so that you can take action before machine failures occur and avoid unplanned downtime.
In this session, learn how Contact Lens for Amazon Connect enables your contact center supervisors to understand the sentiment of customer conversations, identify call drivers, evaluate compliance with company guidelines, and analyze trends. This can help supervisors train agents, replicate successful interactions, and identify crucial company and product feedback. Your supervisors can conduct fast full-text search on all transcripts to quickly troubleshoot customer issues. With real-time capabilities, you can get alerted to issues during live customer calls and deliver proactive assistance to agents while calls are in progress, improving customer satisfaction. Join this session to see how real-time ML-powered analytics can power your contact center.
AWS Local Zones places compute, storage, database, and other select services closer to locations where no AWS Region exists today. Last year, AWS launched the first two Local Zones in Los Angeles, and organizations are using Local Zones to deliver applications requiring ultra-low-latency compute. AWS is launching Local Zones in 15 metro areas to extend access across the contiguous US. In this session, learn how you can run latency-sensitive portions of applications local to end users and resources in a specific geography, delivering single-digit millisecond latency for use cases such as media and entertainment content creation, real-time gaming, reservoir simulations, electronic design automation, and machine learning.
Your customers expect a fast, frictionless, and personalized customer service experience. In this session, learn about Amazon Connect Customer Profiles—a new unified customer profile capability to allow agents to provide more personalized service during a call. Customer Profiles automatically brings together customer information from multiple applications, such as Salesforce, Marketo, Zendesk, ServiceNow, and Amazon Connect contact history, into a unified customer profile. With Customer Profiles, agents have the information they need, when they need it, directly in their agent application, resulting in improved customer satisfaction and reduced call resolution times (by up to 15%).
Preparing training data can be tedious. Amazon SageMaker Data Wrangler provides a faster, visual way to aggregate and prepare data for machine learning. In this session, learn how to use SageMaker Data Wrangler to connect to data sources and use prebuilt visualization templates and built-in data transforms to streamline the process of cleaning, verifying, and exploring data without having to write a single line of code. See a demonstration of how SageMaker Data Wrangler can be used to perform simple tasks as well as more advanced use cases. Finally, see how you can take your data preparation workflows into production with a single click.
To provide access to critical resources when needed and also limit the potential financial impact of an application outage, a highly available application design is critical. In this session, learn how you can use Amazon CloudWatch and AWS X-Ray to increase the availability of your applications. Join this session to learn how AWS observability solutions can help you proactively detect, efficiently investigate, and quickly resolve operational issues. All of which help you manage and improve your application’s availability.
Security is critical for your Kubernetes-based applications. Join this session to learn about the security features and best practices for Amazon EKS. This session covers encryption and other configurations and policies to keep your containers safe.
Don’t miss the AWS Partner Keynote with Doug Yeum, head of Global Partner Organization; Sandy Carter, vice president, Global Public Sector Partners and Programs; and Dave McCann, vice president, AWS Migration, Marketplace, and Control Services, to learn how AWS is helping partners modernize their businesses to help their customers transform.
Join Swami Sivasubramanian for the first-ever Machine Learning Keynote, live at re:Invent. Hear how AWS is freeing builders to innovate on machine learning with the latest developments in AWS machine learning, demos of new technology, and insights from customers.
Join Peter DeSantis, senior vice president of Global Infrastructure and Customer Support, to learn how AWS has optimized its cloud infrastructure to run some of the world’s most demanding womath.ceilrkloads and give your business a competitive edge.
Join Dr. Werner Vogels at 8:00AM (PST) as he goes behind the scenes to show how Amazon is solving today’s hardest technology problems. Based on his experience working with some of the largest and most successful applications in the world, Dr. Vogels shares his insights on building truly resilient architectures and what that means for the future of software development.
Cloud architecture has evolved over the years as the nature of adoption has changed and the level of maturity in our thinking continues to develop. In this session, Rudy Valdez, VP of Solutions Architecture and Training & Certification, walks
Organizations around the world are minimizing operations and maximizing agility by developing with serverless building blocks. Join David Richardson, VP of Serverless, for a closer look at the serverless programming model, including event-dri
AWS edge computing solutions provide infrastructure and software that move data processing and analysis as close to the endpoint where data is generated as required by customers. In this session, learn about new edge computing capabilities announced at re:Invent and how customers are using purpose-built edge solutions to extend the cloud to the edge.
Topics on simplifying container deployment, legacy workload migration using containers, optimizing costs for containerized applications, container architectural choices, and more.
Do you need to know what’s happening with your applications that run on Amazon EKS? In this session, learn how you can combine open-source tools, such as Prometheus and Grafana, with Amazon CloudWatch using CloudWatch Container Insights. Come to this session for a demo of Prometheus metrics with Container Insights.
The hard part is done. You and your team have spent weeks poring over pull requests, building microservices and containerizing them. Congrats! But what do you do now? How do you get those services on AWS? How do you manage multiple environments? How do you automate deployments? AWS Copilot is a new command line tool that makes building, developing, and operating containerized applications on AWS a breeze. In this session, learn how AWS Copilot can help you and your team manage your services and deploy them to production, safely and delightfully.
