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What are the corresponding Azure and Google Cloud services for each of the AWS services?
What are unique distinctions and similarities between AWS, Azure and Google Cloud services? For each AWS service, what is the equivalent Azure and Google Cloud service? For each Azure service, what is the corresponding Google Service? AWS Services vs Azure vs Google Services? Side by side comparison between AWS, Google Cloud and Azure Service?
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Category: Marketplace
Easy-to-deploy and automatically configured third-party applications, including single virtual machine or multiple virtual machine solutions.
References:
[AWS]:AWS Marketplace
[Azure]:Azure Marketplace
[Google]:Google Cloud Marketplace
Tags: #AWSMarketplace, #AzureMarketPlace, #GoogleMarketplace
Differences: They are both digital catalog with thousands of software listings from independent software vendors that make it easy to find, test, buy, and deploy software that runs on their respective cloud platform.
2
Category: AI and machine learning
A cloud service to train, deploy, automate, and manage machine learning models.
References:
[AWS]:AWS SageMaker(build, train and deploy machine learning models), AWS DeepComposer (ML enabled musical keyboard), Amazon Fraud Detector (Detect more online fraud faster), Amazon CodeGuru (Automate code reviews and identify expensive lines of code), Contact Lens for Amazon Connect (Contact center analytics powered by ML), Amazon Kendra (Reinvent enterprise search with ML), Amazon Augmented AI (Easily implement human review of ML predictions), Amazon SageMaker Studio (The first visual IDE for machine learning), Amazon SageMaker Notebooks (Quickly start and share ML notebooks), Amazon SageMaker Experiments (Organize, track, and evaluate ML experiments), Amazon SageMaker Debugger (Analyze and debug ML models in real time), Amazon SageMaker Autopilot (Automatically create high quality ML models), Amazon SageMaker Model Monitor (Continuously monitor ML models)
[Azure]:Azure Machine Learning
[Google]:Google Cloud TensorFlow
Tags: #AI, #CloudAI, #SageMaker, #AzureMachineLearning, #TensorFlow
Differences: According to the StackShare community, Azure Machine Learning has a broader approval, being mentioned in 12 company stacks & 8 developers stacks; compared to Amazon Machine Learning, which is listed in 8 company stacks and 9 developer stacks.
3
Category: AI and machine learning
Build and connect intelligent bots that interact with your users using text/SMS, Skype, Teams, Slack, Office 365 mail, Twitter, and other popular services.
References:
[AWS]:Alexa Skills Kit (enables a developer to build skills, also called conversational applications, on the Amazon Alexa artificial intelligence assistant.)
[Azure]:Microsoft Bot Framework (building enterprise-grade conversational AI experiences.)
[Google]:Google Assistant Actions ( developer platform that lets you create software to extend the functionality of the Google Assistant, Google’s virtual personal assistant,)
Tags: #AlexaSkillsKit, #MicrosoftBotFramework, #GoogleAssistant
Differences: One major advantage Google gets over Alexa is that Google Assistant is available to almost all Android devices.
4
Category: AI and machine learning
Description:API capable of converting speech to text, understanding intent, and converting text back to speech for natural responsiveness.
References:
[AWS]:Amazon Lex (building conversational interfaces into any application using voice and text.)
[Azure]:Azure Speech Services(unification of speech-to-text, text-to-speech, and speech translation into a single Azure subscription)
[Google]:Google APi.ai, AI Hub (Hosted repo of plug-and-play AI component), AI building blocks(for developers to add sight, language, conversation, and structured data to their applications.), AI Platform(code-based data science development environment, lets ML developers and data scientists quickly take projects from ideation to deployment.), DialogFlow (Google-owned developer of human–computer interaction technologies based on natural language conversations. ), TensorFlow(Open Source Machine Learning platform)
Tags: #AmazonLex, #CogintiveServices, #AzureSpeech, #Api.ai, #DialogFlow, #Tensorflow
Differences: api.ai provides us with such a platform which is easy to learn and comprehensive to develop conversation actions. It is a good example of the simplistic approach to solving complex man to machine communication problem using natural language processing in proximity to machine learning. Api.ai supports context based conversations now, which reduces the overhead of handling user context in session parameters. On the other hand in Lex this has to be handled in session. Also, api.ai can be used for both voice and text based conversations (assistant actions can be easily created using api.ai).
5
Category: AI and machine learning
Description:Computer Vision: Extract information from images to categorize and process visual data.
References:
[AWS]:Amazon Rekognition (based on the same proven, highly scalable, deep learning technology developed by Amazon’s computer vision scientists to analyze billions of images and videos daily. It requires no machine learning expertise to use.)
[Azure]:Cognitive Services(bring AI within reach of every developer—without requiring machine-learning expertise.)
[Google]:Google Vision (offers powerful pre-trained machine learning models through REST and RPC APIs.)
Tags: AmazonRekognition, #GoogleVision, #AzureSpeech
Differences: For now, only Google Cloud Vision supports batch processing. Videos are not natively supported by Google Cloud Vision or Amazon Rekognition. The Object Detection functionality of Google Cloud Vision and Amazon Rekognition is almost identical, both syntactically and semantically.
Differences:
Google Cloud Vision and Amazon Rekognition offer a broad spectrum of solutions, some of which are comparable in terms of functional details, quality, performance, and costs.
6
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Category: Big data and analytics: Data warehouse
Description:Cloud-based Enterprise Data Warehouse (EDW) that uses Massively Parallel Processing (MPP) to quickly run complex queries across petabytes of data.
References:
[AWS]:AWS Redshift (scalable data warehouse that makes it simple and cost-effective to analyze all your data across your data warehouse and data lake.), Amazon Redshift Data Lake Export (Save query results in an open format),Amazon Redshift Federated Query(Run queries n line transactional data), Amazon Redshift RA3(Optimize costs with up to 3x better performance), AQUA: AQUA: Advanced Query Accelerator for Amazon Redshift (Power analytics with a new hardware-accelerated cache), UltraWarm for Amazon Elasticsearch Service(Store logs at ~1/10th the cost of existing storage tiers )
[Azure]:Azure Synapse formerly SQL Data Warehouse (limitless analytics service that brings together enterprise data warehousing and Big Data analytics.)
[Google]:BigQuery (RESTful web service that enables interactive analysis of massive datasets working in conjunction with Google Storage. )
Tags:#AWSRedshift, #GoogleBigQuery, #AzureSynapseAnalytics
Differences: Loading data, Managing resources (and hence pricing), Ecosystem. Ecosystem is where Redshift is clearly ahead of BigQuery. While BigQuery is an affordable, performant alternative to Redshift, they are considered to be more up and coming
7
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Category: Big data and analytics: Data warehouse
Description: Apache Spark-based analytics platform. Managed Hadoop service. Data orchestration, ETL, Analytics and visualization
References:
[AWS]:EMR, Data Pipeline, Kinesis Stream, Kinesis Firehose, Glue, QuickSight, Athena, CloudSearch
[Azure]:Azure Databricks, Data Catalog Cortana Intelligence, HDInsight, Power BI, Azure Datafactory, Azure Search, Azure Data Lake Anlytics, Stream Analytics, Azure Machine Learning
[Google]:Cloud DataProc, Machine Learning, Cloud Datalab
Tags:#EMR, #DataPipeline, #Kinesis, #Cortana, AzureDatafactory, #AzureDataAnlytics, #CloudDataProc, #MachineLearning, #CloudDatalab
Differences: All three providers offer similar building blocks; data processing, data orchestration, streaming analytics, machine learning and visualisations. AWS certainly has all the bases covered with a solid set of products that will meet most needs. Azure offers a comprehensive and impressive suite of managed analytical products. They support open source big data solutions alongside new serverless analytical products such as Data Lake. Google provide their own twist to cloud analytics with their range of services. With Dataproc and Dataflow, Google have a strong core to their proposition. Tensorflow has been getting a lot of attention recently and there will be many who will be keen to see Machine Learning come out of preview.
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Category: Virtual servers
Description:Virtual servers allow users to deploy, manage, and maintain OS and server software. Instance types provide combinations of CPU/RAM. Users pay for what they use with the flexibility to change sizes.
Batch: Run large-scale parallel and high-performance computing applications efficiently in the cloud.
References:
[AWS]:Elastic Compute Cloud (EC2), Amazon Bracket(Explore and experiment with quantum computing), Amazon Ec2 M6g Instances (Achieve up to 40% better price performance), Amazon Ec2 Inf1 instancs (Deliver cost-effective ML inference), AWS Graviton2 Processors (Optimize price performance for cloud workloads), AWS Batch, AWS AutoScaling, VMware Cloud on AWS, AWS Local Zones (Run low latency applications at the edge), AWS Wavelength (Deliver ultra-low latency applications for 5G devices), AWS Nitro Enclaves (Further protect highly sensitive data), AWS Outposts (Run AWS infrastructure and services on-premises)
[Azure]:Azure Virtual Machines, Azure Batch, Virtual Machine Scale Sets, Azure VMware by CloudSimple
[Google]:Compute Engine, Preemptible Virtual Machines, Managed instance groups (MIGs), Google Cloud VMware Solution by CloudSimple
Tags: #AWSEC2, #AWSBatch, #AWSAutoscaling, #AzureVirtualMachine, #AzureBatch, #VirtualMachineScaleSets, #AzureVMWare, #ComputeEngine, #MIGS, #VMWare
Differences: There is very little to choose between the 3 providers when it comes to virtual servers. Amazon has some impressive high end kit, on the face of it this sound like it would make AWS a clear winner. However, if your only option is to choose the biggest box available you will need to make sure you have very deep pockets, and perhaps your money may be better spent re-architecting your apps for horizontal scale.Azure’s remains very strong in the PaaS space and now has a IaaS that can genuinely compete with AWS
Google offers a simple and very capable set of services that are easy to understand. However, with availability in only 5 regions it does not have the coverage of the other players.
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Category: Containers and container orchestrators
Description: A container is a standard unit of software that packages up code and all its dependencies so the application runs quickly and reliably from one computing environment to another.
Container orchestration is all about managing the lifecycles of containers, especially in large, dynamic environments.
References:
[AWS]:EC2 Container Service (ECS), Fargate(Run containers without anaging servers or clusters), EC2 Container Registry(managed AWS Docker registry service that is secure, scalable, and reliable.), Elastic Container Service for Kubernetes (EKS: runs the Kubernetes management infrastructure across multiple AWS Availability Zones), App Mesh( application-level networking to make it easy for your services to communicate with each other across multiple types of compute infrastructure)
[Azure]:Azure Container Instances, Azure Container Registry, Azure Kubernetes Service (AKS), Service Fabric Mesh
[Google]:Google Container Engine, Container Registry, Kubernetes Engine
Tags:#ECS, #Fargate, #EKS, #AppMesh, #ContainerEngine, #ContainerRegistry, #AKS
Differences: Google Container Engine, AWS Container Services, and Azure Container Instances can be used to run docker containers. Google offers a simple and very capable set of services that are easy to understand. However, with availability in only 5 regions it does not have the coverage of the other players.
10
Category: Serverless
Description: Integrate systems and run backend processes in response to events or schedules without provisioning or managing servers.
References:
[AWS]:AWS Lambda
[Azure]:Azure Functions
[Google]:Google Cloud Functions
Tags:#AWSLAmbda, #AzureFunctions, #GoogleCloudFunctions
Differences: Both AWS Lambda and Microsoft Azure Functions and Google Cloud Functions offer dynamic, configurable triggers that you can use to invoke your functions on their platforms. AWS Lambda, Azure and Google Cloud Functions support Node.js, Python, and C#. The beauty of serverless development is that, with minor changes, the code you write for one service should be portable to another with little effort – simply modify some interfaces, handle any input/output transforms, and an AWS Lambda Node.JS function is indistinguishable from a Microsoft Azure Node.js Function. AWS Lambda provides further support for Python and Java, while Azure Functions provides support for F# and PHP. AWS Lambda is built from the AMI, which runs on Linux, while Microsoft Azure Functions run in a Windows environment. AWS Lambda uses the AWS Machine architecture to reduce the scope of containerization, letting you spin up and tear down individual pieces of functionality in your application at will.
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Category: Relational databases
Description: Managed relational database service where resiliency, scale, and maintenance are primarily handled by the platform.
References:
[AWS]:AWS RDS(MySQL and PostgreSQL-compatible relational database built for the cloud,), Aurora(MySQL and PostgreSQL-compatible relational database built for the cloud)
[Azure]:SQL Database, Azure Database for MySQL, Azure Database for PostgreSQL
[Google]:Cloud SQL
Tags: #AWSRDS, #AWSAUrora, #AzureSQlDatabase, #AzureDatabaseforMySQL, #GoogleCloudSQL
Differences: All three providers boast impressive relational database offering. RDS supports an impressive range of managed relational stores while Azure SQL Database is probably the most advanced managed relational database available today. Azure also has the best out-of-the-box support for cross-region geo-replication across its database offerings.
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Category: NoSQL, Document Databases
Description:A globally distributed, multi-model database that natively supports multiple data models: key-value, documents, graphs, and columnar.
References:
[AWS]:DynamoDB (key-value and document database that delivers single-digit millisecond performance at any scale.), SimpleDB ( a simple web services interface to create and store multiple data sets, query your data easily, and return the results.), Managed Cassandra Services(MCS)
[Azure]:Table Storage, DocumentDB, Azure Cosmos DB
[Google]:Cloud Datastore (handles sharding and replication in order to provide you with a highly available and consistent database. )
Tags:#AWSDynamoDB, #SimpleDB, #TableSTorage, #DocumentDB, AzureCosmosDB, #GoogleCloudDataStore
Differences:DynamoDB and Cloud Datastore are based on the document store database model and are therefore similar in nature to open-source solutions MongoDB and CouchDB. In other words, each database is fundamentally a key-value store. With more workloads moving to the cloud the need for NoSQL databases will become ever more important, and again all providers have a good range of options to satisfy most performance/cost requirements. Of all the NoSQL products on offer it’s hard not to be impressed by DocumentDB; Azure also has the best out-of-the-box support for cross-region geo-replication across its database offerings.
