The Cloud Education Certification App is an EduFlix App for AWS, Azure, Google Cloud Certification Prep[Android, iOS]
Technology is changing and is moving towards the cloud. The cloud will power most businesses in the coming years and is not taught in schools. How do we ensure that our kids and youth and ourselves are best prepared for this challenge?
Building mobile educational apps that work offline and on any device can help greatly in that sense.
The ability to tab on a button and learn the cloud fundamentals and take quizzes is a great opportunity to help our children and youth to boost their job prospects and be more productive at work.
The App covers the following certifications : AWS Cloud Practitioner Exam Prep CCP CLF-C01, Azure Fundamentals AZ 900 Exam Prep, AWS Certified Solution Architect Associate SAA-C02 Exam Prep, AWS Certified Developer Associate DVA-C01 Exam Prep, Azure Administrator AZ 104 Exam Prep, Google Associate Cloud Engineer Exam Prep, Data Analytics for AWS DAS-C01, Machine Learning for AWS and Google, AWS Certified Security – Specialty (SCS-C01), AWS Certified Machine Learning – Specialty (MLS-C01), Google Cloud Professional Machine Learning Engineer and more… [Android, iOS]
Features: – Practice exams – 1000+ Q&A updated frequently. – 3+ Practice exams per Certification – Scorecard / Scoreboard to track your progress – Quizzes with score tracking, progress bar, countdown timer. – Can only see scoreboard after completing the quiz. – FAQs for most popular Cloud services – Cheat Sheets – Flashcards – works offline
Note and disclaimer: We are not affiliated with AWS, Azure, Microsoft or Google. The questions are put together based on the certification study guide and materials available online. The questions in this app should help you pass the exam but it is not guaranteed. We are not responsible for any exam you did not pass.
Important: To succeed with the real exam, do not memorize the answers in this app. It is very important that you understand why a question is right or wrong and the concepts behind it by carefully reading the reference documents in the answers.
Google Certified Cloud Professional Architect is the top high paying certification in the world: Google Certified Professional Cloud Architect Average Salary – $175,761
The Google Certified Cloud Professional Architect Exam assesses your ability to:
Design and plan a cloud solution architecture
Manage and provision the cloud solution infrastructure
Design for security and compliance
Analyze and optimize technical and business processes
Manage implementations of cloud architecture
Ensure solution and operations reliability
Designing and planning a cloud solution architecture
Designing and planning a cloud solution architecture: 36%
This domain tests your ability to design a solution infrastructure that meets business and technical requirements and considers network, storage and compute resources. It will test your ability to create a migration plan, and that you can envision future solution improvements.
Managing and provisioning a solution Infrastructure: 20%
This domain will test your ability to configure network topologies, individual storage systems and design solutions using Google Cloud networking, storage and compute services.
Designing for security and compliance: 12%
This domain assesses your ability to design for security and compliance by considering IAM policies, separation of duties, encryption of data and that you can design your solutions while considering any compliance requirements such as those for healthcare and financial information.
Managing implementation: 10%
This domain tests your ability to advise development/operation team(s) to make sure you have successful deployment of your solution. It also tests yours ability to interact with Google Cloud using GCP SDK (gcloud, gsutil, and bq).
Ensuring solution and operations reliability: 6%
This domain tests your ability to run your solutions reliably in Google Cloud by building monitoring and logging solutions, quality control measures and by creating release management processes.
Analyzing and optimizing technical and business processes: 16%
This domain will test how you analyze and define technical processes, business processes and develop procedures to ensure resilience of your solutions in production.
Below are the Top 50 Google Certified Cloud Professional Architect Exam Questions and Answers Dumps: You will need to have the three case studies referred to in the exam open in separate tabs in order to complete the exam: Company A , Company B, Company C
Question 1:Because you do not know every possible future use for the data Company A collects, you have decided to build a system that captures and stores all raw data in case you need it later. How can you most cost-effectively accomplish this goal?
A. Have the vehicles in the field stream the data directly into BigQuery.
B. Have the vehicles in the field pass the data to Cloud Pub/Sub and dump it into a Cloud Dataproc cluster that stores data in Apache Hadoop Distributed File System (HDFS) on persistent disks.
C. Have the vehicles in the field continue to dump data via FTP, adjust the existing Linux machines, and use a collector to upload them into Cloud Dataproc HDFS for storage.
D. Have the vehicles in the field continue to dump data via FTP, and adjust the existing Linux machines to immediately upload it to Cloud Storage with gsutil.
ANSWER1:
D
Notes/References1:
D is correct because several load-balanced Compute Engine VMs would suffice to ingest 9 TB per day, and Cloud Storage is the cheapest per-byte storage offered by Google. Depending on the format, the data could be available via BigQuery immediately, or shortly after running through an ETL job. Thus, this solution meets business and technical requirements while optimizing for cost.
Question 2: Today, Company A maintenance workers receive interactive performance graphs for the last 24 hours (86,400 events) by plugging their maintenance tablets into the vehicle. The support group wants support technicians to view this data remotely to help troubleshoot problems. You want to minimize the latency of graph loads. How should you provide this functionality?
A. Execute queries against data stored in a Cloud SQL.
B. Execute queries against data indexed by vehicle_id.timestamp in Cloud Bigtable.
C. Execute queries against data stored on daily partitioned BigQuery tables.
D. Execute queries against BigQuery with data stored in Cloud Storage via BigQuery federation.
ANSWER2:
B
Notes/References2:
B is correct because Cloud Bigtable is optimized for time-series data. It is cost-efficient, highly available, and low-latency. It scales well. Best of all, it is a managed service that does not require significant operations work to keep running.
Question 3: Your agricultural division is experimenting with fully autonomous vehicles. You want your architecture to promote strong security during vehicle operation. Which two architecture characteristics should you consider?