Five years ago, if you talked about containers, the assumption was that you were running them on a Linux VM. Fast forward to today, and now that assumption is challenged—in a good way. Come to this session to explore the best data plane option to meet your needs. This session covers the advantages of different abstraction models (Amazon EC2 or AWS Fargate), the operating system (Linux or Windows), the CPU architecture (x86 or Arm), and the commercial model (Spot or On-Demand Instances.)
Security is critical for your Kubernetes-based applications. Join this session to learn about the security features and best practices for Amazon EKS. This session covers encryption and other configurations and policies to keep your containers safe.
In this session, learn how the Commonwealth Bank of Australia (CommBank) built a platform to run containerized applications in a regulated environment and then replicated it across multiple departments using Amazon EKS, AWS CDK, and GitOps. This session covers how to manage multiple multi-team Amazon EKS clusters across multiple AWS accounts while ensuring compliance and observability requirements and integrating Amazon EKS with AWS Identity and Access Management, Amazon CloudWatch, AWS Secrets Manager, Application Load Balancer, Amazon Route 53, and AWS Certificate Manager.
Amazon EKS is a fully managed service that makes it easy to deploy, manage, and scale containerized applications using Kubernetes on AWS. Join this session to learn about how Verizon runs its core applications on Amazon EKS at scale. Verizon also discusses how it worked with AWS to overcome several post-Amazon EKS migration challenges and ensured that the platform was robust.
Containers have helped revolutionize modern application architecture. While managed container services have enabled greater agility in application development, coordinating safe deployments and maintainable infrastructure has become more important than ever. This session outlines how to integrate CI/CD best practices into deployments of your Amazon ECS and AWS Fargate services using pipelines and the latest in AWS developer tooling.
With Amazon ECS, you can run your containerized workloads securely and with ease. In this session, learn how to utilize the full spectrum of Amazon ECS security features and its tight integrations with AWS security features to help you build highly secure applications.
Do you have to budget your spend for container workloads? Do you need to be able to optimize your spend in multiple services to reduce waste? If so, this session is for you. It walks you through how you can use AWS services and configurations to improve your cost visibility. You learn how you can select the best compute options for your containers to maximize utilization and reduce duplication. This combined with various AWS purchase options helps you ensure that you’re using the best options for your services and your budget.
You have a choice of approach when it comes to provisioning compute for your containers. Some users prefer to have more direct control of their instances, while others could do away with the operational heavy lifting. AWS Fargate removes the need to provision and manage servers, lets you specify and pay for resources per application, and improves security through application isolation by design. This session explores the benefits and considerations of running on Fargate or directly on Amazon EC2 instances. You hear about new and upcoming features and learn how Amenity Analytics benefits from the serverless operational model.
Are you confused by the many choices of containers services that you can run on AWS? This session explores all your options and the advantages of each. Whether you are just beginning to learn Docker or are an expert with Kubernetes, join this session to learn how to pick the right services that would work best for you.
Leading containers migration and modernization initiatives can be daunting, but AWS is making it easier. This session explores architectural choices and common patterns, and it provides real-world customer examples. Learn about core technologies to help you build and operate container environments at scale. Discover how abstractions can reduce the pain for infrastructure teams, operators, and developers. Finally, hear the AWS vision for how to bring it all together with improved usability for more business agility.
As the number of services grow within an application, it becomes difficult to pinpoint the exact location of errors, reroute traffic after failures, and safely deploy code changes. In this session, learn how to integrate AWS App Mesh with Amazon ECS to export monitoring data and implement consistent communications control logic across your application. This makes it easy to quickly pinpoint the exact locations of errors and automatically reroute network traffic, keeping your container applications highly available and performing well.
Enterprises are continually looking to develop new applications using container technologies and leveraging modern CI/CD tools to automate their software delivery lifecycles. This session highlights the types of applications and associated factors that make a candidate suitable to be containerized. It also covers best practices that can be considered as you embark on your modernization journey.
Because of its security, reliability, and scalability capabilities, Amazon Elastic Kubernetes Service (Amazon EKS) is used by organization in their most sensitive and mission-critical applications. This session focuses on how Amazon EKS networking works with an Amazon VPC and how to expose your Kubernetes application using Elastic Load Balancing load balancers. It also looks at options for more efficient IP address utilization.
Network design is a critical component in your large-scale migration journey. This session covers some of the real-world networking challenges faced when migrating to the cloud. You learn how to overcome these challenges by diving deep into topics such as establishing private connectivity to your on-premises data center and accelerating data migrations using AWS Direct Connect/Direct Connect gateway, centralizing and simplifying your networking with AWS Transit Gateway, and extending your private DNS into the cloud. The session also includes a discussion of related best practices.
5G will be the catalyst for the next industrial revolution. In this session, come learn about key technical use cases for different industry segments that will be enabled by 5G and related technologies, and hear about the architectural patterns that will support these use cases. You also learn about AWS-enabled 5G reference architectures that incorporate AWS services.
AWS offers a breadth and depth of machine learning (ML) infrastructure you can use through either a do-it-yourself approach or a fully managed approach with Amazon SageMaker. In this session, explore how to choose the proper instance for ML inference based on latency and throughput requirements, model size and complexity, framework choice, and portability. Join this session to compare and contrast compute-optimized CPU-only instances, such as Amazon EC2 C4 and C5; high-performance GPU instances, such as Amazon EC2 G4 and P3; cost-effective variable-size GPU acceleration with Amazon Elastic Inference; and highest performance/cost with Amazon EC2 Inf1 instances powered by custom-designed AWS Inferentia chips.