13
Category:Caching
Description:An in-memory–based, distributed caching service that provides a high-performance store typically used to offload non transactional work from a database.
References:
[AWS]:AWS ElastiCache (works as an in-memory data store and cache to support the most demanding applications requiring sub-millisecond response times.)
[Azure]:Azure Cache for Redis (based on the popular software Redis. It is typically used as a cache to improve the performance and scalability of systems that rely heavily on backend data-stores.)
[Google]:Memcache (In-memory key-value store, originally intended for caching)
Tags:#Redis, #Memcached
<Differences: They all support horizontal scaling via sharding.They all improve the performance of web applications by allowing you to retrive information from fast, in-memory caches, instead of relying on slower disk-based databases.”, “Differences”: “ElastiCache supports Memcached and Redis. Memcached Cloud provides various data persistence options as well as remote backups for disaster recovery purposes. Redis offers persistence to disk, Memcache does not. This can be very helpful if you cache lots of data, since you remove the slowness around having a fully cold cache. Redis also offers several extra data structures that Memcache doesn’t— Lists, Sets, Sorted Sets, etc. Memcache only has Key/Value pairs. Memcache is multi-threaded. Redis is single-threaded and event driven. Redis is very fast, but it’ll never be multi-threaded. At hight scale, you can squeeze more connections and transactions out of Memcache. Memcache tends to be more memory efficient. This can make a big difference around the magnitude of 10s of millions or 100s of millions of keys. ElastiCache supports Memcached and Redis. Memcached Cloud provides various data persistence options as well as remote backups for disaster recovery purposes. Redis offers persistence to disk, Memcache does not. This can be very helpful if you cache lots of data, since you remove the slowness around having a fully cold cache. Redis also offers several extra data structures that Memcache doesn’t— Lists, Sets, Sorted Sets, etc. Memcache only has Key/Value pairs. Memcache is multi-threaded. Redis is single-threaded and event driven. Redis is very fast, but it’ll never be multi-threaded. At hight scale, you can squeeze more connections and transactions out of Memcache. Memcache tends to be more memory efficient. This can make a big difference around the magnitude of 10s of millions or 100s of millions of keys.
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Category: Security, identity, and access
Description:Authentication and authorization: Allows users to securely control access to services and resources while offering data security and protection. Create and manage users and groups, and use permissions to allow and deny access to resources.
References:
[AWS]:Identity and Access Management (IAM), AWS Organizations, Multi-Factor Authentication, AWS Directory Service, Cognito(provides solutions to control access to backend resources from your app), Amazon Detective (Investigate potential security issues), AWS IAM Access Analyzer(Easily analyze resource accessibility)
[Azure]:Azure Active Directory, Azure Subscription Management + Azure RBAC, Multi-Factor Authentication, Azure Active Directory Domain Services, Azure Active Directory B2C, Azure Policy, Management Groups
[Google]:Cloud Identity, Identity Platform, Cloud IAM, Policy Intelligence, Cloud Resource Manager, Cloud Identity-Aware Proxy, Context-aware accessManaged Service for Microsoft Active Directory, Security key enforcement, Titan Security Key
Tags: #IAM, #AWSIAM, #AzureIAM, #GoogleIAM, #Multi-factorAuthentication
Differences: One unique thing about AWS IAM is that accounts created in the organization (not through federation) can only be used within that organization. This contrasts with Google and Microsoft. On the good side, every organization is self-contained. On the bad side, users can end up with multiple sets of credentials they need to manage to access different organizations. The second unique element is that every user can have a non-interactive account by creating and using access keys, an interactive account by enabling console access, or both. (Side note: To use the CLI, you need to have access keys generated.)
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Category: Object Storage and Content delivery
Description:Object storage service, for use cases including cloud applications, content distribution, backup, archiving, disaster recovery, and big data analytics.
References:
[AWS]:Simple Storage Services (S3), Import/Export(used to move large amounts of data into and out of the Amazon Web Services public cloud using portable storage devices for transport.), Snowball( petabyte-scale data transport solution that uses devices designed to be secure to transfer large amounts of data into and out of the AWS Cloud), CloudFront( content delivery network (CDN) is massively scaled and globally distributed), Elastic Block Store (EBS: high performance block storage service), Elastic File System(shared, elastic file storage system that grows and shrinks as you add and remove files.), S3 Infrequent Access (IA: is for data that is accessed less frequently, but requires rapid access when needed. ), S3 Glacier( long-term storage of data that is infrequently accessed and for which retrieval latency times of 3 to 5 hours are acceptable.), AWS Backup( makes it easy to centralize and automate the back up of data across AWS services in the cloud as well as on-premises using the AWS Storage Gateway.), Storage Gateway(hybrid cloud storage service that gives you on-premises access to virtually unlimited cloud storage), AWS Import/Export Disk(accelerates moving large amounts of data into and out of AWS using portable storage devices for transport)
[Azure]:Azure Blob storage, File Storage, Data Lake Store, Azure Backup, Azure managed disks, Azure Files, Azure Storage cool tier, Azure Storage archive access tier, Azure Backup, StorSimple, Import/Export
[Google]:Cloud Storage, GlusterFS, CloudCDN
Tags:#S3, #AzureBlobStorage, #CloudStorage
Differences:Source: All providers have good object storage options and so storage alone is unlikely to be a deciding factor when choosing a cloud provider. The exception perhaps is for hybrid scenarios, in this case Azure and AWS clearly win. AWS and Google’s support for automatic versioning is a great feature that is currently missing from Azure; however Microsoft’s fully managed Data Lake Store offers an additional option that will appeal to organisations who are looking to run large scale analytical workloads. If you are prepared to wait 4 hours for your data and you have considerable amounts of the stuff then AWS Glacier storage might be a good option. If you use the common programming patterns for atomic updates and consistency, such as etags and the if-match family of headers, then you should be aware that AWS does not support them, though Google and Azure do. Azure also supports blob leasing, which can be used to provide a distributed lock.
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Category:Internet of things (IoT)
Description:A cloud gateway for managing bidirectional communication with billions of IoT devices, securely and at scale. Deploy cloud intelligence directly on IoT devices to run in on-premises scenarios.
References:
[AWS]:AWS IoT (Internet of Things), AWS Greengrass, Kinesis Firehose, Kinesis Streams, AWS IoT Things Graph
[Azure]:Azure IoT Hub, Azure IoT Edge, Event Hubs, Azure Digital Twins, Azure Sphere
[Google]:Google Cloud IoT Core, Firebase, Brillo, Weave, CLoud Pub/SUb, Stream Analysis, Big Query, Big Query Streaming API
Tags:#IoT, #InternetOfThings, #Firebase
Differences:AWS and Azure have a more coherent message with their products clearly integrated into their respective platforms, whereas Google Firebase feels like a distinctly separate product.
17
Category:Web Applications
Description:Managed hosting platform providing easy to use services for deploying and scaling web applications and services. API Gateway is a a turnkey solution for publishing APIs to external and internal consumers. Cloudfront is a global content delivery network that delivers audio, video, applications, images, and other files.
References:
[AWS]:Elastic Beanstalk (for deploying and scaling web applications and services developed with Java, .NET, PHP, Node.js, Python, Ruby, Go, and Docker on familiar servers such as Apache, Nginx, Passenger, and IIS), AWS Wavelength (for delivering ultra-low latency applications for 5G), API Gateway (makes it easy for developers to create, publish, maintain, monitor, and secure APIs at any scale.), CloudFront (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.),Global Accelerator ( improves the availability and performance of your applications with local or global users. It provides static IP addresses that act as a fixed entry point to your application endpoints in a single or multiple AWS Regions, such as your Application Load Balancers, Network Load Balancers or Amazon EC2 instances.)AWS AppSync (simplifies application development by letting you create a flexible API to securely access, manipulate, and combine data from one or more data sources: GraphQL service with real-time data synchronization and offline programming features. )
[Azure]:App Service, API Management, Azure Content Delivery Network, Azure Content Delivery Network
[Google]:App Engine, Cloud API, Cloud Enpoint, APIGee
Tags: #AWSElasticBeanstalk, #AzureAppService, #GoogleAppEngine, #CloudEnpoint, #CloudFront, #APIgee
Differences: With AWS Elastic Beanstalk, developers retain full control over the AWS resources powering their application. If developers decide they want to manage some (or all) of the elements of their infrastructure, they can do so seamlessly by using Elastic Beanstalk’s management capabilities. AWS Elastic Beanstalk integrates with more apps than Google App Engines (Datadog, Jenkins, Docker, Slack, Github, Eclipse, etc..). Google App Engine has more features than AWS Elastic BEanstalk (App Identity, Java runtime, Datastore, Blobstore, Images, Go Runtime, etc..). Developers describe Amazon API Gateway as “Create, publish, maintain, monitor, and secure APIs at any scale”. Amazon API Gateway handles all the tasks involved in accepting and processing up to hundreds of thousands of concurrent API calls, including traffic management, authorization and access control, monitoring, and API version management. On the other hand, Google Cloud Endpoints is detailed as “Develop, deploy and manage APIs on any Google Cloud backend”. An NGINX-based proxy and distributed architecture give unparalleled performance and scalability. Using an Open API Specification or one of our API frameworks, Cloud Endpoints gives you the tools you need for every phase of API development and provides insight with Google Cloud Monitoring, Cloud Trace, Google Cloud Logging and Cloud Trace.
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Category:Encryption
Description:Helps you protect and safeguard your data and meet your organizational security and compliance commitments.
References:
[AWS]:Key Management Service AWS KMS, CloudHSM
[Azure]:Key Vault
[Google]:Encryption By Default at Rest, Cloud KMS
Tags:#AWSKMS, #Encryption, #CloudHSM, #EncryptionAtRest, #CloudKMS
Differences: AWS KMS, is an ideal solution for organizations that want to manage encryption keys in conjunction with other AWS services. In contrast to AWS CloudHSM, AWS KMS provides a complete set of tools to manage encryption keys, develop applications and integrate with other AWS services. Google and Azure offer 4096 RSA. AWS and Google offer 256 bit AES. With AWs, you can bring your own key
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Category:Internet of things (IoT)
Description:A cloud gateway for managing bidirectional communication with billions of IoT devices, securely and at scale. Deploy cloud intelligence directly on IoT devices to run in on-premises scenarios.
References:
[AWS]:AWS IoT, AWS Greengrass, Kinesis Firehose ( captures and loads streaming data in storage and business intelligence (BI) tools to enable near real-time analytics in the AWS cloud), Kinesis Streams (for rapid and continuous data intake and aggregation.), AWS IoT Things Graph (makes it easy to visually connect different devices and web services to build IoT applications.)
[Azure]:Azure IoT Hub, Azure IoT Edge, Event Hubs, Azure Digital Twins, Azure Sphere
[Google]:Google Cloud IoT Core, Firebase, Brillo, Weave, CLoud Pub/SUb, Stream Analysis, Big Query, Big Query Streaming API
Tags:#IoT, #InternetOfThings, #Firebase
Differences:AWS and Azure have a more coherent message with their products clearly integrated into their respective platforms, whereas Google Firebase feels like a distinctly separate product.
20
Category:Object Storage and Content delivery
Description: Object storage service, for use cases including cloud applications, content distribution, backup, archiving, disaster recovery, and big data analytics.
References:
[AWS]:Simple Storage Services (S3), Import/Export Snowball, CloudFront, Elastic Block Store (EBS), Elastic File System, S3 Infrequent Access (IA), S3 Glacier, AWS Backup, Storage Gateway, AWS Import/Export Disk, Amazon S3 Access Points(Easily manage access for shared data)
[Azure]:Azure Blob storage, File Storage, Data Lake Store, Azure Backup, Azure managed disks, Azure Files, Azure Storage cool tier, Azure Storage archive access tier, Azure Backup, StorSimple, Import/Export
[Google]:Cloud Storage, GlusterFS, CloudCDN
Tags:#S3, #AzureBlobStorage, #CloudStorage
Differences:All providers have good object storage options and so storage alone is unlikely to be a deciding factor when choosing a cloud provider. The exception perhaps is for hybrid scenarios, in this case Azure and AWS clearly win. AWS and Google’s support for automatic versioning is a great feature that is currently missing from Azure; however Microsoft’s fully managed Data Lake Store offers an additional option that will appeal to organisations who are looking to run large scale analytical workloads. If you are prepared to wait 4 hours for your data and you have considerable amounts of the stuff then AWS Glacier storage might be a good option. If you use the common programming patterns for atomic updates and consistency, such as etags and the if-match family of headers, then you should be aware that AWS does not support them, though Google and Azure do. Azure also supports blob leasing, which can be used to provide a distributed lock.
21
Category: Backend process logic
Description: Cloud technology to build distributed applications using out-of-the-box connectors to reduce integration challenges. Connect apps, data and devices on-premises or in the cloud.
References:
[AWS]:AWS Step Functions ( lets you build visual workflows that enable fast translation of business requirements into technical requirements. You can build applications in a matter of minutes, and when needs change, you can swap or reorganize components without customizing any code.)
[Azure]:Logic Apps (cloud service that helps you schedule, automate, and orchestrate tasks, business processes, and workflows when you need to integrate apps, data, systems, and services across enterprises or organizations.)
[Google]:Dataflow ( fully managed service for executing Apache Beam pipelines within the Google Cloud Platform ecosystem.)