A. Use multiple connectivity subsystems for redundancy.
B. Require IPv6 for connectivity to ensure a secure address space.
C. Enclose the vehicle’s drive electronics in a Faraday cage to isolate chips.
D. Use a functional programming language to isolate code execution cycles.
E. Treat every microservice call between modules on the vehicle as untrusted.
F. Use a Trusted Platform Module (TPM) and verify firmware and binaries on boot.
ANSWER3:
E and F
Notes/References3:
E is correct because this improves system security by making it more resistant to hacking, especially through man-in-the-middle attacks between modules.
F is correct because this improves system security by making it more resistant to hacking, especially rootkits or other kinds of corruption by malicious actors.
Question 4: For this question, refer to the Company A case study.
Which of Company A’s legacy enterprise processes will experience significant change as a result of increased Google Cloud Platform adoption?
A. OpEx/CapEx allocation, LAN change management, capacity planning
B. Capacity planning, TCO calculations, OpEx/CapEx allocation
C. Capacity planning, utilization measurement, data center expansion
D. Data center expansion, TCO calculations, utilization measurement
ANSWER4:
B
Notes/References4:
B is correct because all of these tasks are big changes when moving to the cloud. Capacity planning for cloud is different than for on-premises data centers; TCO calculations are adjusted because Company A is using services, not leasing/buying servers; OpEx/CapEx allocation is adjusted as services are consumed vs. using capital expenditures.
Question 5: For this question, refer to the Company A case study.
You analyzed Company A’s business requirement to reduce downtime and found that they can achieve a majority of time saving by reducing customers’ wait time for parts. You decided to focus on reduction of the 3 weeks’ aggregate reporting time. Which modifications to the company’s processes should you recommend?
A. Migrate from CSV to binary format, migrate from FTP to SFTP transport, and develop machine learning analysis of metrics.
B. Migrate from FTP to streaming transport, migrate from CSV to binary format, and develop machine learning analysis of metrics.
C. Increase fleet cellular connectivity to 80%, migrate from FTP to streaming transport, and develop machine learning analysis of metrics.
D. Migrate from FTP to SFTP transport, develop machine learning analysis of metrics, and increase dealer local inventory by a fixed factor.
ANSWER5:
C
Notes/References5:
C is correct because using cellular connectivity will greatly improve the freshness of data used for analysis from where it is now, collected when the machines are in for maintenance. Streaming transport instead of periodic FTP will tighten the feedback loop even more. Machine learning is ideal for predictive maintenance workloads.
Question 6: Your company wants to deploy several microservices to help their system handle elastic loads. Each microservice uses a different version of software libraries. You want to enable their developers to keep their development environment in sync with the various production services. Which technology should you choose?
A. RPM/DEB
B. Containers
C. Chef/Puppet
D. Virtual machines
ANSWER6:
B
Notes/References6:
B is correct because using containers for development, test, and production deployments abstracts away system OS environments, so that a single host OS image can be used for all environments. Changes that are made during development are captured using a copy-on-write filesystem, and teams can easily publish new versions of the microservices in a repository.
Question 7: Your company wants to track whether someone is present in a meeting room reserved for a scheduled meeting. There are 1000 meeting rooms across 5 offices on 3 continents. Each room is equipped with a motion sensor that reports its status every second. You want to support the data upload and collection needs of this sensor network. The receiving infrastructure needs to account for the possibility that the devices may have inconsistent connectivity. Which solution should you design?
A. Have each device create a persistent connection to a Compute Engine instance and write messages to a custom application.
B. Have devices poll for connectivity to Cloud SQL and insert the latest messages on a regular interval to a device specific table.
C. Have devices poll for connectivity to Cloud Pub/Sub and publish the latest messages on a regular interval to a shared topic for all devices.
D. Have devices create a persistent connection to an App Engine application fronted by Cloud Endpoints, which ingest messages and write them to Cloud Datastore.
ANSWER7:
C
Notes/References7:
C is correct becauseCloudPub/Sub can handle the frequency of this data, and consumers of the data can pull from the shared topic for further processing.
Question 8: Your company wants to try out the cloud with low risk. They want to archive approximately 100 TB of their log data to the cloud and test the analytics features available to them there, while also retaining that data as a long-term disaster recovery backup. Which two steps should they take?
A. Load logs into BigQuery.
B. Load logs into Cloud SQL.
C. Import logs into Stackdriver.
D. Insert logs into Cloud Bigtable.
E. Upload log files into Cloud Storage.
ANSWER8:
A and E
Notes/References8:
A is correct because BigQuery is the fully managed cloud data warehouse for analytics and supports the analytics requirement.
E is correct because Cloud Storage provides the Coldline storage class to support long-term storage with infrequent access, which would support the long-term disaster recovery backup requirement.
Question 9: You set up an autoscaling instance group to serve web traffic for an upcoming launch. After configuring the instance group as a backend service to an HTTP(S) load balancer, you notice that virtual machine (VM) instances are being terminated and re-launched every minute. The instances do not have a public IP address. You have verified that the appropriate web response is coming from each instance using the curl command. You want to ensure that the backend is configured correctly. What should you do?
A. Ensure that a firewall rule exists to allow source traffic on HTTP/HTTPS to reach the load balancer.
B. Assign a public IP to each instance, and configure a firewall rule to allow the load balancer to reach the instance public IP.
C. Ensure that a firewall rule exists to allow load balancer health checks to reach the instances in the instance group.
D. Create a tag on each instance with the name of the load balancer. Configure a firewall rule with the name of the load balancer as the source and the instance tag as the destination.
ANSWER9:
C
Notes/References9:
C is correct because health check failures lead to a VM being marked unhealthy and can result in termination if the health check continues to fail. Because you have already verified that the instances are functioning properly, the next step would be to determine why the health check is continuously failing.