When it comes to architecting your workloads on VMware Cloud on AWS, it is important to understand design patterns and best practices. Come join this session to learn how you can build well-architected cloud-based solutions for your VMware workloads. This session covers infrastructure designs with native AWS service integrations across compute, networking, storage, security, and operations. It also covers the latest announcements for VMware Cloud on AWS and how you can use these new features in your current architecture.
One of the most critical phases of executing a migration is moving traffic from your existing endpoints to your newly deployed resources in the cloud. This session discusses practices and patterns that can be leveraged to ensure a successful cutover to the cloud. The session covers preparation, tools and services, cutover techniques, rollback strategies, and engagement mechanisms to ensure a successful cutover.
AWS DeepRacer is the fastest way to get rolling with machine learning. Developers of all skill levels can get hands-on, learning how to train reinforcement learning models in a cloud based 3D racing simulator. Attend a session to get started, and then test your skills by competing for prizes and glory in an exciting autonomous car racing experience throughout re:Invent!
AWS DeepRacer gives you an interesting and fun way to get started with reinforcement learning (RL). RL is an advanced machine learning (ML) technique that takes a very different approach to training models than other ML methods. Its super power is that it learns very complex behaviors without requiring any labeled training data, and it can make short-term decisions while optimizing for a longer-term goal. AWS DeepRacer makes it fast and easy to build models in Amazon SageMaker and train, test, and iterate quickly and easily on the track in the AWS DeepRacer 3D racing simulator.
As more organizations are looking to migrate to the cloud, Red Hat OpenShift Service offers a proven, reliable, and consistent platform across the hybrid cloud. Red Hat and AWS recently announced a fully managed joint service that can be deployed directly from the AWS Management Console and can integrate with other AWS Cloud-native services. In this session, you learn about this new service, which delivers production-ready Kubernetes that many enterprises use on premises today, enhancing your ability to shift workloads to the AWS Cloud and making it easier to adopt containers and deploy applications faster. This presentation is brought to you by Red Hat, an AWS Partner.
Event-driven architecture can help you decouple services and simplify dependencies as your applications grow. In this session, you learn how Amazon EventBridge provides new options for developers who are looking to gain the benefits of this approach.
Amazon Timestream is a fast, scalable, and serverless time series database service for IoT and operational applications that makes it easy to store and analyze trillions of events per day at as little as one-tenth the cost of relational databases. In this session, dive deep on Amazon Timestream features and capabilities, including its serverless automatic scaling architecture, its storage tiering that simplifies your data lifecycle management, its purpose-built query engine that lets you access and analyze recent and historical data together, and its built-in time series analytics functions that help you identify trends and patterns in your data in near-real time.
Savings Plans is a flexible pricing model that allows you to save up to 72 percent on Amazon EC2, AWS Fargate, and AWS Lambda. Many AWS users have adopted Savings Plans since its launch in November 2019 for the simplicity, savings, ease of use, and flexibility. In this session, learn how many organizations use Savings Plans to drive more migrations and business outcomes. Hear from Comcast on their compute transformation journey to the cloud and how it started with RIs. As their cloud usage evolved, they adopted Savings Plans to drive business outcomes such as new architecture patterns.
The ability to deploy only configuration changes, separate from code, means you do not have to restart the applications or services that use the configuration and changes take effect immediately. In this session, learn best practices used by teams within Amazon to rapidly release features at scale. Learn about a pattern that uses AWS CodePipeline and AWS AppConfig that will allow you to roll out application configurations without taking applications out of service. This will help you ship features faster across complex environments or regions.
I watched (binged) the A Cloud Guru course in two days and did the 6 practice exams over a week. I originally was only getting 70%’s on the exams, but continued doing them on my free time (to the point where I’d have 15 minutes and knock one out on my phone lol) and started getting 90%’s. – A mix of knowledge vs memorization tbh. Just make sure you read why your answers are wrong.
I don’t really have a huge IT background, although will note I work in a DevOps (1 1/2 years) environment; so I do use AWS to host our infrastructure. However, the exam is very high level compared to what I do/services I use. I’m fairly certain with zero knowledge/experience, someone could pass this within two weeks. AWS is also currently promoting a “get certified” challenge and is offering 50% off.
Went through the entire CloudAcademy course. Most of the info went out the other ear. Got a 67% on their final exam. Took the ExamPro free exam, got 69%.
Was going to take it last Saturday, but I bought TutorialDojo’s exams on Udemy. Did one Friday night, got a 50% and rescheduled it a week later to today Sunday.
Took 4 total TD exams. Got a 50%, 54%, 67%, and 64%. Even up until last night I hated the TD exams with a passion, I thought they were covering way too much stuff that didn’t even pop up in study guides I read. Their wording for some problems were also atrocious. But looking back, the bulk of my “studying” was going through their pretty well written explanations, and their links to the white papers allowed me to know what and where to read.