Tags:#AWSStepFunctions, #LogicApps, #Dataflow
Differences: AWS Step Functions makes it easy to coordinate the components of distributed applications and microservices using visual workflows. Building applications from individual components that each perform a discrete function lets you scale and change applications quickly. AWS Step Functions belongs to \”Cloud Task Management\” category of the tech stack, while Google Cloud Dataflow can be primarily classified under \”Real-time Data Processing\”. According to the StackShare community, Google Cloud Dataflow has a broader approval, being mentioned in 32 company stacks & 8 developers stacks; compared to AWS Step Functions, which is listed in 19 company stacks and 7 developer stacks.
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Category: Enterprise application services
Description:Fully integrated Cloud service providing communications, email, document management in the cloud and available on a wide variety of devices.
References:
[AWS]:Amazon WorkMail, Amazon WorkDocs, Amazon Kendra (Sync and Index)
[Azure]:Office 365
[Google]:G Suite
Tags: #AmazonWorkDocs, #Office365, #GoogleGSuite
Differences: G suite document processing applications like Google Docs are far behind Office 365 popular Word and Excel software, but G Suite User interface is intuite, simple and easy to navigate. Office 365 is too clunky. Get 20% off G-Suite Business Plan with Promo Code: PCQ49CJYK7EATNC
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Category: Networking
Description: Provides an isolated, private environment in the cloud. Users have control over their virtual networking environment, including selection of their own IP address range, creation of subnets, and configuration of route tables and network gateways.
References:
[AWS]:Virtual Private Cloud (VPC), Cloud virtual networking, Subnets, Elastic Network Interface (ENI), Route Tables, Network ACL, Secutity Groups, Internet Gateway, NAT Gateway, AWS VPN Gateway, AWS Route 53, AWS Direct Connect, AWS Network Load Balancer, VPN CloudHub, AWS Local Zones, AWS Transit Gateway network manager (Centrally manage global networks)
[Azure]:Virtual Network(provide services for building networks within Azure.),Subnets (network resources can be grouped by subnet for organisation and security.), Network Interface (Each virtual machine can be assigned one or more network interfaces (NICs)), Network Security Groups (NSG: contains a set of prioritised ACL rules that explicitly grant or deny access), Azure VPN Gateway ( allows connectivity to on-premise networks), Azure DNS, Traffic Manager (DNS based traffic routing solution.), ExpressRoute (provides connections up to 10 Gbps to Azure services over a dedicated fibre connection), Azure Load Balancer, Network Peering, Azure Stack (Azure Stack allows organisations to use Azure services running in private data centers.), Azure Load Balancer , Azure Log Analytics, Azure DNS,
[Google]:Cloud Virtual Network, Subnets, Network Interface, Protocol fowarding, Cloud VPN, Cloud DNS, Virtual Private Network, Cloud Interconnect, CDN interconnect, Cloud DNS, Stackdriver, Google Cloud Load Balancing,
Tags:#VPC, #Subnets, #ACL, #VPNGateway, #CloudVPN, #NetworkInterface, #ENI, #RouteTables, #NSG, #NetworkACL, #InternetGateway, #NatGateway, #ExpressRoute, #CloudInterConnect, #StackDriver
Differences: Subnets group related resources, however, unlike AWS and Azure, Google do not constrain the private IP address ranges of subnets to the address space of the parent network. Like Azure, Google has a built in internet gateway that can be specified from routing rules.
24
Category: Management
Description: A unified management console that simplifies building, deploying, and operating your cloud resources.
References:
[AWS]: AWS Management Console, Trusted Advisor, AWS Usage and Billing Report, AWS Application Discovery Service, Amazon EC2 Systems Manager, AWS Personal Health Dashboard, AWS Compute Optimizer (Identify optimal AWS Compute resources)
[Azure]:Azure portal, Azure Advisor, Azure Billing API, Azure Migrate, Azure Monitor, Azure Resource Health
[Google]:Google CLoud Platform, Cost Management, Security Command Center, StackDriver
Tags: #AWSConsole, #AzurePortal, #GoogleCloudConsole, #TrustedAdvisor, #AzureMonitor, #SecurityCommandCenter
Differences: AWS Console categorizes its Infrastructure as a Service offerings into Compute, Storage and Content Delivery Network (CDN), Database, and Networking to help businesses and individuals grow. Azure excels in the Hybrid Cloud space allowing companies to integrate onsite servers with cloud offerings. Google has a strong offering in containers, since Google developed the Kubernetes standard that AWS and Azure now offer. GCP specializes in high compute offerings like Big Data, analytics and machine learning. It also offers considerable scale and load balancing – Google knows data centers and fast response time.
25
Category: DevOps and application monitoring
Description: Comprehensive solution for collecting, analyzing, and acting on telemetry from your cloud and on-premises environments; Cloud services for collaborating on code development; Collection of tools for building, debugging, deploying, diagnosing, and managing multiplatform scalable apps and services; Fully managed build service that supports continuous integration and deployment.
References:
[AWS]:AWS CodePipeline(orchestrates workflow for continuous integration, continuous delivery, and continuous deployment), AWS CloudWatch (monitor your AWS resources and the applications you run on AWS in real time. ), AWS X-Ray (application performance management service that enables a developer to analyze and debug applications in aws), AWS CodeDeploy (automates code deployments to Elastic Compute Cloud (EC2) and on-premises servers. ), AWS CodeCommit ( source code storage and version-control service), AWS Developer Tools, AWS CodeBuild (continuous integration service that compiles source code, runs tests, and produces software packages that are ready to deploy. ), AWS Command Line Interface (unified tool to manage your AWS services), AWS OpsWorks (Chef-based), AWS CloudFormation ( provides a common language for you to describe and provision all the infrastructure resources in your cloud environment.), Amazon CodeGuru (for automated code reviews and application performance recommendations)
[Azure]:Azure Monitor, Azure DevOps, Azure Developer Tools, Azure CLI Azure PowerShell, Azure Automation, Azure Resource Manager , VM extensions , Azure Automation
[Google]:DevOps Solutions (Infrastructure as code, Configuration management, Secrets management, Serverless computing, Continuous delivery, Continuous integration , Stackdriver (combines metrics, logs, and metadata from all of your cloud accounts and projects into a single comprehensive view of your environment)
Tags: #CloudWatch, #StackDriver, #AzureMonitor, #AWSXray, #AWSCodeDeploy, #AzureDevOps, #GoogleDevopsSolutions
Differences: CodeCommit eliminates the need to operate your own source control system or worry about scaling its infrastructure. Azure DevOps provides unlimited private Git hosting, cloud build for continuous integration, agile planning, and release management for continuous delivery to the cloud and on-premises. Includes broad IDE support.
SageMaker | Azure Machine Learning Studio
A collaborative, drag-and-drop tool to build, test, and deploy predictive analytics solutions on your data.
Alexa Skills Kit | Microsoft Bot Framework
Build and connect intelligent bots that interact with your users using text/SMS, Skype, Teams, Slack, Office 365 mail, Twitter, and other popular services.
API capable of converting speech to text, understanding intent, and converting text back to speech for natural responsiveness.
Amazon Lex | Language Understanding (LUIS)
Allows your applications to understand user commands contextually.
Amazon Polly, Amazon Transcribe | Azure Speech Services
Enables both Speech to Text, and Text into Speech capabilities.
The Speech Services are the unification of speech-to-text, text-to-speech, and speech-translation into a single Azure subscription. It’s easy to speech enable your applications, tools, and devices with the Speech SDK, Speech Devices SDK, or REST APIs.
Amazon Polly is a Text-to-Speech (TTS) service that uses advanced deep learning technologies to synthesize speech that sounds like a human voice. With dozens of lifelike voices across a variety of languages, you can select the ideal voice and build speech-enabled applications that work in many different countries.
Amazon Transcribe is an automatic speech recognition (ASR) service that makes it easy for developers to add speech-to-text capability to their applications. Using the Amazon Transcribe API, you can analyze audio files stored in Amazon S3 and have the service return a text file of the transcribed speech.
Amazon Rekognition | Cognitive Services
Computer Vision: Extract information from images to categorize and process visual data.
Amazon Rekognition is a simple and easy to use API that can quickly analyze any image or video file stored in Amazon S3. Amazon Rekognition is always learning from new data, and we are continually adding new labels and facial recognition features to the service.
Face: Detect, identy, and analyze faces in photos.
Emotions: Recognize emotions in images.
Alexa Skill Set | Azure Virtual Assistant
The Virtual Assistant Template brings together a number of best practices we’ve identified through the building of conversational experiences and automates integration of components that we’ve found to be highly beneficial to Bot Framework developers.
Big data and analytics
Data warehouse
AWS Redshift | SQL Data Warehouse
Cloud-based Enterprise Data Warehouse (EDW) that uses Massively Parallel Processing (MPP) to quickly run complex queries across petabytes of data.
Big data processing EMR | Azure Databricks
Apache Spark-based analytics platform.
Managed Hadoop service. Deploy and manage Hadoop clusters in Azure.
Data orchestration / ETL
AWS Data Pipeline, AWS Glue | Data Factory
Processes and moves data between different compute and storage services, as well as on-premises data sources at specified intervals. Create, schedule, orchestrate, and manage data pipelines.
A fully managed service that serves as a system of registration and system of discovery for enterprise data sources
Analytics and visualization
AWS Kinesis Analytics | Stream Analytics
Data Lake Analytics | Data Lake Store
Storage and analysis platforms that create insights from large quantities of data, or data that originates from many sources.
Business intelligence tools that build visualizations, perform ad hoc analysis, and develop business insights from data.
Delivers full-text search and related search analytics and capabilities.
Amazon Athena | Azure Data Lake Analytics
Provides a serverless interactive query service that uses standard SQL for analyzing databases.
Compute
Virtual servers
Elastic Compute Cloud (EC2) | Azure Virtual Machines
Virtual servers allow users to deploy, manage, and maintain OS and server software. Instance types provide combinations of CPU/RAM. Users pay for what they use with the flexibility to change sizes.
Run large-scale parallel and high-performance computing applications efficiently in the cloud.
AWS Auto Scaling | Virtual Machine Scale Sets
Allows you to automatically change the number of VM instances. You set defined metric and thresholds that determine if the platform adds or removes instances.
VMware Cloud on AWS | Azure VMware by CloudSimple
Redeploy and extend your VMware-based enterprise workloads to Azure with Azure VMware Solution by CloudSimple. Keep using the VMware tools you already know to manage workloads on Azure without disrupting network, security, or data protection policies.
Containers and container orchestrators
EC2 Container Service (ECS), Fargate | Azure Container Instances
Azure Container Instances is the fastest and simplest way to run a container in Azure, without having to provision any virtual machines or adopt a higher-level orchestration service.
EC2 Container Registry | Azure Container Registry
Allows customers to store Docker formatted images. Used to create all types of container deployments on Azure.
Elastic Container Service for Kubernetes (EKS) | Azure Kubernetes Service (AKS)
Deploy orchestrated containerized applications with Kubernetes. Simplify monitoring and cluster management through auto upgrades and a built-in operations console.
App Mesh | Service Fabric Mesh
Fully managed service that enables developers to deploy microservices applications without managing virtual machines, storage, or networking.
AWS App Mesh is a service mesh that provides application-level networking to make it easy for your services to communicate with each other across multiple types of compute infrastructure. App Mesh standardizes how your services communicate, giving you end-to-end visibility and ensuring high-availability for your applications.
Serverless
Integrate systems and run backend processes in response to events or schedules without provisioning or managing servers.
AWS Lambda is an event-driven, serverless computing platform provided by Amazon as a part of the Amazon Web Services. It is a computing service that runs code in response to events and automatically manages the computing resources required by that code
Database
Relational database
AWS RDS | SQL Database Azure Database for MySQL Azure Database for PostgreSQL
Managed relational database service where resiliency, scale, and maintenance are primarily handled by the platform.
Amazon Relational Database Service is a distributed relational database service by Amazon Web Services. It is a web service running “in the cloud” designed to simplify the setup, operation, and scaling of a relational database for use in applications. Administration processes like patching the database software, backing up databases and enabling point-in-time recovery are managed automatically. Scaling storage and compute resources can be performed by a single API call as AWS does not offer an ssh connection to RDS instances.
NoSQL / Document
DynamoDB and SimpleDB | Azure Cosmos DB
A globally distributed, multi-model database that natively supports multiple data models: key-value, documents, graphs, and columnar.
Caching
AWS ElastiCache | Azure Cache for Redis
An in-memory–based, distributed caching service that provides a high-performance store typically used to offload non transactional work from a database.
Amazon ElastiCache is a fully managed in-memory data store and cache service by Amazon Web Services. The service improves the performance of web applications by retrieving information from managed in-memory caches, instead of relying entirely on slower disk-based databases. ElastiCache supports two open-source in-memory caching engines: Memcached and Redis.
Database migration
AWS Database Migration Service | Azure Database Migration Service
Migration of database schema and data from one database format to a specific database technology in the cloud.
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.
DevOps and application monitoring
AWS CloudWatch, AWS X-Ray | Azure Monitor
Comprehensive solution for collecting, analyzing, and acting on telemetry from your cloud and on-premises environments.
Amazon CloudWatch is a monitoring and observability service built for DevOps engineers, developers, site reliability engineers (SREs), and IT managers. CloudWatch provides you with data and actionable insights to monitor your applications, respond to system-wide performance changes, optimize resource utilization, and get a unified view of operational health. CloudWatch collects monitoring and operational data in the form of logs, metrics, and events, providing you with a unified view of AWS resources, applications, and services that run on AWS and on-premises servers.
AWS X-Ray is an application performance management service that enables a developer to analyze and debug applications in the Amazon Web Services (AWS) public cloud. A developer can use AWS X-Ray to visualize how a distributed application is performing during development or production, and across multiple AWS regions and accounts.
AWS CodeDeploy, AWS CodeCommit, AWS CodePipeline | Azure DevOps
A cloud service for collaborating on code development.