Question 10: Your organization has a 3-tier web application deployed in the same network on Google Cloud Platform. Each tier (web, API, and database) scales independently of the others. Network traffic should flow through the web to the API tier, and then on to the database tier. Traffic should not flow between the web and the database tier. How should you configure the network?
A. Add each tier to a different subnetwork.
B. Set up software-based firewalls on individual VMs.
C. Add tags to each tier and set up routes to allow the desired traffic flow.
D. Add tags to each tier and set up firewall rules to allow the desired traffic flow.
ANSWER10:
D
Notes/References10:
D is correct because as instances scale, they will all have the same tag to identify the tier. These tags can then be leveraged in firewall rules to allow and restrict traffic as required, because tags can be used for both the target and source.
Question 11: Your organization has 5 TB of private data on premises. You need to migrate the data to Cloud Storage. You want to maximize the data transfer speed. How should you migrate the data?
A. Use gsutil.
B. Use gcloud.
C. Use GCS REST API.
D. Use Storage Transfer Service.
ANSWER11:
A
Notes/References11:
A is correct because gsutil gives you access to write data to Cloud Storage.
Question 12: You are designing a mobile chat application. You want to ensure that people cannot spoof chat messages by proving that a message was sent by a specific user. What should you do?
A. Encrypt the message client-side using block-based encryption with a shared key.
B. Tag messages client-side with the originating user identifier and the destination user.
C. Use a trusted certificate authority to enable SSL connectivity between the client application and the server.
D. Use public key infrastructure (PKI) to encrypt the message client-side using the originating user’s private key.
ANSWER12:
D
Notes/References12:
D is correct because PKI requires that both the server and the client have signed certificates, validating both the client and the server.
Question 13: You are designing a large distributed application with 30 microservices. Each of your distributed microservices needs to connect to a database backend. You want to store the credentials securely. Where should you store the credentials?
A. In the source code
B. In an environment variable
C. In a key management system
D. In a config file that has restricted access through ACLs
Question 14: For this question, refer to the Company B case study.
Company B wants to set up a real-time analytics platform for their new game. The new platform must meet their technical requirements. Which combination of Google technologies will meet all of their requirements?
A. Kubernetes Engine, Cloud Pub/Sub, and Cloud SQL
B. Cloud Dataflow, Cloud Storage, Cloud Pub/Sub, and BigQuery
C. Cloud SQL, Cloud Storage, Cloud Pub/Sub, and Cloud Dataflow
D. Cloud Pub/Sub, Compute Engine, Cloud Storage, and Cloud Dataproc
ANSWER14:
B
Notes/References14:
B is correct because: – Cloud Dataflow dynamically scales up or down, can process data in real time, and is ideal for processing data that arrives late using Beam windows and triggers. – Cloud Storage can be the landing space for files that are regularly uploaded by users’ mobile devices. – Cloud Pub/Sub can ingest the streaming data from the mobile users. BigQuery can query more than 10 TB of historical data.
Question 15: For this question, refer to the Company B case study.
Company B has deployed their new backend on Google Cloud Platform (GCP). You want to create a thorough testing process for new versions of the backend before they are released to the public. You want the testing environment to scale in an economical way. How should you design the process?A. Create a scalable environment in GCP for simulating production load.B. Use the existing infrastructure to test the GCP-based backend at scale. C. Build stress tests into each component of your application and use resources from the already deployed production backend to simulate load.D. Create a set of static environments in GCP to test different levels of load—for example, high, medium, and low.
ANSWER15:
A
Notes/References15:
A is correct because simulating production load in GCP can scale in an economical way.
Question 16:For this question, refer to the Company B case study.
Company B wants to set up a continuous delivery pipeline. Their architecture includes many small services that they want to be able to update and roll back quickly. Company B has the following requirements:
Services are deployed redundantly across multiple regions in the US and Europe
Only frontend services are exposed on the public internet.
They can reserve a single frontend IP for their fleet of services.
Deployment artifacts are immutable
Which set of products should they use?
A. Cloud Storage, Cloud Dataflow, Compute Engine
B. Cloud Storage, App Engine, Cloud Load Balancing
C. Container Registry, Google Kubernetes Engine, Cloud Load Balancing
D. Cloud Functions, Cloud Pub/Sub, Cloud Deployment Manager
ANSWER16:
C
Notes/References16:
C is correct because: –Google Kubernetes Engine is ideal for deploying small services that can be updated and rolled back quickly. It is a best practice to manage services using immutable containers. –Cloud Load Balancing supports globally distributed services across multiple regions. It provides a single global IP address that can be used in DNS records. Using URL Maps, the requests can be routed to only the services that Company B wants to expose. –Container Registry is a single place for a team to manage Docker images for the services.
Question 17: Your customer is moving their corporate applications to Google Cloud Platform. The security team wants detailed visibility of all resources in the organization. You use Resource Manager to set yourself up as the org admin. What Cloud Identity and Access Management (Cloud IAM) roles should you give to the security team?
A. Org viewer, Project owner
B. Org viewer, Project viewer
C. Org admin, Project browser
D. Project owner, Network admin
ANSWER17:
B
Notes/References17:
B is correct because: –Org viewer grants the security team permissions to view the organization's display name. –Project viewer grants the security team permissions to see the resources within projects.
Question 18: To reduce costs, the Director of Engineering has required all developers to move their development infrastructure resources from on-premises virtual machines (VMs) to Google Cloud Platform. These resources go through multiple start/stop events during the day and require state to persist. You have been asked to design the process of running a development environment in Google Cloud while providing cost visibility to the finance department. Which two steps should you take?
A. Use persistent disks to store the state. Start and stop the VM as needed.
B. Use the –auto-delete flag on all persistent disks before stopping the VM.
C. Apply VM CPU utilization label and include it in the BigQuery billing export.
D. Use BigQuery billing export and labels to relate cost to groups.
E. Store all state in local SSD, snapshot the persistent disks, and terminate the VM.F. Store all state in Cloud Storage, snapshot the persistent disks, and terminate the VM.