Not sure what score I got yet on the exam. As someone who always hated testing, I’m pretty proud of myself. I also had to take a dump really bad starting at around question 25. Thanks to TutorialsDojo Jon Bonso for completely destroying my confidence before the exam, forcing me to up my game. It’s better to walk in way over prepared than underprepared.
I would like to thank this community for recommendations about exam preparation. It was wayyyy easier than I expected (also way easier than TD practice exams scenario-based questions-a lot less wordy on real exam). I felt so unready before the exam that I rescheduled the exam twice. Quick tip: if you have limited time to prepare for this exam, I would recommend scheduling the exam beforehand so that you don’t procrastinate fully.
Resources:
-Stephane’s course on Udemy (I have seen people saying to skip hands-on videos but I found them extremely helpful to understand most of the concepts-so try to not skip those hands-on)
-Tutorials Dojo practice exams (I did only 3.5 practice tests out of 5 and already got 8-10 EXACTLY worded questions on my real exam)
Previous Aws knowledge:
-Very little to no experience (deployed my group’s app to cloud via Elastic beanstalk in college-had 0 clue at the time about what I was doing-had clear guidelines)
Preparation duration: -2 weeks (honestly watched videos for 12 days and then went over summary and practice tests on the last two days)
I used Stephane Maarek on Udemy. Purchased his course and the 6 Practice Exams. Also got Neal Davis’ 500 practice questions on Udemy. I took Stephane’s class over 2 days, then spent the next 2 weeks going over the tests (3~4 per day) till I was constantly getting over 80% – passed my exam with a 882.
What an adventure, I’ve never really gieven though to getting a cert until one day it just dawned on me that it’s one of the few resources that are globally accepted. So you can approach any company and basically prove you know what’s up on AWS 😀
Passed with two weeks of prep (after work and weekends)
This was just a nice structured presentation that also gives you the powerpoint slides plus cheatsheets and a nice overview of what is said in each video lecture.
Udemy – AWS Certified Cloud Practitioner Practice Exams, created by Jon Bonso**, Tutorials Dojo**
These are some good prep exams, they ask the questions in a way that actually make you think about the related AWS Service. With only a few “Bullshit! That was asked in a confusing way” questions that popped up.
I took CCP 2 days ago and got the pass notification right after submitting the answers. In about the next 3 hours I got an email from Credly for the badge. This morning I got an official email from AWS congratulating me on passing, the score is much higher than I expected. I took Stephane Maarek’s CCP course and his 6 demo exams, then Neal Davis’ 500 questions also. On all the demo exams, I took 1 fail and all passes with about 700-800. But in the real exam, I got 860. The questions in the real exam are kind of less verbose IMO, but I don’t truly agree with some people I see on this sub saying that they are easier. Just a little bit of sharing, now I’ll find something to continue ^^
Passed the exam! Spent 25 minutes answering all the questions. Another 10 to review. I might come back and update this post with my actual score.
Background
– A year of experience working with AWS (e.g., EC2, Elastic Beanstalk, Route 53, and Amplify).
– Cloud development on AWS is not my strong suit. I just Google everything, so my knowledge is very spotty. Less so now since I studied for this exam.
Study stats
– Spent three weeks studying for the exam.
– Studied an hour to two every day.
– Solved 800-1000 practice questions.
– Took 450 screenshots of practice questions and technology/service descriptions as reference notes to quickly swift through on my phone and computer for review. Screenshots were of questions that I either didn’t know, knew but was iffy on, or those I believed I’d easily forget.
– Made 15-20 pages of notes. Chill. Nothing crazy. This is on A4 paper. Free-form note taking. With big diagrams. Around 60-80 words per page.
– I was getting low-to-mid 70%s on Neal Davis’s and Stephane Maarek’s practice exams. Highest score I got was an 80%.
– I got a 67(?)% on one of Stephane Maarek’s exams. The only sub-70% I ever got on any practice test. I got slightly anxious. But given how much harder Maarek’s exams are compared to the actual exam, the anxiety was undue.
– Finishing the practice exams on time was never a problem for me. I would finish all of them comfortably within 35 minutes.
Resources used
– AWS Cloud Practitioner Essentials on the AWS Training and Certification Portal
– AWS Certified Cloud Practitioner Practice Tests (Book) by Neal Davis
– 6 Practice Exams | AWS Certified Cloud Practitioner CLF-C01 by Stephane Maarek*
– Certified Cloud Practitioner Course by Exam Pro (Paid Version)**
– One or two free practice exams found by a quick Google search
*Regarding Exam Pro: I went through about 40% of the video lectures. I went through all the videos in the first few sections but felt that watching the lectures was too slow and laborious even at 1.5-2x speed. (The creator, for the most part, reads off of the slides, adding brief comments here and there.) So, I decided to only watch the video lectures for sections I didn’t have a good grasp on. (I believe the video lectures provided in the course are just split versions of the full length course available for free on YouTube under the freeCodeCamp channel, here.) The online course provides five practice exams. I did not take any of them.
**Regarding Stephane Maarek: I only took his practice exams. I did not take his study guide course.
Notes
– My study regimen (i.e., an hour to two every day for three weeks) was overkill.
– The questions on the practice exams created by Neal Davis and Stephane Maarek were significantly harder than those on the actual exam. I believe I could’ve passed without touching any of these resources.