AWS CodeDeploy is a fully managed deployment service that automates software deployments to a variety of compute services such as Amazon EC2, AWS Fargate, AWS Lambda, and your on-premises servers. AWS CodeDeploy makes it easier for you to rapidly release new features, helps you avoid downtime during application deployment, and handles the complexity of updating your applications.
AWS CodePipeline is a fully managed continuous delivery service that helps you automate your release pipelines for fast and reliable application and infrastructure updates. CodePipeline automates the build, test, and deploy phases of your release process every time there is a code change, based on the release model you define.
AWS CodeCommit is a source code storage and version-control service for Amazon Web Services’ public cloud customers. CodeCommit was designed to help IT teams collaborate on software development, including continuous integration and application delivery.
AWS Developer Tools | Azure Developer Tools
Collection of tools for building, debugging, deploying, diagnosing, and managing multiplatform scalable apps and services.
The AWS Developer Tools are designed to help you build software like Amazon. They facilitate practices such as continuous delivery and infrastructure as code for serverless, containers, and Amazon EC2.
AWS CodeBuild | Azure DevOps
Fully managed build service that supports continuous integration and deployment.
AWS Command Line Interface | Azure CLI Azure PowerShell
Built on top of the native REST API across all cloud services, various programming language-specific wrappers provide easier ways to create solutions.
The AWS Command Line Interface (CLI) is a unified tool to manage your AWS services. With just one tool to download and configure, you can control multiple AWS services from the command line and automate them through scripts.
AWS OpsWorks (Chef-based) | Azure Automation
Configures and operates applications of all shapes and sizes, and provides templates to create and manage a collection of resources.
AWS OpsWorks is a configuration management service that provides managed instances of Chef and Puppet. Chef and Puppet are automation platforms that allow you to use code to automate the configurations of your servers.
AWS CloudFormation | Azure Resource Manager , VM extensions , Azure Automation
Provides a way for users to automate the manual, long-running, error-prone, and frequently repeated IT tasks.
AWS CloudFormation provides a common language for you to describe and provision all the infrastructure resources in your cloud environment. CloudFormation allows you to use a simple text file to model and provision, in an automated and secure manner, all the resources needed for your applications across all regions and accounts.
Networking
Area
Cloud virtual networking, Virtual Private Cloud (VPC) | Virtual Network
Provides an isolated, private environment in the cloud. Users have control over their virtual networking environment, including selection of their own IP address range, creation of subnets, and configuration of route tables and network gateways.
Cross-premises connectivity
AWS VPN Gateway | Azure VPN Gateway
Connects Azure virtual networks to other Azure virtual networks, or customer on-premises networks (Site To Site). Allows end users to connect to Azure services through VPN tunneling (Point To Site).
DNS management
AWS Route 53 | Azure DNS
Manage your DNS records using the same credentials and billing and support contract as your other Azure services
Route 53 | Traffic Manager
A service that hosts domain names, plus routes users to Internet applications, connects user requests to datacenters, manages traffic to apps, and improves app availability with automatic failover.
Dedicated network
AWS Direct Connect | ExpressRoute
Establishes a dedicated, private network connection from a location to the cloud provider (not over the Internet).
Load balancing
AWS Network Load Balancer | Azure Load Balancer
Azure Load Balancer load-balances traffic at layer 4 (TCP or UDP).
Application Load Balancer | Application Gateway
Application Gateway is a layer 7 load balancer. It supports SSL termination, cookie-based session affinity, and round robin for load-balancing traffic.
Internet of things (IoT)
AWS IoT | Azure IoT Hub
A cloud gateway for managing bidirectional communication with billions of IoT devices, securely and at scale.
AWS Greengrass | Azure IoT Edge
Deploy cloud intelligence directly on IoT devices to run in on-premises scenarios.
Kinesis Firehose, Kinesis Streams | Event Hubs
Services that allow the mass ingestion of small data inputs, typically from devices and sensors, to process and route the data.
AWS IoT Things Graph | Azure Digital Twins
Azure Digital Twins is an IoT service that helps you create comprehensive models of physical environments. Create spatial intelligence graphs to model the relationships and interactions between people, places, and devices. Query data from a physical space rather than disparate sensors.
Management
Trusted Advisor | Azure Advisor
Provides analysis of cloud resource configuration and security so subscribers can ensure they’re making use of best practices and optimum configurations.
AWS Usage and Billing Report | Azure Billing API
Services to help generate, monitor, forecast, and share billing data for resource usage by time, organization, or product resources.
AWS Management Console | Azure portal
A unified management console that simplifies building, deploying, and operating your cloud resources.
AWS Application Discovery Service | Azure Migrate
Assesses on-premises workloads for migration to Azure, performs performance-based sizing, and provides cost estimations.
Amazon EC2 Systems Manager | Azure Monitor
Comprehensive solution for collecting, analyzing, and acting on telemetry from your cloud and on-premises environments.
AWS Personal Health Dashboard | Azure Resource Health
Provides detailed information about the health of resources as well as recommended actions for maintaining resource health.
Security, identity, and access
Authentication and authorization
Identity and Access Management (IAM) | Azure Active Directory
Allows users to securely control access to services and resources while offering data security and protection. Create and manage users and groups, and use permissions to allow and deny access to resources.
Identity and Access Management (IAM) | Azure Role Based Access Control
Role-based access control (RBAC) helps you manage who has access to Azure resources, what they can do with those resources, and what areas they have access to.
AWS Organizations | Azure Subscription Management + Azure RBAC
Security policy and role management for working with multiple accounts.
Multi-Factor Authentication | Multi-Factor Authentication
Safeguard access to data and applications while meeting user demand for a simple sign-in process.
AWS Directory Service | Azure Active Directory Domain Services
Provides managed domain services such as domain join, group policy, LDAP, and Kerberos/NTLM authentication that are fully compatible with Windows Server Active Directory.
Cognito | Azure Active Directory B2C
A highly available, global, identity management service for consumer-facing applications that scales to hundreds of millions of identities.
AWS Organizations | Azure Policy
Azure Policy is a service in Azure that you use to create, assign, and manage policies. These policies enforce different rules and effects over your resources, so those resources stay compliant with your corporate standards and service level agreements.
AWS Organizations | Management Groups
Azure management groups provide a level of scope above subscriptions. You organize subscriptions into containers called “management groups” and apply your governance conditions to the management groups. All subscriptions within a management group automatically inherit the conditions applied to the management group. Management groups give you enterprise-grade management at a large scale, no matter what type of subscriptions you have.
Encryption
Server-side encryption with Amazon S3 Key Management Service | Azure Storage Service Encryption
Helps you protect and safeguard your data and meet your organizational security and compliance commitments.
Key Management Service AWS KMS, CloudHSM | Key Vault
Provides security solution and works with other services by providing a way to manage, create, and control encryption keys stored in hardware security modules (HSM).
Firewall
Web Application Firewall | Application Gateway – Web Application Firewall
A firewall that protects web applications from common web exploits.
Web Application Firewall | Azure Firewall
Provides inbound protection for non-HTTP/S protocols, outbound network-level protection for all ports and protocols, and application-level protection for outbound HTTP/S.
Security
Inspector | Security Center
An automated security assessment service that improves the security and compliance of applications. Automatically assess applications for vulnerabilities or deviations from best practices.
Certificate Manager | App Service Certificates available on the Portal
Service that allows customers to create, manage, and consume certificates seamlessly in the cloud.
GuardDuty | Azure Advanced Threat Protection
Detect and investigate advanced attacks on-premises and in the cloud.
AWS Artifact | Service Trust Portal
Provides access to audit reports, compliance guides, and trust documents from across cloud services.
AWS Shield | Azure DDos Protection Service
Provides cloud services with protection from distributed denial of services (DDoS) attacks.
Storage
Object storage
Simple Storage Services (S3) | Azure Blob storage
Object storage service, for use cases including cloud applications, content distribution, backup, archiving, disaster recovery, and big data analytics.
Virtual server disks
Elastic Block Store (EBS) | Azure managed disks
SSD storage optimized for I/O intensive read/write operations. For use as high-performance Azure virtual machine storage.
Shared files
Elastic File System | Azure Files
Provides a simple interface to create and configure file systems quickly, and share common files. Can be used with traditional protocols that access files over a network.
Archiving and backup
S3 Infrequent Access (IA) | Azure Storage cool tier
Cool storage is a lower-cost tier for storing data that is infrequently accessed and long-lived.
S3 Glacier | Azure Storage archive access tier
Archive storage has the lowest storage cost and higher data retrieval costs compared to hot and cool storage.
AWS Backup | Azure Backup
Back up and recover files and folders from the cloud, and provide offsite protection against data loss.
Hybrid storage
Storage Gateway | StorSimple
Integrates on-premises IT environments with cloud storage. Automates data management and storage, plus supports disaster recovery.
Bulk data transfer
AWS Import/Export Disk | Import/Export
A data transport solution that uses secure disks and appliances to transfer large amounts of data. Also offers data protection during transit.
AWS Import/Export Snowball, Snowball Edge, Snowmobile | Azure Data Box
Petabyte- to exabyte-scale data transport solution that uses secure data storage devices to transfer large amounts of data to and from Azure.
Web applications
Elastic Beanstalk | App Service
Managed hosting platform providing easy to use services for deploying and scaling web applications and services.
API Gateway | API Management
A turnkey solution for publishing APIs to external and internal consumers.
CloudFront | Azure Content Delivery Network
A global content delivery network that delivers audio, video, applications, images, and other files.
Global Accelerator | Azure Front Door
Easily join your distributed microservice architectures into a single global application using HTTP load balancing and path-based routing rules. Automate turning up new regions and scale-out with API-driven global actions, and independent fault-tolerance to your back end microservices in Azure—or anywhere.
Miscellaneous
Backend process logic
AWS Step Functions | Logic Apps
Cloud technology to build distributed applications using out-of-the-box connectors to reduce integration challenges. Connect apps, data and devices on-premises or in the cloud.
Enterprise application services
Amazon WorkMail, Amazon WorkDocs | Office 365
Fully integrated Cloud service providing communications, email, document management in the cloud and available on a wide variety of devices.
Gaming
GameLift, GameSparks | PlayFab
Managed services for hosting dedicated game servers.
Media transcoding
Elastic Transcoder | Media Services
Services that offer broadcast-quality video streaming services, including various transcoding technologies.
Workflow
Simple Workflow Service (SWF) | Logic Apps
Serverless technology for connecting apps, data and devices anywhere, whether on-premises or in the cloud for large ecosystems of SaaS and cloud-based connectors.
Hybrid
Outposts | Azure Stack
Azure Stack is a hybrid cloud platform that enables you to run Azure services in your company’s or service provider’s datacenter. As a developer, you can build apps on Azure Stack. You can then deploy them to either Azure Stack or Azure, or you can build truly hybrid apps that take advantage of connectivity between an Azure Stack cloud and Azure.
How does a business decide between Microsoft Azure or AWS?
Basically, it all comes down to what your organizational needs are and if there’s a particular area that’s especially important to your business (ex. serverless, or integration with Microsoft applications).
Some of the main things it comes down to is compute options, pricing, and purchasing options.
Here’s a brief comparison of the compute option features across cloud providers:
Here’s an example of a few instances’ costs (all are Linux OS):
Each provider offers a variety of options to lower costs from the listed On-Demand prices. These can fall under reservations, spot and preemptible instances and contracts.
Both AWS and Azure offer a way for customers to purchase compute capacity in advance in exchange for a discount: AWS Reserved Instances and Azure Reserved Virtual Machine Instances. There are a few interesting variations between the instances across the cloud providers which could affect which is more appealing to a business.
Another discounting mechanism is the idea of spot instances in AWS and low-priority VMs in Azure. These options allow users to purchase unused capacity for a steep discount.
With AWS and Azure, enterprise contracts are available. These are typically aimed at enterprise customers, and encourage large companies to commit to specific levels of usage and spend in exchange for an across-the-board discount – for example, AWS EDPs and Azure Enterprise Agreements.
You can read more about the differences between AWS and Azure to help decide which your business should use in this blog post
Source: AWS to Azure services comparison – Azure Architecture
Top 100 AWS Solutions Architect Associate Certification Exam Questions and Answers Dump SAA-C03
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What are the Top 100 AWS Solutions Architect Associate Certification Exam Questions and Answers Dump SAA-C03?
AWS Certified Solutions Architects are responsible for designing, deploying, and managing AWS cloud applications. The AWS Cloud Solutions Architect Associate exam validates an examinee’s ability to effectively demonstrate knowledge of how to design and deploy secure and robust applications on AWS technologies. The AWS Solutions Architect Associate training provides an overview of key AWS services, security, architecture, pricing, and support.
An Insightful Overview of SAA-C03 Exam Topics Encountered and Reflecting on My SAA-C03 Exam Journey: From Setback to Success
The AWS Certified Solutions Architect – Associate (SAA-C03) Examination is a required examination for the AWS Certified Solutions Architect – Professional level. Successful completion of this examination can lead to a salary raise or promotion for those in cloud roles. Below is the Top 100 AWS solutions architect associate exam prep facts and summaries questions and answers dump.
With average increases in salary of over 25% for certified individuals, you’re going to be in a much better position to secure your dream job or promotion if you earn your AWS Certified Solutions Architect Associate certification. You’ll also develop strong hands-on skills by doing the guided hands-on lab exercises in our course which will set you up for successfully performing in a solutions architect role.
AWS solutions architect associate SAA-C03 practice exam and cheat sheet 2023 pdf eBook Print Book
aws solutions architect associate SAA-C03 practice exam and flashcards 2023 pdf eBook Print Book
aws certified solutions architect pdf book 2023
aws solutions architect cheat sheet ebook 2023
The AWS Solutions Architect Associate is ideal for those performing in Solutions Architect roles and for anyone working at a technical level with AWS technologies. Earning the AWS Certified Solutions Architect Associate will build your credibility and confidence as it demonstrates that you have the cloud skills companies need to innovate for the future.