ANSWER18:
A and D
Notes/References18:
A is correct because persistent disks will not be deleted when an instance is stopped.
D is correct because exporting daily usage and cost estimates automatically throughout the day to a BigQuery dataset is a good way of providing visibility to the finance department. Labels can then be used to group the costs based on team or cost center.
Question 19: Your company has decided to make a major revision of their API in order to create better experiences for their developers. They need to keep the old version of the API available and deployable, while allowing new customers and testers to try out the new API. They want to keep the same SSL and DNS records in place to serve both APIs. What should they do?
A. Configure a new load balancer for the new version of the API.
B. Reconfigure old clients to use a new endpoint for the new API.
C. Have the old API forward traffic to the new API based on the path.
D. Use separate backend services for each API path behind the load balancer.
ANSWER19:
D
Notes/References19:
D is correct because an HTTP(S) load balancer can direct traffic reaching a single IP to different backends based on the incoming URL.
Question 20: The database administration team has asked you to help them improve the performance of their new database server running on Compute Engine. The database is used for importing and normalizing the company’s performance statistics. It is built with MySQL running on Debian Linux. They have an n1-standard-8 virtual machine with 80 GB of SSD zonal persistent disk. What should they change to get better performance from this system in a cost-effective manner?
A. Increase the virtual machine’s memory to 64 GB.
B. Create a new virtual machine running PostgreSQL.
C. Dynamically resize the SSD persistent disk to 500 GB.
D. Migrate their performance metrics warehouse to BigQuery.
ANSWER20:
C
Notes/References20:
C is correct because persistent disk performance is based on the total persistent disk capacity attached to an instance and the number of vCPUs that the instance has. Incrementing the persistent disk capacity will increment its throughput and IOPS, which in turn improve the performance of MySQL.
Question 21: You need to ensure low-latency global access to data stored in a regional GCS bucket. Data access is uniform across many objects and relatively high. What should you do to address the latency concerns?
A. Use Google’s Cloud CDN.
B. Use Premium Tier routing and Cloud Functions to accelerate access at the edges.
C. Do nothing.
D. Use global BigTable storage.
E. Use a global Cloud Spanner instance.
F. Migrate the data to a new multi-regional GCS bucket.
G. Change the storage class to multi-regional.
ANSWER21:
A
Notes/References21:
Cloud Functions cannot be used to affect GCS data access, so that option is simply wrong. BigTable does not have any “global” mode, so that option is wrong, too. Cloud Spanner is not a good replacement for GCS data: the data use cases are different enough that we can assume it would probably not be a good fit. You cannot change a bucket’s location after it has been created–not via the storage class nor any other way; you would have to migrate the data to a new bucket. Google’s Cloud CDN is very easy to turn on, but it does only work for data that comes from within GCP and only if the objects are being accessed frequently enough.
Question 22: You are building a sign-up app for your local neighbourhood barbeque party and you would like to quickly throw together a low-cost application that tracks who will bring what. Which of the following options should you choose?
A. Python, Flask, App Engine Standard
B. Ruby, Nginx, GKE
C. HTML, CSS, Cloud Storage
D. Node.js, Express, Cloud Functions
E. Rust, Rocket, App Engine Flex
F. Perl, CGI, GCE
ANSWER22:
A
Notes/References22:
The Cloud Storage option doesn’t offer any way to coordinate the guest data. App Engine Flex would cost much more to run when no one is on the sign-up site. Cloud Functions could handle processing some API calls, but it would be more work to set up and that option doesn’t mention anything about storage. GKE is way overkill for such a small and simple application. Running Perl CGI scripts on GCE would also cost more than it needs (and probably make you very sad). App Engine Standard makes it super-easy to stand up a Python Flask app and includes easy data storage options, too.
Question 23: Your company has decided to migrate your AWS DynamoDB database to a multi-regional Cloud Spanner instance and you are designing the system to transfer and load all the data to synchronize the DBs and eventually allow for a quick cut-over. A member of your team has some previous experience working with Apache Hadoop. Which of the following options will you choose for the streamed updates that follow the initial import?
A. The DynamoDB table change is captured by Cloud Pub/Sub and written to Cloud Dataproc for processing into a Spanner-compatible format.
B. The DynamoDB table change is captured by Cloud Pub/Sub and written to Cloud Dataflow for processing into a Spanner-compatible format.
C. Changes to the DynamoDB table are captured by DynamoDB Streams. A Lambda function triggered by the stream writes the change to Cloud Pub/Sub. Cloud Dataflow processes the data from Cloud Pub/Sub and writes it to Cloud Spanner.
D. The DynamoDB table is rescanned by a GCE instance and written to a Cloud Storage bucket. Cloud Dataproc processes the data from Cloud Storage and writes it to Cloud Spanner.
E. The DynamoDB table is rescanned by an EC2 instance and written to an S3 bucket. Storage Transfer Service moves the data from S3 to a Cloud Storage bucket. Cloud Dataflow processes the data from Cloud Storage and writes it to Cloud Spanner.
ANSWER23:
C
Notes/References23:
Rescanning the DynamoDB table is not an appropriate approach to tracking data changes to keep the GCP-side of this in synch. The fact that someone on your team has previous Hadoop experience is not a good enough reason to choose Cloud Dataproc; that’s a red herring. The options purporting to connect Cloud Pub/Sub directly to the DynamoDB table won’t work because there is no such functionality.
Question 24: Your client is a manufacturing company and they have informed you that they will be pausing all normal business activities during a five-week summer holiday period. They normally employ thousands of workers who constantly connect to their internal systems for day-to-day manufacturing data such as blueprints and machine imaging, but during this period the few on-site staff will primarily be re-tooling the factory for the next year’s production runs and will not be performing any manufacturing tasks that need to access these cloud-based systems. When the bulk of the staff return, they will primarily work on the new models but may spend about 20% of their time working with models from previous years. The company has asked you to reduce their GCP costs during this time, so which of the following options will you suggest?