– I retook one or two practice exams out of the 10+ I’ve taken. I don’t think there’s a need to retake the exams as long as you are diligent about studying the questions and underlying concepts you got wrong. I reviewed all the questions I missed on every practice exam the day before.
What would I do differently?
– Focus on practice tests only. No video lectures.
– Focus on the technologies domain. You can intuit your way through questions in the other domains.
I thank you all for helping me through this process! Couldn’t have done it without all of the recommendations and guidance on this page.
Background: I am a back-end developer that works 12 hours a day for corporate America, so no time to study (or do anything) but I made it work.
Could I have probably gone for SAA first? Yeah, but I wanted to prove to myself that I could do it. I studied for about a month. I used Maarek’s Udemy course at 1.5x speed and I couldn’t recommend it more. I also used his practice exams. I’ll be honest, I took 5 practice exams and got somehow managed to fail every single one in the mid 60’s lol. Cleared the exam with an 800. Practice exams WAY harder.
My 2 cents on must knows:
AWS Shared Security Model (who owns what)
Everything Billing (EC2 instance, S3, different support plans)
I had a few ML questions that caught me off guard
VPC concepts – i.e. subnets, NACL, Transit Gateway
I studied solidly for two weeks, starting with Tutorials Dojo (which was recommended somewhere on here). I turned all of their vocabulary words and end of module questions into note cards. I did the same with their final assessment and one free exam.
During my second week, I studied the cards for anywhere from one to two hours a day, and I’d randomly watch videos on common exam questions.
The last thing I did was watch a 3 hr long video this morning that walks you through setting up AWS Instances. The visual of setting things up filled in a lot of holes.
I had some PSI software problems, and ended up getting started late. I was pretty dejected towards the end of the exam, and was honestly (and pleasantly) surprised to see that I passed.
Hopefully this helps someone. Keep studying and pushing through – if you know it, you know it. Even if you have a bad start. Cheers 🍻
Amazon Relational Database Service (Amazon RDS) for Db2 now supports local time zones. You can now set the time zone for your Amazon RDS for Db2 instances to the local time zone of your choice.
Today, AWS AppFabric announces support for SentinelOne Singularity Cloud as data source and compatible security destination. Starting now, IT administrators and security analysts can use AppFabric to quickly integrate with 27 supported SaaS applications, aggregate enriched and normalized SaaS audit logs, and audit end-user access across their SaaS apps.
Amazon VPC announces a network interface setting to dynamically remove and add an auto assigned public IPv4 address on EC2 instances. With this capability, customers that no longer require an auto assigned public IPv4 address on their EC2 instance can remove the public IPv4 address, and if needed attach back a new public IPv4 address, by modifying the public IP setting on the network interface. Before today, once a public IPv4 address was auto assigned to EC2 instance it was not possible to remove it. It remained on the network interface for the lifetime of the EC2 instance.
Amazon Relational Database Service (Amazon RDS) for PostgreSQL, MySQL, and MariaDB now supports AWS Graviton2-based M6gd database instances in Asia Pacific (Hyderabad), Europe (Spain, Zurich), and Middle East (UAE) regions.
Foundation model evaluations with SageMaker Clarify is now generally available. This capability helps data scientists and machine learning engineers evaluate, compare, and select foundation models based on a variety of criteria across different tasks within minutes.
Starting today, AWS Global Accelerator supports application endpoints in the AWS Canada West (Calgary) Region, expanding the number of supported AWS Regions to twenty-nine.
Hello, I want to prepare for the aws associate certifications. I have a study plan and tools to review and note taking. Who is down to study together from time to time. submitted by /u/oussamanhairech [link] [comments]
Hi everyone. I have a functional background with some security knowledge. I am looking to increase my knowledge and also need the certification for work. Any guidance or what has worked to clear the AWS security certification ? Anything that has worked for others. Your advice is highly appreciated. submitted by /u/Wide-Entrepreneur658 [link] [comments]
Hi All, hope you all doing good? I've a question that someone might have asked before..Just need some clarification about going for CCNA or Aws (Certified Cloud practitioner) As I'm a beginner I have no idea about networking or cloud but my goal is to become an Cloud engineer in Future. Shall I need to Do CCNA or Can jump straight to CCP as a beginner I mean to say CCNA is it Necessary to start the career in Cloud or will I be learning about networking during CCP training?? submitted by /u/Upper_Aspect_4353 [link] [comments]
Hello Recently attempted AWS Data Engineer Associate exam (today) and at the final screen can see only this "Thank you for taking the AWS Certified Data Engineer - Associate exam" In previous certifications exams (for associate, professional , specialty) the results of PASS always came on the go in real time on final screen. But I attempted those exams in 2022 Has something changed since then if anyone is aware of the process ? Or should I assume this as FAIL result ? PS : I am aware that one should wait for 5 business days for AWS results per the process. Update : I got the results after 9 hours approximately and it was a PASS submitted by /u/Capital_Window_7382 [link] [comments]
Hi guys, I just completed my Cloud practitioner and want to proceed to Solutions Architect. Was wondering if anyone knows websites or ways to get at least 50% discount code for AWS. I have been working as analyst and L1 triage and want to move on to cloud. Still unsure on which area I should be focusing on but I have interest on cloud and that’s my motivation in pursuing the certifications so I appreciate any feedback and advise. Thank you! submitted by /u/Fearless_Guidance_10 [link] [comments]
I Want to do an AWS certification which can provide me with most job opportunities in the current market, At least getting an Internship in the current US market. I can do any one of them right now. Please guide me which one has most potential to land me a decent internship. I am open to suggestion's for any other AWS cert as well if seem feasible to my requirements. Thanks! submitted by /u/Level-Cartographer72 [link] [comments]
What happened to ETC, the platform has been under maintenance for a couple of months now. I had saved up a couple of points with the aim of using them as vouchers. submitted by /u/Stanley397018 [link] [comments]
What is the best resource to prepare for AWS EKS certification exam (like the list of questions/answers, mock exam, etc)? submitted by /u/AdSubstantial8808 [link] [comments]
We are excited to announce that Amazon GameLift now supports containers for building, deploying, and running game server packages. Amazon GameLift is a fully managed service that allows developers to quickly manage and scale dedicated game servers for multiplayer games. With this preview release, GameLift now supports end-to-end development of containerized workloads, including deployment and scaling on-premises, in the cloud, or hybrid configurations.