AWS Certified Solutions Architect – Associate average salary
The AWS Certified Solutions Architect – Associate average salary is $149,446/year
In this blog, we will help you prepare for the AWS Solution Architect Associate Certification Exam, give you some facts and summaries, provide AWS Solution Architect Associate Top Questions and Answers Dump
How long to study for the AWS Solutions Architect exam?
We recommend that you allocate at least 60 minutes of study time per day and you will then be able to complete the certification within 5 weeks (including taking the actual exam). Study times can vary based on your experience with AWS and how much time you have each day, with some students passing their exams much faster and others taking a little longer. Get our eBook here.
AWS Certified Solutions Architects are IT professionals who design cloud solutions with AWS services to meet given technical requirements. An AWS Solutions Architect Associate is expected to design and implement distributed systems on AWS that are high-performing, scalable, secure and cost optimized.
How hard is the AWS Certified Solutions Architect Associate exam?
The AWS Solutions Architect Associate exam is an associate-level exam that requires a solid understanding of the AWS platform and a broad range of AWS services. The AWS Certified Solutions Architect Associate exam questions are scenario-based questions and can be challenging. Despite this, the AWS Solutions Architect Associate is often earned by beginners to cloud computing.
The popular AWS Certified Solutions Architect Associate exam have its new version this August 2022.
AWS Certified Solutions Architect – Associate (SAA-C03) Exam Guide
The AWS Certified Solutions Architect – Associate (SAA-C03) exam is intended for individuals who perform in a solutions architect role.
The exam validates a candidate’s ability to use AWS technologies to design solutions based on the AWS Well-Architected Framework.
What is the format of the AWS Certified Solutions Architect Associate exam?
The SAA-C03 exam is a multiple choice examination that is 65 questions in length. You can take the exam in a testing center or using an online proctored exam from your home or office. You have 130 minutes to complete your exam and the passing mark is 720 points out of 100 points (72%). If English is not your first language you can request an accommodation when booking your exam that will qualify you for an additional 30 minutes exam extension.
The exam also validates a candidate’s ability to complete the following tasks:
• Design solutions that incorporate AWS services to meet current business requirements and future projected needs
• Design architectures that are secure, resilient, high-performing, and cost-optimized
• Review existing solutions and determine improvements
Unscored content
The exam includes 15 unscored questions that do not affect your score.
AWS collects information about candidate performance on these unscored questions to evaluate these questions for future use as scored questions. These unscored questions are not identified on the exam.
Target candidate description
The target candidate should have at least 1 year of hands-on experience designing cloud solutions that use AWS services
Your results for the exam are reported as a scaled score of 100–1,000. The minimum passing score is 720.
Your score shows how you performed on the exam as a whole and whether or not you passed. Scaled scoring models help equate scores across multiple exam forms that might have slightly different difficulty levels.
What is the passing score for the AWS Solutions Architect exam?
All AWS certification exam results are reported as a score from 100 to 1000. Your score shows how you performed on the examination as a whole and whether or not you passed. The passing score for the AWS Certified Solutions Architect Associate is 720 (72%).
Can I take the AWS Exam from Home?
Yes, you can now take all AWS Certification exams with online proctoring using Pearson Vue or PSI. Here’s a detailed guide on how to book your AWS exam.
Are there any prerequisites for taking the AWS Certified Solutions Architect exam?
There are no prerequisites for taking AWS exams. You do not need any programming knowledge or experience working with AWS. Everything you need to know is included in our courses. We do recommend that you have a basic understanding of fundamental computing concepts such as compute, storage, networking, and databases.
How much does the AWS Solution Architect Exam cost?
The AWS Solutions Architect Associate exam cost is $150 US.
Once you successfully pass your exam, you will be issued a 50% discount voucher that you can use towards your next AWS Exam.
For more detailed information, check out this blog article on AWS Certification Costs.
The Role of an AWS Certified Solutions Architect Associate
AWS Certified Solutions Architects are IT professionals who design cloud solutions with AWS services to meet given technical requirements. An AWS Solutions Architect Associate is expected to design and implement distributed systems on AWS that are high-performing, scalable, secure and cost optimized.
Content outline:
Domain 1: Design Secure Architectures 30%
Domain 2: Design Resilient Architectures 26%
Domain 3: Design High-Performing Architectures 24%
Domain 4: Design Cost-Optimized Architectures 20%
Domain 1: Design Secure Architectures
This exam domain is focused on securing your architectures on AWS and comprises 30% of the exam. Task statements include:
Task Statement 1: Design secure access to AWS resources.
Knowledge of:
• Access controls and management across multiple accounts
• AWS federated access and identity services (for example, AWS Identity and Access Management [IAM], AWS Single Sign-On [AWS SSO])
• AWS global infrastructure (for example, Availability Zones, AWS Regions)
• AWS security best practices (for example, the principle of least privilege)
• The AWS shared responsibility model
Skills in:
• Applying AWS security best practices to IAM users and root users (for example, multi-factor authentication [MFA])
• Designing a flexible authorization model that includes IAM users, groups, roles, and policies
• Designing a role-based access control strategy (for example, AWS Security Token Service [AWS STS], role switching, cross-account access)
• Designing a security strategy for multiple AWS accounts (for example, AWS Control Tower, service control policies [SCPs])
• Determining the appropriate use of resource policies for AWS services
• Determining when to federate a directory service with IAM roles
Task Statement 2: Design secure workloads and applications.
Knowledge of:
• Application configuration and credentials security
• AWS service endpoints
• Control ports, protocols, and network traffic on AWS
• Secure application access
• Security services with appropriate use cases (for example, Amazon Cognito, Amazon GuardDuty, Amazon Macie)
• Threat vectors external to AWS (for example, DDoS, SQL injection)
Skills in:
• Designing VPC architectures with security components (for example, security groups, route tables, network ACLs, NAT gateways)
• Determining network segmentation strategies (for example, using public subnets and private subnets)
• Integrating AWS services to secure applications (for example, AWS Shield, AWS WAF, AWS SSO, AWS Secrets Manager)
• Securing external network connections to and from the AWS Cloud (for example, VPN, AWS Direct Connect)
Task Statement 3: Determine appropriate data security controls.
Knowledge of:
• Data access and governance
• Data recovery
• Data retention and classification
• Encryption and appropriate key management
Skills in:
• Aligning AWS technologies to meet compliance requirements
• Encrypting data at rest (for example, AWS Key Management Service [AWS KMS])
• Encrypting data in transit (for example, AWS Certificate Manager [ACM] using TLS)
• Implementing access policies for encryption keys
• Implementing data backups and replications
• Implementing policies for data access, lifecycle, and protection
• Rotating encryption keys and renewing certificates
Domain 2: Design Resilient Architectures
This exam domain is focused on designing resilient architectures on AWS and comprises 26% of the exam. Task statements include:
Task Statement 1: Design scalable and loosely coupled architectures.
Knowledge of:
• API creation and management (for example, Amazon API Gateway, REST API)
• AWS managed services with appropriate use cases (for example, AWS Transfer Family, Amazon
Simple Queue Service [Amazon SQS], Secrets Manager)
• Caching strategies
• Design principles for microservices (for example, stateless workloads compared with stateful workloads)
• Event-driven architectures
• Horizontal scaling and vertical scaling
• How to appropriately use edge accelerators (for example, content delivery network [CDN])
• How to migrate applications into containers
• Load balancing concepts (for example, Application Load Balancer)
• Multi-tier architectures
• Queuing and messaging concepts (for example, publish/subscribe)
• Serverless technologies and patterns (for example, AWS Fargate, AWS Lambda)
• Storage types with associated characteristics (for example, object, file, block)
• The orchestration of containers (for example, Amazon Elastic Container Service [Amazon ECS],Amazon Elastic Kubernetes Service [Amazon EKS])
• When to use read replicas
• Workflow orchestration (for example, AWS Step Functions)
Skills in:
• Designing event-driven, microservice, and/or multi-tier architectures based on requirements
• Determining scaling strategies for components used in an architecture design
• Determining the AWS services required to achieve loose coupling based on requirements
• Determining when to use containers
• Determining when to use serverless technologies and patterns
• Recommending appropriate compute, storage, networking, and database technologies based on requirements
• Using purpose-built AWS services for workloads
Task Statement 2: Design highly available and/or fault-tolerant architectures.
Knowledge of:
• AWS global infrastructure (for example, Availability Zones, AWS Regions, Amazon Route 53)
• AWS managed services with appropriate use cases (for example, Amazon Comprehend, Amazon Polly)
• Basic networking concepts (for example, route tables)
• Disaster recovery (DR) strategies (for example, backup and restore, pilot light, warm standby,
active-active failover, recovery point objective [RPO], recovery time objective [RTO])
• Distributed design patterns
• Failover strategies
• Immutable infrastructure
• Load balancing concepts (for example, Application Load Balancer)
• Proxy concepts (for example, Amazon RDS Proxy)
• Service quotas and throttling (for example, how to configure the service quotas for a workload in a standby environment)
• Storage options and characteristics (for example, durability, replication)
• Workload visibility (for example, AWS X-Ray)
Skills in:
• Determining automation strategies to ensure infrastructure integrity
• Determining the AWS services required to provide a highly available and/or fault-tolerant architecture across AWS Regions or Availability Zones
• Identifying metrics based on business requirements to deliver a highly available solution
• Implementing designs to mitigate single points of failure
• Implementing strategies to ensure the durability and availability of data (for example, backups)
• Selecting an appropriate DR strategy to meet business requirements
• Using AWS services that improve the reliability of legacy applications and applications not built for the cloud (for example, when application changes are not possible)
• Using purpose-built AWS services for workloads
Domain 3: Design High-Performing Architectures
This exam domain is focused on designing high-performing architectures on AWS and comprises 24% of the exam. Task statements include:
Task Statement 1: Determine high-performing and/or scalable storage solutions.
Knowledge of:
• Hybrid storage solutions to meet business requirements
• Storage services with appropriate use cases (for example, Amazon S3, Amazon Elastic File System [Amazon EFS], Amazon Elastic Block Store [Amazon EBS])
• Storage types with associated characteristics (for example, object, file, block)
Skills in:
• Determining storage services and configurations that meet performance demands
• Determining storage services that can scale to accommodate future needs
Task Statement 2: Design high-performing and elastic compute solutions.
Knowledge of:
• AWS compute services with appropriate use cases (for example, AWS Batch, Amazon EMR, Fargate)
• Distributed computing concepts supported by AWS global infrastructure and edge services
• Queuing and messaging concepts (for example, publish/subscribe)
• Scalability capabilities with appropriate use cases (for example, Amazon EC2 Auto Scaling, AWS Auto Scaling)
• Serverless technologies and patterns (for example, Lambda, Fargate)
• The orchestration of containers (for example, Amazon ECS, Amazon EKS)
Skills in:
• Decoupling workloads so that components can scale independently
• Identifying metrics and conditions to perform scaling actions
• Selecting the appropriate compute options and features (for example, EC2 instance types) to meet business requirements
• Selecting the appropriate resource type and size (for example, the amount of Lambda memory) to meet business requirements
Task Statement 3: Determine high-performing database solutions.
Knowledge of:
• AWS global infrastructure (for example, Availability Zones, AWS Regions)
• Caching strategies and services (for example, Amazon ElastiCache)
• Data access patterns (for example, read-intensive compared with write-intensive)
• Database capacity planning (for example, capacity units, instance types, Provisioned IOPS)
• Database connections and proxies
• Database engines with appropriate use cases (for example, heterogeneous migrations, homogeneous migrations)
• Database replication (for example, read replicas)
• Database types and services (for example, serverless, relational compared with non-relational, in-memory)
Skills in:
• Configuring read replicas to meet business requirements
• Designing database architectures
• Determining an appropriate database engine (for example, MySQL compared with
PostgreSQL)
• Determining an appropriate database type (for example, Amazon Aurora, Amazon DynamoDB)
• Integrating caching to meet business requirements
Task Statement 4: Determine high-performing and/or scalable network architectures.
Knowledge of:
• Edge networking services with appropriate use cases (for example, Amazon CloudFront, AWS Global Accelerator)
• How to design network architecture (for example, subnet tiers, routing, IP addressing)
• Load balancing concepts (for example, Application Load Balancer)
• Network connection options (for example, AWS VPN, Direct Connect, AWS PrivateLink)
Skills in:
• Creating a network topology for various architectures (for example, global, hybrid, multi-tier)
• Determining network configurations that can scale to accommodate future needs
• Determining the appropriate placement of resources to meet business requirements
• Selecting the appropriate load balancing strategy
Task Statement 5: Determine high-performing data ingestion and transformation solutions.
Knowledge of:
• Data analytics and visualization services with appropriate use cases (for example, Amazon Athena, AWS Lake Formation, Amazon QuickSight)
• Data ingestion patterns (for example, frequency)
• Data transfer services with appropriate use cases (for example, AWS DataSync, AWS Storage Gateway)
• Data transformation services with appropriate use cases (for example, AWS Glue)
• Secure access to ingestion access points
• Sizes and speeds needed to meet business requirements
• Streaming data services with appropriate use cases (for example, Amazon Kinesis)
Skills in:
• Building and securing data lakes
• Designing data streaming architectures
• Designing data transfer solutions
• Implementing visualization strategies
• Selecting appropriate compute options for data processing (for example, Amazon EMR)
• Selecting appropriate configurations for ingestion
• Transforming data between formats (for example, .csv to .parquet)
Domain 4: Design Cost-Optimized Architectures
This exam domain is focused optimizing solutions for cost-effectiveness on AWS and comprises 20% of the exam. Task statements include:
Task Statement 1: Design cost-optimized storage solutions.