A. Pause all Cloud Functions via the UI and unpause them when work starts back up.
B. Disable all Cloud Functions via the command line and re-enable them when work starts back up.
C. Delete all Cloud Functions and recreate them when work starts back up.
D. Convert all Cloud Functions to run as App Engine Standard applications during the break.
E. None of these options is a good suggestion.
ANSWER24:
E
Notes/References24:
Cloud Functions scale themselves down to zero when they’re not being used. There is no need to do anything with them.
Question 25: You need a place to store images before updating them by file-based render farm software running on a cluster of machines. Which of the following options will you choose?
A. Container Registry
B. Cloud Storage
C. Cloud Filestore
D. Persistent Disk
ANSWER25:
C
Notes/References25:
There are several different kinds of “images” that you might need to consider–maybe they are normal picture-image files, maybe they are Docker container images, maybe VM or disk images, or maybe something else. In this question, “images” refers to visual images, thus eliminating CI/CD products like Container Registry. Compute Engine is not a storage product and should be eliminated. The term “file-based” software means that it is unlikely to work well with object-based storage like Cloud Storage (or any of its storage classes). Persistent Disk cannot offer shared access across a cluster of machines when writes are involved; it only handles multiple readers. However, Cloud Filestore is made to provide shared, file-based storage for a cluster of machines as described in the question.
Question 26: Your company has decided to migrate your AWS DynamoDB database to a multi-regional Cloud Spanner instance and you are designing the system to transfer and load all the data to synchronize the DBs and eventually allow for a quick cut-over. A member of your team has some previous experience working with Apache Hadoop. Which of the following options will you choose for the initial data import?
A. The DynamoDB table is scanned by an EC2 instance and written to an S3 bucket. Storage Transfer Service moves the data from S3 to a Cloud Storage bucket. Cloud Dataflow processes the data from Cloud Storage and writes it to Cloud Spanner.
B. The DynamoDB table data is captured by DynamoDB Streams. A Lambda function triggered by the stream writes the data to Cloud Pub/Sub. Cloud Dataflow processes the data from Cloud Pub/Sub and writes it to Cloud Spanner.
C. The DynamoDB table data is captured by Cloud Pub/Sub and written to Cloud Dataproc for processing into a Spanner-compatible format.
D. The DynamoDB table is scanned by a GCE instance and written to a Cloud Storage bucket. Cloud Dataproc processes the data from Cloud Storage and writes it to Cloud Spanner.
ANSWER26:
A
Notes/References26:
The same data processing will have to happen for both the initial (batch) data load and the incremental (streamed) data changes that follow it. So if the solution built to handle the initial batch doesn't also work for the stream that follows it, then the processing code would have to be written twice. A Professional Cloud Architect should recognize this project-level issue and not over-focus on the (batch) portion called out in this particular question. This is why you don’t want to choose Cloud Dataproc. Instead, Cloud Dataflow will handle both the initial batch load and also the subsequent streamed data. The fact that someone on your team has previous Hadoop experience is not a good enough reason to choose Cloud Dataproc; that’s a red herring. The DynamoDB streams option would be great for the db synchronization that follows, but it can’t handle the initial data load because DynamoDB Streams only fire for data changes. The option purporting to connect Cloud Pub/Sub directly to the DynamoDB table won’t work because there is no such functionality.
Question 27: You need a managed service to handle logging data coming from applications running in GKE and App Engine Standard. Which option should you choose?
A. Cloud Storage
B. Logstash
C. Cloud Monitoring
D. Cloud Logging
E. BigQuery
F. BigTable
ANSWER27:
D
Notes/References27:
Cloud Monitoring is made to handle metrics, not logs. Logstash is not a managed service. And while you could store application logs in almost any storage service, the Cloud Logging service–aka Stackdriver Logging–is purpose-built to accept and process application logs from many different sources. Oh, and you should also be comfortable dealing with products and services by names other than their current official ones. For example, “GKE” used to be called “Container Engine”, “Cloud Build” used to be “Container Builder”, the “GCP Marketplace” used to be called “Cloud Launcher”, and so on.
Question 28: You need a place to store images before serving them from AppEngine Standard. Which of the following options will you choose?
A. Compute Engine
B. Cloud Filestore
C. Cloud Storage
D. Persistent Disk
E. Container Registry
F. Cloud Source Repositories
G. Cloud Build
H. Nearline
ANSWER28:
C
Notes/References28:
There are several different kinds of “images” that you might need to consider–maybe they are normal picture-image files, maybe they are Docker container images, maybe VM or disk images, or maybe something else. In this question, “images” refers to picture files, because that’s something that you would serve from a web server product like AppEngine Standard, so we eliminate Cloud Build (which isn’t actually for storage, at all) and the other two CI/CD products: Cloud Source Repositories and Container Registry. You definitely could store image files on Cloud Filestore or Persistent Disk, but you can’t hook those up to AppEngine Standard, so those options need to be eliminated, too. The only options left are both types of Cloud Storage, but since “Cloud Storage” sits next to “Coldline” as an option, we can confidently infer that the former refers to the “Standard” storage class. Since the question implies that these images will be served by AppEngine Standard, we would prefer to use the Standard storage class over the Coldline one–so there’s our answer.
Question 29: You need to ensure low-latency global access to data stored in a multi-regional GCS bucket. Data access is uniform across many objects and relatively low. What should you do to address the latency concerns?