Hi! I have done my CCP recently and I would kinda enjoy architecting cloud systems. Is there any point of doing SAA and SysOps if I have no IT background. Also what about the new data cert? Thanks. submitted by /u/GPX722 [link] [comments]
AWS DataSync now lets you enable and disable task schedules. Using this new feature, you can temporarily disable scheduled executions of your task to accommodate events such as maintenance on your storage systems. Once the event is complete, you can enable your task schedule to resume execution of your task at the next scheduled interval.
AWS CodeBuild now supports managed GitHub Action self-hosted runners. Customers can configure their CodeBuild projects to receive GitHub Actions workflow job events and run them on CodeBuild ephemeral hosts. AWS CodeBuild is a fully managed continuous integration service that compiles source code, runs tests, and produces software packages ready for deployment.
NoSQL Workbench for Amazon DynamoDB is a client-side application that provides data modeling and query development features to help you design, create, and work with DynamoDB tables. You can use the NoSQL Workbench operation builder to build and save operations for viewing, updating, and exploring your live datasets. You can even generate code in multiple programming languages. Today, we are pleased to announce quality enhancements to the operation builder to help customers better navigate, run operations, and browse their DynamoDB tables.
This might be unrelated but I don't know where else to ask. I have been working as a Windows Administrator for the past 2 years, recently I have been getting into learning AWS and am thinking about preparing for the SAA-C03 exam. But I have been told by some of my friends who are devops engineers or sysops admins that pivoting into a cloud architect now would be like starting from scratch since the job market wants cloud architects who also have experience into programming as well(which I don't have), basically asking for someone with devops skillset but working on a sysadmin's pay. Please suggest whether it would be a good idea for me to get into AWS now or pivot to something else. submitted by /u/ryuu_shogun [link] [comments]
Today, AWS Direct Connect now enables AWS Direct Connect Service Delivery Partners (AWS Direct Connect Partners) to support 25 Gbps hosted connection capacity .
Hi. I would like to ask some advice on career expansion.. I am currently in data analysis...and curious about cloud. No background nor prior knowledge of it. I was wondering if I can take the CCP without any of the comptia A+ or network certs etc. Read from a forum comment that one needs to have an understanding of these before foraying into cloud...what can u recommend.. Thank you. submitted by /u/ILoveSpring_4401 [link] [comments]
hello, so i recently got laid off due to surplus as a software engineer 1 i am considering getting some AWS certs so i can apply for more cloud based roles and/or transition into security work as i don’t think i love being a developer should i pursue the professional track for SAA? is that worth it? are there any pre-reqs u suggest for SCS? i saw CCP is a pre-req but i read a lot about how that can be skipped. what resources do you recommend to study for these exams? i’d prefer resources that are affordable/free as i previously stated i just got laid off. i have heard about: adrian cantrill, udemy, tutorial dojo, plura insights if u have any experience or recommendations from these resources let me know i’m more so interested in purchasing just 1 course that would prep me for each test any recommendations for this hard time for me would be great as i am just wanting to possibly move into security or something else tech related that may have less developer/coding work thanks in advance submitted by /u/HunnyBunnyBandit [link] [comments]
I passed my sysops admin exam with 890 score and I would say really exam is somewhat intense as 90% will be scenario based questions with more than 2 services being referred in question . There will be a couple of surprise questions but just understand the options and you’ll find correct one. I took Stephan’s course and then TD and ND practice exams . Td has best explanations although lengthy but ND practice test actually matches level of real exam. Took me me around 3 weeks in total to prepare and appear for final exam. Just adding a few questions I faced in exam so anyone taking exam can understand exam level- 1) company is using AWS organization, member accounts want to see the billing in their accounts so they can keep track of spending but they are unable to view it in their accounts. What’s the reason 2) cloud front is using alb as origin. But after a week sysops admin finds that requests are still being served by alb . What are 2 possible reasons 3) application is running in 2 private subnets with alb in 2 public subnets in 2 az. 1 igw is attached and 1 nat gw is attached to vpc. What could be point of failure in case of az outage 4) what to implement for disaster recovery of aurora in another region. 5) Company is launching an application in Europe. Company would like only users from France to access first version of app. Company plans to add other countries in next versions. Which r53 policy should be used(answer to this is not geolocation) 6) want to get cpu utilization of my ec2 and on prem machines on my cw dashboard . what is most secure way of providing access for ec2 and on prem hardware so they can publish logs to cw dashboard. submitted by /u/Weeeb111 [link] [comments]