Knowledge of:
• Access options (for example, an S3 bucket with Requester Pays object storage)
• AWS cost management service features (for example, cost allocation tags, multi-account billing)
• AWS cost management tools with appropriate use cases (for example, AWS Cost Explorer, AWS Budgets, AWS Cost and Usage Report)
• AWS storage services with appropriate use cases (for example, Amazon FSx, Amazon EFS, Amazon S3, Amazon EBS)
• Backup strategies
• Block storage options (for example, hard disk drive [HDD] volume types, solid state drive [SSD] volume types)
• Data lifecycles
• Hybrid storage options (for example, DataSync, Transfer Family, Storage Gateway)
• Storage access patterns
• Storage tiering (for example, cold tiering for object storage)
• Storage types with associated characteristics (for example, object, file, block)
Skills in:
• Designing appropriate storage strategies (for example, batch uploads to Amazon S3 compared with individual uploads)
• Determining the correct storage size for a workload
• Determining the lowest cost method of transferring data for a workload to AWS storage
• Determining when storage auto scaling is required
• Managing S3 object lifecycles
• Selecting the appropriate backup and/or archival solution
• Selecting the appropriate service for data migration to storage services
• Selecting the appropriate storage tier
• Selecting the correct data lifecycle for storage
• Selecting the most cost-effective storage service for a workload
Task Statement 2: Design cost-optimized compute solutions.
Knowledge of:
• AWS cost management service features (for example, cost allocation tags, multi-account billing)
• AWS cost management tools with appropriate use cases (for example, Cost Explorer, AWS Budgets, AWS Cost and Usage Report)
• AWS global infrastructure (for example, Availability Zones, AWS Regions)
• AWS purchasing options (for example, Spot Instances, Reserved Instances, Savings Plans)
• Distributed compute strategies (for example, edge processing)
• Hybrid compute options (for example, AWS Outposts, AWS Snowball Edge)
• Instance types, families, and sizes (for example, memory optimized, compute optimized, virtualization)
• Optimization of compute utilization (for example, containers, serverless computing, microservices)
• Scaling strategies (for example, auto scaling, hibernation)
Skills in:
• Determining an appropriate load balancing strategy (for example, Application Load Balancer [Layer 7] compared with Network Load Balancer [Layer 4] compared with Gateway Load Balancer)
• Determining appropriate scaling methods and strategies for elastic workloads (for example, horizontal compared with vertical, EC2 hibernation)
• Determining cost-effective AWS compute services with appropriate use cases (for example, Lambda, Amazon EC2, Fargate)
• Determining the required availability for different classes of workloads (for example, production workloads, non-production workloads)
• Selecting the appropriate instance family for a workload
• Selecting the appropriate instance size for a workload
Task Statement 3: Design cost-optimized database solutions.
Knowledge of:
• AWS cost management service features (for example, cost allocation tags, multi-account billing)
• AWS cost management tools with appropriate use cases (for example, Cost Explorer, AWS Budgets, AWS Cost and Usage Report)
• Caching strategies
• Data retention policies
• Database capacity planning (for example, capacity units)
• Database connections and proxies
• Database engines with appropriate use cases (for example, heterogeneous migrations, homogeneous migrations)
• Database replication (for example, read replicas)
• Database types and services (for example, relational compared with non-relational, Aurora, DynamoDB)
Skills in:
• Designing appropriate backup and retention policies (for example, snapshot frequency)
• Determining an appropriate database engine (for example, MySQL compared with PostgreSQL)
• Determining cost-effective AWS database services with appropriate use cases (for example, DynamoDB compared with Amazon RDS, serverless)
• Determining cost-effective AWS database types (for example, time series format, columnar format)
• Migrating database schemas and data to different locations and/or different database engines
Task Statement 4: Design cost-optimized network architectures.
Knowledge of:
• AWS cost management service features (for example, cost allocation tags, multi-account billing)
• AWS cost management tools with appropriate use cases (for example, Cost Explorer, AWS Budgets, AWS Cost and Usage Report)
• Load balancing concepts (for example, Application Load Balancer)
• NAT gateways (for example, NAT instance costs compared with NAT gateway costs)
• Network connectivity (for example, private lines, dedicated lines, VPNs)
• Network routing, topology, and peering (for example, AWS Transit Gateway, VPC peering)
• Network services with appropriate use cases (for example, DNS)
Skills in:
• Configuring appropriate NAT gateway types for a network (for example, a single shared NAT
gateway compared with NAT gateways for each Availability Zone)
• Configuring appropriate network connections (for example, Direct Connect compared with VPN compared with internet)
• Configuring appropriate network routes to minimize network transfer costs (for example, Region to Region, Availability Zone to Availability Zone, private to public, Global Accelerator, VPC endpoints)
• Determining strategic needs for content delivery networks (CDNs) and edge caching
• Reviewing existing workloads for network optimizations
• Selecting an appropriate throttling strategy
• Selecting the appropriate bandwidth allocation for a network device (for example, a single VPN compared with multiple VPNs, Direct Connect speed)
Which key tools, technologies, and concepts might be covered on the exam?
The following is a non-exhaustive list of the tools and technologies that could appear on the exam.
This list is subject to change and is provided to help you understand the general scope of services, features, or technologies on the exam.
The general tools and technologies in this list appear in no particular order.
AWS services are grouped according to their primary functions. While some of these technologies will likely be covered more than others on the exam, the order and placement of them in this list is no indication of relative weight or importance:
• Compute
• Cost management
• Database
• Disaster recovery
• High performance
• Management and governance
• Microservices and component decoupling
• Migration and data transfer
• Networking, connectivity, and content delivery
• Resiliency
• Security
• Serverless and event-driven design principles
• Storage
AWS Services and Features
There are lots of new services and feature updates in scope for the new AWS Certified Solutions Architect Associate certification! Here’s a list of some of the new services that will be in scope for the new version of the exam:
Analytics:
• Amazon Athena
• AWS Data Exchange
• AWS Data Pipeline
• Amazon EMR
• AWS Glue
• Amazon Kinesis
• AWS Lake Formation
• Amazon Managed Streaming for Apache Kafka (Amazon MSK)
• Amazon OpenSearch Service (Amazon Elasticsearch Service)
• Amazon QuickSight
• Amazon Redshift
Application Integration:
• Amazon AppFlow
• AWS AppSync
• Amazon EventBridge (Amazon CloudWatch Events)
• Amazon MQ
• Amazon Simple Notification Service (Amazon SNS)
• Amazon Simple Queue Service (Amazon SQS)
• AWS Step Functions
AWS Cost Management:
• AWS Budgets
• AWS Cost and Usage Report
• AWS Cost Explorer
• Savings Plans
Compute:
• AWS Batch
• Amazon EC2
• Amazon EC2 Auto Scaling
• AWS Elastic Beanstalk
• AWS Outposts
• AWS Serverless Application Repository
• VMware Cloud on AWS
• AWS Wavelength
Containers:
• Amazon Elastic Container Registry (Amazon ECR)
• Amazon Elastic Container Service (Amazon ECS)
• Amazon ECS Anywhere
• Amazon Elastic Kubernetes Service (Amazon EKS)
• Amazon EKS Anywhere
• Amazon EKS Distro
Database:
• Amazon Aurora
• Amazon Aurora Serverless
• Amazon DocumentDB (with MongoDB compatibility)
• Amazon DynamoDB
• Amazon ElastiCache
• Amazon Keyspaces (for Apache Cassandra)
• Amazon Neptune
• Amazon Quantum Ledger Database (Amazon QLDB)
• Amazon RDS
• Amazon Redshift
• Amazon Timestream
Developer Tools:
• AWS X-Ray
Front-End Web and Mobile:
• AWS Amplify
• Amazon API Gateway
• AWS Device Farm
• Amazon Pinpoint
Machine Learning:
• Amazon Comprehend
• Amazon Forecast
• Amazon Fraud Detector
• Amazon Kendra
• Amazon Lex
• Amazon Polly
• Amazon Rekognition
• Amazon SageMaker
• Amazon Textract
• Amazon Transcribe
• Amazon Translate
Management and Governance:
• AWS Auto Scaling
• AWS CloudFormation
• AWS CloudTrail
• Amazon CloudWatch
• AWS Command Line Interface (AWS CLI)
• AWS Compute Optimizer
• AWS Config
• AWS Control Tower
• AWS License Manager
• Amazon Managed Grafana
• Amazon Managed Service for Prometheus
• AWS Management Console
• AWS Organizations
• AWS Personal Health Dashboard
• AWS Proton
• AWS Service Catalog
• AWS Systems Manager
• AWS Trusted Advisor
• AWS Well-Architected Tool
Media Services:
• Amazon Elastic Transcoder
• Amazon Kinesis Video Streams
Migration and Transfer:
• AWS Application Discovery Service
• AWS Application Migration Service (CloudEndure Migration)
• AWS Database Migration Service (AWS DMS)
• AWS DataSync
• AWS Migration Hub
• AWS Server Migration Service (AWS SMS)
• AWS Snow Family
• AWS Transfer Family
Networking and Content Delivery:
• Amazon CloudFront
• AWS Direct Connect
• Elastic Load Balancing (ELB)
• AWS Global Accelerator
• AWS PrivateLink
• Amazon Route 53
• AWS Transit Gateway
• Amazon VPC
• AWS VPN
Security, Identity, and Compliance:
• AWS Artifact
• AWS Audit Manager
• AWS Certificate Manager (ACM)
• AWS CloudHSM
• Amazon Cognito
• Amazon Detective
• AWS Directory Service
• AWS Firewall Manager
• Amazon GuardDuty
• AWS Identity and Access Management (IAM)
• Amazon Inspector
• AWS Key Management Service (AWS KMS)
• Amazon Macie
• AWS Network Firewall
• AWS Resource Access Manager (AWS RAM)
• AWS Secrets Manager
• AWS Security Hub
• AWS Shield
• AWS Single Sign-On
• AWS WAF
Serverless:
• AWS AppSync
• AWS Fargate
• AWS Lambda
Storage:
• AWS Backup
• Amazon Elastic Block Store (Amazon EBS)
• Amazon Elastic File System (Amazon EFS)
• Amazon FSx (for all types)
• Amazon S3
• Amazon S3 Glacier
• AWS Storage Gateway
Out-of-scope AWS services and features
The following is a non-exhaustive list of AWS services and features that are not covered on the exam.
These services and features do not represent every AWS offering that is excluded from the exam content.
Analytics:
• Amazon CloudSearch
Application Integration:
• Amazon Managed Workflows for Apache Airflow (Amazon MWAA)
AR and VR:
• Amazon Sumerian
Blockchain:
• Amazon Managed Blockchain
Compute:
• Amazon Lightsail
Database:
• Amazon RDS on VMware
Developer Tools:
• AWS Cloud9
• AWS Cloud Development Kit (AWS CDK)
• AWS CloudShell
• AWS CodeArtifact
• AWS CodeBuild
• AWS CodeCommit
• AWS CodeDeploy
• Amazon CodeGuru
• AWS CodeStar
• Amazon Corretto
• AWS Fault Injection Simulator (AWS FIS)
• AWS Tools and SDKs
Front-End Web and Mobile:
• Amazon Location Service
Game Tech:
• Amazon GameLift
• Amazon Lumberyard
Internet of Things:
• All services
Which new AWS services will be covered in the SAA-C03?
AWS Data Exchange,
AWS Data Pipeline,
AWS Lake Formation,
Amazon Managed Streaming for Apache Kafka,
Amazon AppFlow,
AWS Outposts,
VMware Cloud on AWS,
AWS Wavelength,
Amazon Neptune,
Amazon Quantum Ledger Database,
Amazon Timestream,
AWS Amplify,
Amazon Comprehend,
Amazon Forecast,
Amazon Fraud Detector,
Amazon Kendra,
AWS License Manager,
Amazon Managed Grafana,
Amazon Managed Service for Prometheus,
AWS Proton,
Amazon Elastic Transcoder,
Amazon Kinesis Video Streams,
AWS Application Discovery Service,
AWS WAF Serverless,
AWS AppSync,
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AWS solutions architect associate exam prep facts and summaries questions and answers dump – Solution Architecture Definition 1:
Solution architecture is a practice of defining and describing an architecture of a system delivered in context of a specific solution and as such it may encompass description of an entire system or only its specific parts. Definition of a solution architecture is typically led by a solution architect.
AWS solutions architect associate exam prep facts and summaries questions and answers dump – Solution Architecture Definition 2:
The AWS Certified Solutions Architect – Associate examination is intended for individuals who perform a solutions architect role and have one or more years of hands-on experience designing available, cost-efficient, fault-tolerant, and scalable distributed systems on AWS.
AWS solutions architect associate exam prep facts and summaries questions and answers dump – AWS Solution Architect Associate Exam Facts and Summaries (SAA-C03)
- Take an AWS Training Class
- Study AWS Whitepapers and FAQs: AWS Well-Architected webpage (various whitepapers linked)
- If you are running an application in a production environment and must add a new EBS volume with data from a snapshot, what could you do to avoid degraded performance during the volume’s first use?
Initialize the data by reading each storage block on the volume.
Volumes created from an EBS snapshot must be initialized. Initializing occurs the first time a storage block on the volume is read, and the performance impact can be impacted by up to 50%. You can avoid this impact in production environments by pre-warming the volume by reading all of the blocks. - If you are running a legacy application that has hard-coded static IP addresses and it is running on an EC2 instance; what is the best failover solution that allows you to keep the same IP address on a new instance?
Elastic IP addresses (EIPs) are designed to be attached/detached and moved from one EC2 instance to another. They are a great solution for keeping a static IP address and moving it to a new instance if the current instance fails. This will reduce or eliminate any downtime uses may experience. - Which feature of Intel processors help to encrypt data without significant impact on performance?