A. Use a global Cloud Spanner instance.
B. Change the storage class to multi-regional.
C. Use Google’s Cloud CDN.
D. Migrate the data to a new regional GCS bucket.
E. Do nothing.
F. Use global BigTable storage.
ANSWER29:
E
Notes/References29:
Cloud Functions cannot be used to affect GCS data access, so that option is simply wrong. BigTable does not have any “global” mode, so that option is wrong, too. Cloud Spanner is not a good replacement for GCS data: the data use cases are different enough that we can assume it would probably not be a good fit. You cannot change a bucket’s location after it has been created–not via the storage class nor any other way; you would have to migrate the data to a new bucket. But migrating the data to a regional bucket only helps when the data access will primarily be from that region. Google’s Cloud CDN is very easy to turn on, but it does only work for data that comes from within GCP and only if the objects are being accessed frequently enough to get cached based on previous requests. Because the access per object is so low, Cloud CDN won’t really help. This then brings us back to the question. Now, it may seem implied, but the question does not specifically state that there is currently a problem with latency, only that you need to ensure low latency–and we are already using what would be the best fit for this situation: a multi-regional CS bucket.
Question 30: You need to ensure low-latency GCP access to a volume of historical data that is currently stored in an S3 bucket. Data access is uniform across many objects and relatively high. What should you do to address the latency concerns?
A. Use Premium Tier routing and Cloud Functions to accelerate access at the edges.
B. Use Google’s Cloud CDN.
C. Use global BigTable storage.
D. Do nothing.
E. Migrate the data to a new multi-regional GCS bucket.
F. Use a global Cloud Spanner instance.
ANSWER30:
E
Notes/References30:
Cloud Functions cannot be used to affect GCS data access, so that option is simply wrong. BigTable does not have any “global” mode, so that option is wrong, too. Cloud Spanner is not a good replacement for GCS data: the data use cases are different enough that we can assume it would probably not be a good fit–and it would likely be unnecessarily expensive. You cannot change a bucket’s location after it has been created–not via the storage class nor any other way; you would have to migrate the data to a new bucket. Google’s Cloud CDN is very easy to turn on, but it does only work for data that comes from within GCP and only if the objects are being accessed frequently enough. So even if you would want to use Cloud CDN, you have to migrate the data into a GCS bucket first, so that’s a better option.
Question 31: You are lifting and shifting into GCP a system that uses a subnet-based security model. It has frontend and backend tiers and will be deployed in three regions. How many subnets will you need?
A. Six
B. One
C. Three
D. Four
E. Two
F. Nine
ANSWER31:
A
Notes/References31:
A single subnet spans and can be used across all zones in a single region, but you will need different subnets in different regions. Also, to implement subnet-level network security, you need to separate each tier into its own subnet. In this case, you have two tiers which will each need their own subnet in each of the three regions in which you will deploy this system.
Question 32: You need a place to produce images before deploying them to AppEngine Flex. Which of the following options will you choose?
A. Container Registry
B. Cloud Storage
C. Persistent Disk
D. Nearline
E. Cloud Source Repositories
F. Cloud Build
G. Cloud Filestore
H. Compute Engine
ANSWER32:
F
Notes/References32:
There are several different kinds of “images” that you might need to consider–maybe they are normal picture-image files, maybe they are Docker container images, maybe VM or disk images, or maybe something else. In this question, “deploying [these images] to AppEngine Flex” lets us know that we are dealing with Docker container images, and thus although they would likely be stored in the Container Registry, after being built, this question asks us where that building might happen, which is Cloud Build. Cloud Build, which used to be called Container Builder, is ideal for building container images–though it can also be used to build almost any artifacts, really. You could also do this on Compute Engine, but that option requires much more work to manage and is therefore worse.
Question 33: You are lifting and shifting into GCP a system that uses a subnet-based security model. It has frontend, app, and data tiers and will be deployed in three regions. How many subnets will you need?
A. Two
B. One
C. Three
D. Nine
E. Four
F. Six
ANSWER33:
D
Notes/References33:
A single subnet spans and can be used across all zones in a single region, but you will need different subnets in different regions. Also, to implement subnet-level network security, you need to separate each tier into its own subnet. In this case, you have three tiers which will each need their own subnet in each of the three regions in which you will deploy this system.
Question 34: You need a place to store images in case any of them are needed as evidence for a tax audit over the next seven years. Which of the following options will you choose?
A. Cloud Filestore
B. Coldline
C. Nearline
D. Persistent Disk
E. Cloud Source Repositories
F. Cloud Storage
G. Container Registry
ANSWER34:
B
Notes/References34:
There are several different kinds of “images” that you might need to consider–maybe they are normal picture-image files, maybe they are Docker container images, maybe VM or disk images, or maybe something else. In this question, “images” probably refers to picture files, and so Cloud Storage seems like an interesting option. But even still, when “Cloud Storage” is used without any qualifier, it generally refers to the “Standard” storage class, and this question also offers other storage classes as response options. Because the images in this scenario are unlikely to be used more than once a year (we can assume that taxes are filed annually and there’s less than 100% chance of being audited), the right storage class is Coldline.
Question 35: You need a place to store images before deploying them to AppEngine Flex. Which of the following options will you choose?
A. Container Registry
B. Cloud Filestore
C. Cloud Source Repositories
D. Persistent Disk
E. Cloud Storage
F. Code Build
G. Nearline
ANSWER35:
A
Notes/References35:
Compute Engine is not a storage product and should be eliminated. There are several different kinds of “images” that you might need to consider–maybe they are normal picture-image files, maybe they are Docker container images, maybe VM or disk images, or maybe something else. In this question, “deploying [these images] to AppEngine Flex” lets us know that we are dealing with Docker container images, and thus they would likely have been stored in the Container Registry.
Question 36: You are configuring a SaaS security application that updates your network’s allowed traffic configuration to adhere to internal policies. How should you set this up?
A. Install the application on a new appropriately-sized GCE instance running in your host VPC, and apply a read-only service account to it.
B. Create a new service account for the app to use and grant it the compute.networkViewer role on the production VPC.
C. Create a new service account for the app to use and grant it the compute.securityAdmin role on the production VPC.
D. Run the application as a container in your system’s staging GKE cluster and grant it access to a read-only service account.