The badge of aws educate is actually worth it. Because, officially providing from aws. And it gives a credibility for the resume? submitted by /u/PremKumarRK [link] [comments]
Hi happy to share i passed my AWS SAA exam w/ a 1 week full-time preparation. Any idea how hard is SAP to SAA, im planning to take it as my next goal. Shoutout to Stephane Maarek for his awesome udemy course and practice exam as only my resource throughout this journey. Cheers! submitted by /u/pmventura [link] [comments]
I am so fresh into the AWS cert world and have been doing research on where to begin, etc. I decided to obviously start with the Cloud Practitioner cert and saw many paid resources in terms of exam prep guides / practice exams. I saw a few mentions of the FCC video guide and am wondering if anyone used just this video and maybe another resource for practice exams and was able to pass the exam and get certified? My concern isn't as much about paying for resources as it is with just being overwhelmed with which resource to go for and put my time into. This video is 14 hours and seems comprehensive. The comments on the video also say that they passed the exam just by following the video but I think I trust Reddit more (lol). My current plan was to watch this entire video and take notes. Then take practice exams either on ExamPro or TD (or anything you all recommend) and then take the exam in a couple weeks. I just don't want to spend 14 hours watching this video and it ends up not being enough prep for the exam and then I have to look into other courses and end up over studying. Any advice or validation for this course would be appreciated! submitted by /u/AFriendlyInternetGuy [link] [comments]
Amazon RDS (Relational Database Service) Performance Insights now collects the query execution plans of the resource-intensive SQL queries in Amazon RDS for SQL Server, and stores them over time. It helps you identify if a change in the query execution plan is the cause of performance degradation or stalled query.
Today, myApplications in the AWS Management Console has expanded the ability to create and manage your applications to 9 additional AWS Regions: Africa (Cape Town), Middle East (UAE), Asia Pacific (Hong Kong), Asia Pacific (Hyderabad), Asia Pacific (Melbourne), Europe (Milan), Israel (Tel Aviv), Europe (Spain), and Europe (Zurich).
Amazon CloudWatch RUM, which enables customers to monitor their web applications by collecting client side performance and error data in real time, is generally available in the following 5 AWS Regions starting today: Asia Pacific (Hyderabad), Asia Pacific (Melbourne), Europe (Spain), Europe (Zurich), and Middle East (UAE).
Possible 75% off AWS Certification Exam for AWS Summit attendees. Source : Noticed the card being held by Viktoria Semaan from AWS on her LinkedIn Post. Go to her profile at https://www.linkedin.com/in/semaan/ and find the "5 Reasons Why You'll Regret Missing Your Local AWS Summit" post and it has a picture of her holding a card saying "75% off". If I include the exact post url - reddit just pulls in the picture which I find a bit weird. Previous Summits have made similar offers / leaked some of the codes / signup pages (please do NOT post the codes etc online - it just ruins such offers for others) While the actual summit is free to register and go to - its only in select cities and there is no formal notice of how many vouchers etc I am gutted to not make the London summit myself tomorrow (24-Apr) due to work commitments - hope someone else going can confirm this offer / details (again - dont leak the code etc) submitted by /u/madrasi2021 [link] [comments]
As with all my previous certifications: theoretical lessons by Adrian Cantrill and practical tests by TutorialDojo. Both resources are brilliant! Now I am certified in the following areas: AWS Certified Advanced Networking Specialist, AWS Certified DevOps Professional, AWS Certified Solutions Architect Associate, AWS Certified Security Specialist, AWS Certified SysOps Administrator Associate submitted by /u/nitalaut [link] [comments]
Amazon RDS for Oracle now supports external authentication of database users using Kerberos and Microsoft Active Directory in additional regions. This feature provides the benefits of single sign-on and centralized authentication of Oracle Database users. Keeping all of your user credentials in the same Active Directory will save you time and effort as you will now have a centralized place for storing and managing them for multiple DB instances.
Amazon Elastic Container Service (Amazon ECS) now lets you add automated safeguards for rolling updates of Amazon ECS services in the AWS GovCloud (US) Regions. You can now monitor and automatically react to changes during an Amazon ECS rolling update by using Amazon CloudWatch alarms. This allows you to more easily automate discovery and remediation for failed deployments and minimize the impact of a bad change.
Today, AWS IoT Core for LoRaWAN announced the expansion of the public network support in the Spain region. With this expansion, Internet of Things (IoT) customers that offer LoRaWAN-based systems and solutions in Spain can seamlessly connect their LoRaWAN-powered devices to AWS over a public network infrastructure. This public infrastructure is provided as a service and supported by Everynet - a global LoRaWAN network operator offering networks in the United States, United Kingdom, and Spain. Thanks to the publicly available network infrastructure, customers in Spain can realize improved savings in time and costs associated with managing a private network infrastructure for LoRaWAN-based solutions.