AES-NI - You can mount to EFS from which two of the following?
- On-prem servers running Linux
- EC2 instances running Linux
EFS is not compatible with Windows operating systems.
When a file(s) is encrypted and the stored data is not in transit it’s known as encryption at rest. What is an example of encryption at rest?
When would vertical scaling be necessary? When an application is built entirely into one source code, otherwise known as a monolithic application.
Fault-Tolerance allows for continuous operation throughout a failure, which can lead to a low Recovery Time Objective. RPO vs RTO
- High-Availability means automating tasks so that an instance will quickly recover, which can lead to a low Recovery Time Objective. RPO vs. RTO
- Frequent backups reduce the time between the last backup and recovery point, otherwise known as the Recovery Point Objective. RPO vs. RTO
- Which represents the difference between Fault-Tolerance and High-Availability? High-Availability means the system will quickly recover from a failure event, and Fault-Tolerance means the system will maintain operations during a failure.
- From a security perspective, what is a principal? An anonymous user falls under the definition of a principal. A principal can be an anonymous user acting on a system.
An authenticated user falls under the definition of a principal. A principal can be an authenticated user acting on a system.
- What are two types of session data saving for an Application Session State? Stateless and Stateful
23. It is the customer’s responsibility to patch the operating system on an EC2 instance.
24. In designing an environment, what four main points should a Solutions Architect keep in mind? Cost-efficient, secure, application session state, undifferentiated heavy lifting: These four main points should be the framework when designing an environment.
25. In the context of disaster recovery, what does RPO stand for? RPO is the abbreviation for Recovery Point Objective.
26. What are the benefits of horizontal scaling?
Vertical scaling can be costly while horizontal scaling is cheaper.
Horizontal scaling suffers from none of the size limitations of vertical scaling.
Having horizontal scaling means you can easily route traffic to another instance of a server.
Top
Reference: AWS Solution Architect Associate Exam Prep
Top 100 AWS solutions architect associate exam prep facts and summaries questions and answers dump – SAA-C03
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Top AWS solutions architect associate exam prep facts and summaries questions and answers dump – Quizzes
A company is developing a highly available web application using stateless web servers. Which services are suitable for storing session state data? (Select TWO.)
- A. CloudWatch
- B. DynamoDB
- C. Elastic Load Balancing
- D. ElastiCache
- E. Storage Gateway
Q1: A Solutions Architect is designing a critical business application with a relational database that runs on an EC2 instance. It requires a single EBS volume that can support up to 16,000 IOPS.
Which Amazon EBS volume type can meet the performance requirements of this application?
- A. EBS Provisioned IOPS SSD
- B. EBS Throughput Optimized HDD
- C. EBS General Purpose SSD
- D. EBS Cold HDD
Q2: An application running on EC2 instances processes sensitive information stored on Amazon S3. The information is accessed over the Internet. The security team is concerned that the Internet connectivity to Amazon S3 is a security risk.
Which solution will resolve the security concern?
- A. Access the data through an Internet Gateway.
- B. Access the data through a VPN connection.
- C. Access the data through a NAT Gateway.
- D.Access the data through a VPC endpoint for Amazon S3
Q3: An organization is building an Amazon Redshift cluster in their shared services VPC. The cluster will host sensitive data.
How can the organization control which networks can access the cluster?
- A. Run the cluster in a different VPC and connect through VPC peering.
- B. Create a database user inside the Amazon Redshift cluster only for users on the network.
- C. Define a cluster security group for the cluster that allows access from the allowed networks.
- D. Only allow access to networks that connect with the shared services network via VPN.
Q4: A web application allows customers to upload orders to an S3 bucket. The resulting Amazon S3 events trigger a Lambda function that inserts a message to an SQS queue. A single EC2 instance reads messages from the queue, processes them, and stores them in an DynamoDB table partitioned by unique order ID. Next month traffic is expected to increase by a factor of 10 and a Solutions Architect is reviewing the architecture for possible scaling problems.
Which component is MOST likely to need re-architecting to be able to scale to accommodate the new traffic?
- A. Lambda function
- B. SQS queue
- C. EC2 instance
- D. DynamoDB table
Q5: An application requires a highly available relational database with an initial storage capacity of 8 TB. The database will grow by 8 GB every day. To support expected traffic, at least eight read replicas will be required to handle database reads.
Which option will meet these requirements?
- A. DynamoDB
- B. Amazon S3
- C. Amazon Aurora
- D. Amazon Redshift
Q6: How can you improve the performance of EFS?
- A. Use an instance-store backed EC2 instance.
- B. Provision more throughput than is required.
- C. Divide your files system into multiple smaller file systems.
- D. Provision higher IOPs for your EFS.
Q7:
If you are designing an application that requires fast (10 – 25Gbps), low-latency connections between EC2 instances, what EC2 feature should you use?
- A. Snapshots
- B. Instance store volumes
- C. Placement groups
- D. IOPS provisioned instances.
Q8: A Solution Architect is designing an online shopping application running in a VPC on EC2 instances behind an ELB Application Load Balancer. The instances run in an Auto Scaling group across multiple Availability Zones. The application tier must read and write data to a customer managed database cluster. There should be no access to the database from the Internet, but the cluster must be able to obtain software patches from the Internet.
Which VPC design meets these requirements?
- A. Public subnets for both the application tier and the database cluster
- B. Public subnets for the application tier, and private subnets for the database cluster
- C. Public subnets for the application tier and NAT Gateway, and private subnets for the database cluster
- D. Public subnets for the application tier, and private subnets for the database cluster and NAT Gateway
Q9: What command should you run on a running instance if you want to view its user data (that is used at launch)?
- A. curl http://254.169.254.169/latest/user-data
- B. curl http://localhost/latest/meta-data/bootstrap
- C. curl http://localhost/latest/user-data
- D. curl http://169.254.169.254/latest/user-data
Q10: A company is developing a highly available web application using stateless web servers. Which services are suitable for storing session state data? (Select TWO.)
- A. CloudWatch
- B. DynamoDB
- C. Elastic Load Balancing
- D. ElastiCache
- E. Storage Gateway
Q11: From a security perspective, what is a principal?
- A. An identity
- B. An anonymous user
- C. An authenticated user
- D. A resource
Q12: What are the characteristics of a tiered application?
- A. All three application layers are on the same instance
- B. The presentation tier is on an isolated instance than the logic layer
- C. None of the tiers can be cloned
- D. The logic layer is on an isolated instance than the data layer
- E. Additional machines can be added to help the application by implementing horizontal scaling
- F. Incapable of horizontal scaling
Q13: When using horizontal scaling, how can a server’s capacity closely match it’s rising demand?
A. By frequently purchasing additional instances and smaller resources
B. By purchasing more resources very far in advance
C. By purchasing more resources after demand has risen
D. It is not possible to predict demand
Q14: What is the concept behind AWS’ Well-Architected Framework?
A. It’s a set of best practice areas, principles, and concepts that can help you implement effective AWS solutions.
B. It’s a set of best practice areas, principles, and concepts that can help you implement effective solutions tailored to your specific business.
C. It’s a set of best practice areas, principles, and concepts that can help you implement effective solutions from another web host.
D. It’s a set of best practice areas, principles, and concepts that can help you implement effective E-Commerce solutions.
Question 127: Which options are examples of steps you take to protect your serverless application from attacks? (Select FOUR.)
A. Update your operating system with the latest patches.
B. Configure geoblocking on Amazon CloudFront in front of regional API endpoints.
C. Disable origin access identity on Amazon S3.
D. Disable CORS on your APIs.
E. Use resource policies to limit access to your APIs to users from a specified account.
F. Filter out specific traffic patterns with AWS WAF.
G. Parameterize queries so that your Lambda function expects a single input.
Question 128: Which options reflect best practices for automating your deployment pipeline with serverless applications? (Select TWO.)
A. Select one deployment framework and use it for all of your deployments for consistency.
B. Use different AWS accounts for each environment in your deployment pipeline.
C. Use AWS SAM to configure safe deployments and include pre- and post-traffic tests.
D. Create a specific AWS SAM template to match each environment to keep them distinct.
Question 129: Your application needs to connect to an Amazon RDS instance on the backend. What is the best recommendation to the developer whose function must read from and write to the Amazon RDS instance?
A. Use reserved concurrency to limit the number of concurrent functions that would try to write to the database
B. Use the database proxy feature to provide connection pooling for the functions
C. Initialize the number of connections you want outside of the handler
D. Use the database TTL setting to clean up connections
Question 130: A company runs a cron job on an Amazon EC2 instance on a predefined schedule. The cron job calls a bash script that encrypts a 2 KB file. A security engineer creates an AWS Key Management Service (AWS KMS) CMK with a key policy.
The key policy and the EC2 instance role have the necessary configuration for this job.
Which process should the bash script use to encrypt the file?
A) Use the aws kms encrypt command to encrypt the file by using the existing CMK.
B) Use the aws kms create-grant command to generate a grant for the existing CMK.
C) Use the aws kms encrypt command to generate a data key. Use the plaintext data key to encrypt the file.
D) Use the aws kms generate-data-key command to generate a data key. Use the encrypted data key to encrypt the file.
Question 131: A Security engineer must develop an AWS Identity and Access Management (IAM) strategy for a company’s organization in AWS Organizations. The company needs to give developers autonomy to develop and test their applications on AWS, but the company also needs to implement security guardrails to help protect itself. The company creates and distributes applications with different levels of data classification and types. The solution must maximize scalability.
Which combination of steps should the security engineer take to meet these requirements? (Choose three.)
A) Create an SCP to restrict access to highly privileged or unauthorized actions to specific AM principals. Assign the SCP to the appropriate AWS accounts.
B) Create an IAM permissions boundary to allow access to specific actions and IAM principals. Assign the IAM permissions boundary to all AM principals within the organization
C) Create a delegated IAM role that has capabilities to create other IAM roles. Use the delegated IAM role to provision IAM principals by following the principle of least privilege.
D) Create OUs based on data classification and type. Add the AWS accounts to the appropriate OU. Provide developers access to the AWS accounts based on business need.
E) Create IAM groups based on data classification and type. Add only the required developers’ IAM role to the IAM groups within each AWS account.
F) Create IAM policies based on data classification and type. Add the minimum required IAM policies to the developers’ IAM role within each AWS account.
Question 132: A company is ready to deploy a public web application. The company will use AWS and will host the application on an Amazon EC2 instance. The company must use SSL/TLS encryption. The company is already using AWS Certificate Manager (ACM) and will export a certificate for use with the deployment.
How can a security engineer deploy the application to meet these requirements?
A) Put the EC2 instance behind an Application Load Balancer (ALB). In the EC2 console, associate the certificate with the ALB by choosing HTTPS and 443.
B) Put the EC2 instance behind a Network Load Balancer. Associate the certificate with the EC2 instance.
C) Put the EC2 instance behind a Network Load Balancer (NLB). In the EC2 console, associate the certificate with the NLB by choosing HTTPS and 443.
D) Put the EC2 instance behind an Application Load Balancer. Associate the certificate with the EC2 instance.
What are the 6 pillars of a well architected framework:
AWS Well-Architected helps cloud architects build secure, high-performing, resilient, and efficient infrastructure for their applications and workloads. Based on five pillars — operational excellence, security, reliability, performance efficiency, and cost optimization — AWS Well-Architected provides a consistent approach for customers and partners to evaluate architectures, and implement designs that can scale over time.
1. Operational Excellence
The operational excellence pillar includes the ability to run and monitor systems to deliver business value and to continually improve supporting processes and procedures. You can find prescriptive guidance on implementation in the Operational Excellence Pillar whitepaper.
2. Security
The security pillar includes the ability to protect information, systems, and assets while delivering business value through risk assessments and mitigation strategies. You can find prescriptive guidance on implementation in the Security Pillar whitepaper.
3. Reliability
The reliability pillar includes the ability of a system to recover from infrastructure or service disruptions, dynamically acquire computing resources to meet demand, and mitigate disruptions such as misconfigurations or transient network issues. You can find prescriptive guidance on implementation in the Reliability Pillar whitepaper.
4. Performance Efficiency
The performance efficiency pillar includes the ability to use computing resources efficiently to meet system requirements and to maintain that efficiency as demand changes and technologies evolve. You can find prescriptive guidance on implementation in the Performance Efficiency Pillar whitepaper.
5. Cost Optimization
The cost optimization pillar includes the ability to avoid or eliminate unneeded cost or suboptimal resources. You can find prescriptive guidance on implementation in the Cost Optimization Pillar whitepaper.
6. Sustainability
- The ability to increase efficiency across all components of a workload by maximizing the benefits from the provisioned resources.
- There are six best practice areas for sustainability in the cloud:
- Region Selection – AWS Global Infrastructure
- User Behavior Patterns – Auto Scaling, Elastic Load Balancing
- Software and Architecture Patterns – AWS Design Principles
- Data Patterns – Amazon EBS, Amazon EFS, Amazon FSx, Amazon S3
- Hardware Patterns – Amazon EC2, AWS Elastic Beanstalk
- Development and Deployment Process – AWS CloudFormation
- Key AWS service:
- Amazon EC2 Auto Scaling
Source: 6 pillards of AWs Well architected Framework
The AWS Well-Architected Framework provides architectural best practices across the five pillars for designing and operating reliable, secure, efficient, and cost-effective systems in the cloud. The framework provides a set of questions that allows you to review an existing or proposed architecture. It also provides a set of AWS best practices for each pillar.
Using the Framework in your architecture helps you produce stable and efficient systems, which allows you to focus on functional requirements.