E. Install the application on a new appropriately-sized GCE instance running in your host VPC, and let it use the default service account.
ANSWER36:
C
Notes/References36:
You do not install a Software-as-a-Service application yourself; instead, it runs on the vendor's own hardware and you configure it for external access. Service accounts are great for this, as they can be used externally and you maintain full control over them (disabling them, rotating their keys, etc.). The principle of least privilege dictates that you should not give any application more ability than it needs, but this app does need to make changes, so you'll need to grant securityAdmin, not networkViewer.
Question 37:You are lifting and shifting into GCP a system that uses a subnet-based security model. It has frontend and backend tiers and will be deployed across three zones. How many subnets will you need?
A. One
B. Six
C. Four
D. Three
E. Nine
ANSWER37:
F
Notes/References37:
A single subnet spans and can be used across all zones in a given region. But to implement subnet-level network security, you need to separate each tier into its own subnet. In this case, you have two tiers, so you only need two subnets.
Question 38:You have been tasked with setting up a system to comply with corporate standards for container image approvals. Which of the following is your best choice for this project?
A. Binary Authorization
B. Cloud IAM
C. Security Key Enforcement
D. Cloud SCC
E. Cloud KMS
ANSWER38:
A
Notes/References38:
Cloud KMS is Google's product for managing encryption keys. Security Key Enforcement is about making sure that people's accounts do not get taken over by attackers, not about managing encryption keys. Cloud IAM is about managing what identities (both humans and services) can access in GCP. Cloud DLP–or Data Loss Prevention–is for preventing data loss by scanning for and redacting sensitive information. Cloud SCC–the Security Command Center–centralizes security information so you can manage it all in one place. Binary Authorization is about making sure that only properly-validated containers can run in your environments.
Question 39: For this question, refer to the Company B‘s case study. Which of the following are most likely to impact the operations of Company B’s game backend and analytics systems?
A. PCI
B. PII
C. SOX
D. GDPR
E. HIPAA
ANSWER39:
B and D
Notes/References39:
There is no patient/health information, so HIPAA does not apply. It would be a very bad idea to put payment card information directly into these systems, so we should assume they’ve not done that–therefore the Payment Card Industry (PCI) standards/regulations should not affect normal operation of these systems. Besides, it’s entirely likely that they never deal with payments directly, anyway–choosing to offload that to the relevant app stores for each mobile platform. Sarbanes-Oxley (SOX) is about proper management of financial records for publicly traded companies and should therefore not apply to these systems. However, these systems are likely to contain some Personally-Identifying Information (PII) about the users who may reside in the European Union and therefore the EU’s General Data Protection Regulations (GDPR) will apply and may require ongoing operations to comply with the “Right to be Forgotten/Erased”.
Question 40:Your new client has advised you that their organization falls within the scope of HIPAA. What can you infer about their information systems?
A. Their customers located in the EU may require them to delete their user data and provide evidence of such.
B. They will also need to pass a SOX audit.
C. They handle money-linked information.
D. Their system deals with medical information.
ANSWER40:
D
Notes/References40:
SOX stands for Sarbanes Oxley and is US regulation governing financial reporting for publicly-traded companies. HIPAA–the Health Insurance Portability and Accountability Act of 1996–is US regulation aimed at safeguarding individuals' (i.e. patients’) health information. PCI is the Payment Card Industry, and they have Data Security Standards (DSS) that must be adhered to by systems handling payment information of any of their member brands (which include Visa, Mastercard, and several others).
Question 41:Your new client has advised you that their organization needs to pass audits by ISO and PCI. What can you infer about their information systems?
A. They handle money-linked information.
B. Their customers located in the EU may require them to delete their user data and provide evidence of such.
C. Their system deals with medical information.
D. They will also need to pass a SOX audit.
ANSWER42:
A
Notes/References42:
SOX stands for Sarbanes Oxley and is US regulation governing financial reporting for publicly-traded companies. HIPAA–the Health Insurance Portability and Accountability Act of 1996–is US regulation aimed at safeguarding individuals' (i.e. patients’) health information. PCI is the Payment Card Industry, and they have Data Security Standards (DSS) that must be adhered to by systems handling payment information of any of their member brands (which include Visa, Mastercard, and several others). ISO is the International Standards Organization, and since they have so many completely different certifications, this does not tell you much.
Question 43:Your new client has advised you that their organization deals with GDPR. What can you infer about their information systems?
A. Their system deals with medical information.
B. Their customers located in the EU may require them to delete their user data and provide evidence of such.
C. They will also need to pass a SOX audit.
D. They handle money-linked information.
ANSWER43:
B
Notes/References43:
SOX stands for Sarbanes Oxley and is US regulation governing financial reporting for publicly-traded companies. HIPAA–the Health Insurance Portability and Accountability Act of 1996–is US regulation aimed at safeguarding individuals' (i.e. patients’) health information. PCI is the Payment Card Industry, and they have Data Security Standards (DSS) that must be adhered to by systems handling payment information of any of their member brands (which include Visa, Mastercard, and several others).
Question 44:For this question, refer to the Company C case study. Once Company C has completed their initial cloud migration as described in the case study, which option would represent the quickest way to migrate their production environment to GCP?
A. Apply the strangler pattern to their applications and reimplement one piece at a time in the cloud
B. Lift and shift all servers at one time
C. Lift and shift one application at a time
D. Lift and shift one server at a time
E. Set up cloud-based load balancing then divert traffic from the DC to the cloud system
F. Enact their disaster recovery plan and fail over
ANSWER44:
F
Notes/References44:
The proposed Lift and Shift options are all talking about different situations than Dress4Win would find themselves in, at that time: they’d then have automation to build a complete prod system in the cloud, but they’d just need to migrate to it. “Just”, right? 🙂 The strangler pattern approach is similarly problematic (in this case), in that it proposes a completely different cloud migration strategy than the one they’ve almost completed. Now, if we purely consider the kicker’s key word “quickest”, using the DR plan to fail over definitely seems like it wins. Setting up an additional load balancer and migrating slowly/carefully would take more time.