Just passed my AWS SAA C03 exam today after a hard grind of about a month of studying. I am a cybersecurity analyst who is interested of applying security solutions on the cloud, so I am planning to take the AWS security specialty next. For those who have taken both, which one was easier to prepare for and how would you compare the two exams? Is the security exam as scenario-based as the SAA? or is it more so a definitions test like the CCP? submitted by /u/Internal_Piece6619 [link] [comments]
I've heard that Tutorials Dojo offers 5 practice exams for the SAA-CO3 (Solutions Architect Associate - Certified CO3) certification. However, when I checked their portal, I found 7 sets available. Can anyone confirm if the last two sets are repetitions of the previous ones? I want to make sure I'm utilizing the resources effectively. submitted by /u/mouli_chaithanya [link] [comments]
Amazon OpenSearch Service adds support for Hebrew and HanLP (Chinese NLP) language analyzer plugins. These are now available as optional plugins that you can associate with your Amazon OpenSearch Service clusters.
Amazon QuickSight now includes cross-sheet filters and controls. This enables authors to create and manage filters and controls across an entire analysis or dashboard.
Today, AWS AppFabric announces support for 1Password. Starting now, IT administrators and security analysts can use AppFabric to quickly integrate with 26 supported SaaS applications, aggregate enriched and normalized SaaS audit logs, and audit end-user access across their SaaS apps.
Finally I passed my CLF-C02 exam in my first attempt. I'm happy. there are some technical questions in the exam about AWS Cloud Adoption Framework, about Which Amazon service to be used for hosting a new Microsoft SQL server database on AWS, about Amazon services to inspect your AWS environment and making recommendations for lower expenditures and for good system perfommance. I was curious about my preparation for the exam but somehow I prepared from multiple resources like tutorial dojo and some conceptual videos from youtube but most reliable to me was a guide I got from itexamshub. Because after learning all the questions I was able to attempt most of the questions easily. Well I wish everyone will pass their exam with good marks. submitted by /u/Commercial-Suit-7693 [link] [comments]
Amazon CloudWatch Container Insights with Enhanced Observability for EKS now auto-discovers critical health metrics from your AWS accelerators Trainium and Inferentia, and AWS high performance network adapters (Elastic Fabric Adapters) as well as NVIDIA GPUs. You can visualize these out-of-the-box metrics in curated Container Insights dashboards to help monitor your accelerated infrastructure and optimize your AI workloads for operational excellence.
Today, we're excited to announce the availability of a new capability of Amazon Q to analyze issues for complexity and propose splitting the work into separate tasks.
AWS Transfer Family customers can now use SFTP connectors to list files stored in remote SFTP servers, enabling visibility into the contents of directories in remote SFTP file systems and transfer files when file names are not known in advance.
Hello, with the precious inputs from this group and carving out path, I have achieved my first ever AWS certification(796) after studying 8 weeks with being full time job. Studying thru ACloudGuru ( provisioned via employer) was like signing up for failure. Sorry AcloudGuru but you barely just touched upon topics. Thanks to Stephane Mareek and tutorial dojo for the preparation. Also thanks to people who posted questions about snapmirror, nitro,sagemaker etc. I did see those questions in exam and was able to navigate thru quickly. I saw very weird question about ACM. You dont want to use cloudfront default domain name and want to use your own domain name. Which cert will be cheapest? Options- Private cert in east Public cert in east Private cert in west Public cert in west I was blank at this question. Any insights are welcome. Rest - lot of questions on fargate, container , cost management console, tagging, gateway endpoint, vpc, storage choice, s3 etc…. submitted by /u/Chilli_green [link] [comments]
Amazon Titan Image Generator's new watermark detection feature is now generally available in Amazon Bedrock. All Amazon Titan-generated images contain an invisible watermark, by default. The watermark detection mechanism allows you to identify images generated by Amazon Titan Image Generator, a foundation model that allows users to create realistic, studio-quality images in large volumes and at low cost, using natural language prompts.
You can now access Meta’s Llama 3 models, Llama 3 8B and Llama 3 70B, in Amazon Bedrock. Meta Llama 3 is designed for you to build, experiment, and responsibly scale your generative artificial intelligence applications. You can now use these two new Llama 3 models in Amazon Bedrock enabling you to easily experiment with and evaluate even more top foundation models for your use case.
Agents for Amazon Bedrock enable generative AI applications to automate multi-step tasks across company systems and data sources. Agents removes the undifferentiated lifting of orchestration, infrastructure hosting and management, and we’re making building Agents easier than ever.
Model Evaluation on Amazon Bedrock allows you to evaluate, compare, and select the best foundation models for your use case. Amazon Bedrock offers a choice of automatic evaluation and human evaluation. You can use automatic evaluation with predefined algorithms for metrics such as accuracy, robustness, and toxicity. Additionally, for those metrics or subjective and custom metrics, such as friendliness, style, and alignment to brand voice, you can set up a human evaluation workflow with a few clicks. Human evaluation workflows can leverage your own employees or an AWS-managed team as reviewers. Model evaluation provides built-in curated datasets or you can bring your own datasets.
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