Other AWS Facts and Summaries and Questions/Answers Dump
- AWS Certified Solution Architect Associate Exam Prep App
- AWS S3 facts and summaries and Q&A Dump
- AWS DynamoDB facts and summaries and Questions and Answers Dump
- AWS EC2 facts and summaries and Questions and Answers Dump
- AWS Serverless facts and summaries and Questions and Answers Dump
- AWS Developer and Deployment Theory facts and summaries and Questions and Answers Dump
- AWS IAM facts and summaries and Questions and Answers Dump
- AWS Lambda facts and summaries and Questions and Answers Dump
- AWS SQS facts and summaries and Questions and Answers Dump
- AWS RDS facts and summaries and Questions and Answers Dump
- AWS ECS facts and summaries and Questions and Answers Dump
- AWS CloudWatch facts and summaries and Questions and Answers Dump
- AWS SES facts and summaries and Questions and Answers Dump
- AWS EBS facts and summaries and Questions and Answers Dump
- AWS ELB facts and summaries and Questions and Answers Dump
- AWS Autoscaling facts and summaries and Questions and Answers Dump
- AWS VPC facts and summaries and Questions and Answers Dump
- AWS KMS facts and summaries and Questions and Answers Dump
- AWS Elastic Beanstalk facts and summaries and Questions and Answers Dump
- AWS CodeBuild facts and summaries and Questions and Answers Dump
- AWS CodeDeploy facts and summaries and Questions and Answers Dump
- AWS CodePipeline facts and summaries and Questions and Answers Dump
What means undifferentiated heavy lifting?
The reality, of course, today is that if you come up with a great idea you don’t get to go quickly to a successful product. There’s a lot of undifferentiated heavy lifting that stands between your idea and that success. The kinds of things that I’m talking about when I say undifferentiated heavy lifting are things like these: figuring out which servers to buy, how many of them to buy, what time line to buy them.
Eventually you end up with heterogeneous hardware and you have to match that. You have to think about backup scenarios if you lose your data center or lose connectivity to a data center. Eventually you have to move facilities. There’s negotiations to be done. It’s a very complex set of activities that really is a big driver of ultimate success.
But they are undifferentiated from, it’s not the heart of, your idea. We call this muck. And it gets worse because what really happens is you don’t have to do this one time. You have to drive this loop. After you get your first version of your idea out into the marketplace, you’ve done all that undifferentiated heavy lifting, you find out that you have to cycle back. Change your idea. The winners are the ones that can cycle this loop the fastest.
On every cycle of this loop you have this undifferentiated heavy lifting, or muck, that you have to contend with. I believe that for most companies, and it’s certainly true at Amazon, that 70% of your time, energy, and dollars go into the undifferentiated heavy lifting and only 30% of your energy, time, and dollars gets to go into the core kernel of your idea.
I think what people are excited about is that they’re going to get a chance they see a future where they may be able to invert those two. Where they may be able to spend 70% of their time, energy and dollars on the differentiated part of what they’re doing.
AWS Certified Solutions Architect Associates Questions and Answers around the web.
Testimonial: Passed SAA-C02!
So my exam was yesterday and I got the results in 24 hours. I think that’s how they review all saa exams, not showing the results right away anymore.
I scored 858. Was practicing with Stephan’s udemy lectures and Bonso exam tests. My test results were as follows Test 1. 63%, 93% Test 2. 67%, 87% Test 3. 81 % Test 4. 72% Test 5. 75 % Test 6. 81% Stephan’s test. 80%
I was reading all question explanations (even the ones I got correct)
The actual exam was pretty much similar to these. The topics I got were:
A lot of S3 (make sure you know all of it from head to toes)
VPC peering
DataSync and Database Migration Service in same questions. Make sure you know the difference
One EKS question
2-3 KMS questions
Security group question
A lot of RDS Multi-AZ
SQS + SNS fan out pattern
ECS microservice architecture question
Route 53
NAT gateway
And that’s all I can remember)
I took extra 30 minutes, because English is not my native language and I had plenty of time to think and then review flagged questions.
Good luck with your exams guys!
Testimonial: Passed SAA-C02
Hey guys, just giving my update so all of you guys working towards your certs can stay motivated as these success stories drove me to reach this goal.
Background: 12 years of military IT experience, never worked with the cloud. I’ve done 7 deployments (that is a lot in 12 years), at which point I came home from the last one burnt out with a family that barely knew me. I knew I needed a change, but had no clue where to start or what I wanted to do. I wasn’t really interested in IT but I knew it’d pay the bills. After seeing videos about people in IT working from home(which after 8+ years of being gone from home really appealed to me), I stumbled across a video about a Solutions Architect’s daily routine working from home and got me interested in AWS.
AWS Solutions Architect SAA Certification Preparation time: It took me 68 days straight of hard work to pass this exam with confidence. No rest days, more than 120 pages of hand-written notes and hundreds and hundreds of flash cards.
In the beginning, I hopped on Stephane Maarek’s course for the CCP exam just to see if it was for me. I did the course in about a week and then after doing some research on here, got the CCP Practice exams from tutorialsdojo.com Two weeks after starting the Udemy course, I passed the exam. By that point, I’d already done lots of research on the different career paths and the best way to study, etc.
Cantrill(10/10) – That same day, I hopped onto Cantrill’s course for the SAA and got to work. Somebody had mentioned that by doing his courses you’d be over-prepared for the exam. While I think a combination of material is really important for passing the certification with confidence, I can say without a doubt Cantrill’s courses got me 85-90% of the way there. His forum is also amazing, and has directly contributed to me talking with somebody who works at AWS to land me a job, which makes the money I spent on all of his courses A STEAL. As I continue my journey (up next is SA Pro), I will be using all of his courses.
Neal Davis(8/10) – After completing Cantrill’s course, I found myself needing a resource to reinforce all the material I’d just learned. AWS is an expansive platform and the many intricacies of the different services can be tricky. For this portion, I relied on Neal Davis’s Training Notes series. These training notes are a very condensed version of the information you’ll need to pass the exam, and with the proper context are very useful to find the things you may have missed in your initial learnings. I will be using his other Training Notes for my other exams as well.
TutorialsDojo(10/10) – These tests filled in the gaps and allowed me to spot my weaknesses and shore them up. I actually think my real exam was harder than these, but because I’d spent so much time on the material I got wrong, I was able to pass the exam with a safe score.
As I said, I was surprised at how difficult the exam was. A lot of my questions were related to DBs, and a lot of them gave no context as to whether the data being loaded into them was SQL or NoSQL which made the choice selection a little frustrating. A lot of the questions have 2 VERY SIMILAR answers, and often time the wording of the answers could be easy to misinterpret (such as when you are creating a Read Replica, do you attach it to the primary application DB that is slowing down because of read issues or attach it to the service that is causing the primary DB to slow down). For context, I was scoring 95-100% on the TD exams prior to taking the test and managed a 823 on the exam so I don’t know if I got unlucky with a hard test or if I’m not as prepared as I thought I was (i.e. over-thinking questions).
Anyways, up next is going back over the practical parts of the course as I gear up for the SA Pro exam. I will be taking my time with this one, and re-learning the Linux CLI in preparation for finding a new job.
PS if anybody on here is hiring, I’m looking! I’m the hardest worker I know and my goal is to make your company as streamlined and profitable as possible. 🙂
Testimonial: How did you prepare for AWS Certified Solutions Architect – Associate Level certification?
Best way to prepare for aws solution architect associate certification
Practical knowledge is 30% important and rest is Jayendra blog and Dumps.
Buying udemy courses doesn’t make you pass, I can tell surely without going to dumps and without going to jayendra’s blog not easy to clear the certification.
Read FAQs of S3, IAM, EC2, VPC, SQS, Autoscaling, Elastic Load Balancer, EBS, RDS, Lambda, API Gateway, ECS.
Read the Security Whitepaper and Shared Responsibility model.
The most important thing is basic questions from the last introduced topics to the exam is very important like Amazon Kinesis, etc…
– ACloudGuru course with practice test’s
– Created my own cheat sheet in excel
– Practice questions on various website
– Few AWS services FAQ’s
– Some questions were your understanding about which service to pick for the use case.
– many questions on VPC
– a couple of unexpected question on AWS CloudHSM, AWS systems manager, aws athena
– encryption at rest and in transit services
– migration from on-premise to AWS
– backup data in az vs regional
I believe the time was sufficient.
Overall I feel AWS SAA was more challenging in theory than GCP Associate CE.
some resources I bookmarked:
- Comparison of AWS Services
- Solutions Architect – Associate | Qwiklabs
- okeeffed/cheat-sheets
- A curated list of AWS resources to prepare for the AWS Certifications
- AWS Cheat Sheet
Whitepapers are the important information about each services that are published by Amazon in their website. If you are preparing for the AWS certifications, it is very important to use the some of the most recommended whitepapers to read before writing the exam.
The following are the list of whitepapers that are useful for preparing solutions architectexam. Also you will be able to find the list of whitepapers in the exam blueprint.
- Overview of Security Processes
- Storage Options in the Cloud
- Defining Fault Tolerant Applications in the AWS Cloud
- Overview of Amazon Web Services
- Compliance Whitepaper
- Architecting for the AWS Cloud
Data Security questions could be the more challenging and it’s worth noting that you need to have a good understanding of security processes described in the whitepaper titled “Overview of Security Processes”.
In the above list, most important whitepapers are Overview of Security Processes and Storage Options in the Cloud. Read more here…
Big thanks to /u/acantril for his amazing course – AWS Certified Solutions Architect – Associate (SAA-C02) – the best IT course I’ve ever had – and I’ve done many on various other platforms:
CBTNuggets
LinuxAcademy
ACloudGuru
Udemy
Linkedin
O’Reilly
- #AWS #SAAC02 #SAAC03 #SolutionsArchitect #AWSSAA #SAA #AWSCertification #AWSTraining #LearnAWS #CloudArchitect #SolutionsArchitect #Djamgatech
If you’re on the fence with buying one of his courses, stop thinking and buy it, I guarantee you won’t regret it! Other materials used for study:
Jon Bonso Practice Exams for SAA-C02 @ Tutorialsdojo (amazing practice exams!)
Random YouTube videos (example)
Official AWS Documentation (example)
TechStudySlack (learning community)
Study duration approximately ~3 months with the following regimen:
Daily study from
30min
to2hrs
Usually early morning before work
Sometimes on the train when commuting from/to work
Sometimes in the evening
Due to being a father/husband, study wasn’t always possible
All learned topics reviewed weekly
Testimonial: I passed SAA-C02 … But don’t do what I did to pass it
I’ve been following this subreddit for awhile and gotten some helpful tips, so I’d like to give back with my two cents. FYI I passed the exam 788
The exam materials that I used were the following:
AWS Certified Solutions Architect Associate All-in-One Exam Guide (Banerjee)
Stephen Maarek’s Udemy course, and his 6 exam practices
Adrian Cantrill’s online course (about `60% done)
TutorialDojo’s exams
(My company has udemy business account so I was able to use Stephen’s course/exam)
I scheduled my exam at the end of March, and started with Adrian’s. But I was dumb thinking that I could go through his course within 3 weeks… I stopped around 12% of his course and went to the textbook and finished reading the all-in-one exam guide within a weekend. Then I started going through Stephen’s course. While learning the course, I pushed back the exam to end of April, because I knew I wouldn’t be ready by the exam comes along.
Five days before the exam, I finished Stephen’s course, and then did his final exam on the course. I failed miserably (around 50%). So I did one of Stephen’s practice exam and did worse (42%). I thought maybe it might be his exams that are slightly difficult, so I went and bought Jon Bonso’s exam and got 60% on his first one. And then I realized based on all the questions on the exams, I was definitely lacking some fundamentals. I went back to Adrian’s course and things were definitely sticking more – I think it has to do with his explanations + more practical stuff. Unfortunately, I could not finish his course before the exam (because I was cramming), and on the day of the exam, I could only do Bonso’s four of six exams, with barely passing one of them.
Please, don’t do what I did. I was desperate to get this thing over with it. I wanted to move on and work on other things for job search, but if you’re not in this situation, please don’t do this. I can’t for love of god tell you about OAI and Cloudfront and why that’s different than S3 URL. The only thing that I can remember is all the practical stuff that I did with Adrian’s course. I’ll never forget how to create VPC, because he make you manually go through it. I’m not against Stephen’s course – they are different on its own way (see the tips below).
So here’s what I recommend doing before writing for aws exam:
Don’t schedule your exam beforehand. Go through the materials that you are doing, and make sure you get at least 80% on all of the Jon Bonso’s exam (I’d recommend maybe 90% or higher)
If you like to learn things practically, I do recommend Adrian’s course. If you like to learn things conceptually, go with Stephen Maarek’s course. I find Stephen’s course more detailed when going through different architectures, but I can’t really say that because I didn’t really finish Adrian’s course
Jon Bonso’s exam was about the same difficulty as the actual exam. But they’re slightly more tricky. For example, many of the questions will give you two different situation and you really have to figure out what they are asking for because they might contradict to each other, but the actual question is asking one specific thing. However, there were few questions that were definitely obvious if you knew the service.
I’m upset that even though I passed the exam, I’m still lacking some practical stuff, so I’m just going to go through Adrian’s Developer exam but without cramming this time. If you actually learn the materials and practice them, they are definitely useful in the real world. I hope this will help you passing and actually learning the stuff.
P.S I vehemently disagree with Adrian in one thing in his course. doggogram.io is definitely better than catagram.io, although his cats are pretty cool
Testimonial: I passed the SAA-C02 exam!
I sat the exam at a PearsonVUE test centre and scored 816.
The exam had lots of questions around S3, RDS and storage. To be honest it was a bit of a blur but they are the ones I remember.
I was a bit worried before sitting the exam as I was only hit 76% in the official AWS practice exam the night before but it turned out alright in the end!
I have around 8 years of experience in IT but AWS was relatively new to me around 5 weeks ago.
Training Material Used
Firstly I ran through the u/stephanemaarek course which I found to pretty much cover all that was required!