Question 45:Which of the following commands is most likely to appear in an environment setup script?
A. gsutil mb -l asia gs://${project_id}-logs
B. gcloud compute instances create –zone–machine-type=n1-highmem-16 newvm
C. gcloud compute instances create –zone–machine-type=f1-micro newvm
D. gcloud compute ssh ${instance_id}
E. gsutil cp -r gs://${project_id}-setup ./install
F. gsutil cp -r logs/* gs://${project_id}-logs/${instance_id}/
ANSWER45:
A
Notes/References45:
The context here indicates that “environment” is an infrastructure environment like “staging” or “prod”, not just a particular command shell. In that sort of a situation, it is likely that you might create some core per-environment buckets that will store different kinds of data like configuration, communication, logging, etc. You're not likely to be creating, deleting, or connecting (sshing) to instances, nor copying files to or from any instances.
Question 46:Your developers are working to expose a RESTful API for your company’s physical dealer locations. Which of the following endpoints would you advise them to include in their design?
A. /dealerLocations/get
B. /dealerLocations
C. /dealerLocations/list
D. Source and destination
E. /getDealerLocations
ANSWER46:
B
Notes/References46:
It might not feel like it, but this is in scope and a fair question. Google expects Professional Cloud Architects to be able to advise on designing APIs according to best practices (check the exam guide!). In this case, it's important to know that RESTful interfaces (when properly designed) use nouns for the resources identified by a given endpoint. That, by itself, eliminates most of the listed options. In HTTP, verbs like GET, PUT, and POST are then used to interact with those endpoints to retrieve and act upon those resources. To choose between the two noun-named options, it helps to know that plural resources are generally already understood to be lists, so there should be no need to add another “/list” to the endpoint.
Question 47:Which of the following commands is most likely to appear in an instance shutdown script?
A. gsutil cp -r gs://${project_id}-setup ./install
B. gcloud compute instances create –zone–machine-type=n1-highmem-16 newvm
C. gcloud compute ssh ${instance_id}
D. gsutil mb -l asia gs://${project_id}-logs
E. gcloud compute instances delete ${instance_id}
F. gsutil cp -r logs/* gs://${project_id}-logs/${instance_id}/
G. gcloud compute instances create –zone–machine-type=f1-micro newvm
ANSWER47:
F
Notes/References47:
The startup and shutdown scripts run on an instance at the time when that instance is starting up or shutting down. Those situations do not generally call for any other instances to be created, deleted, or connected (sshed) to. Also, those would be a very unusual time to make a Cloud Storage bucket, since buckets are the overall and highly-scalable containers that would likely hold the data for all (or at least many) instances in a given project. That said, instance shutdown time may be a time when you'd want to copy some final logs from the instance into some project-wide bucket. (In general, though, you really want to be doing that kind of thing continuously and not just at shutdown time, in case the instance shuts down unexpectedly and not in an orderly fashion that runs your shutdown script.)
Question 48:It is Saturday morning and you have been alerted to a serious issue in production that is both reducing availability to 95% and corrupting some data. Your monitoring tools noticed the issue 5 minutes ago and it was just escalated to you because the on-call tech in line before you did not respond to the page. Your system has an RPO of 10 minutes and an RTO of 120 minutes, with an SLA of 90% uptime. What should you do first?
A. Escalate the decision to the business manager responsible for the SLA
B. Take the system offline
C. Revert the system to the state it was in on Friday morning
D. Investigate the cause of the issue
ANSWER48:
B
Notes/References48:
The data corruption is your primary concern, as your Recovery Point Objective allows only 10 minutes of data loss and you may already have lost 5. (The data corruption means that you may well need to roll back the data to before that started happening.) It might seem crazy, but you should as quickly as possible stop the system so that you do not lose any more data. It would almost certainly take more time than you have left in your RPO to properly investigate and address the issue, but you should then do that next, during the disaster response clock set by your Recovery Time Objective. Escalating the issue to a business manager doesn't make any sense. And neither does it make sense to knee-jerk revert the system to an earlier state unless you have some good indication that doing so will address the issue. Plus, we'd better assume that “revert the system” refers only to the deployment and not the data, because rolling the data back that far would definitely violate the RPO.
Question 49:Which of the following are not processes or practices that you would associate with DevOps?
A. Raven-test the candidate
B. Obfuscate the code
C. Only one of the other options is made up
D. Run the code in your cardinal environment
E. Do a canary deploy
ANSWER49:
A and D
Notes/References49:
Testing your understanding of development and operations in DevOps. In particular, you need to know that a canary deploy is a real thing and it can be very useful to identify problems with a new change you're making before it is fully rolled out to and therefore impacts everyone. You should also understand that “obfuscating” code is a real part of a release process that seeks to protect an organization's source code from theft (by making it unreadable by humans) and usually happens in combination with “minification” (which improves the speed of downloading and interpreting/running the code). On the other hand, “raven-testing” isn't a thing, and neither is a “cardinal environment”. Those bird references are just homages to canary deployments.
Question 50:Your CTO is going into budget meetings with the board, next month, and has asked you to draw up plans to optimize your GCP-based systems for capex. Which of the following options will you prioritize in your proposal?
A. Object lifecycle management
B. BigQuery Slots
C. Committed use discounts
D. Sustained use discounts
E. Managed instance group autoscaling
F. Pub/Sub topic centralization
ANSWER50:
B and C
Notes/References50:
Pub/Sub usage is based on how much data you send through it, not any sort of “topic centralization” (which isn't really a thing). Sustained use discounts can reduce costs, but that's not really something you structure your system around. Now, most organizations prefer to turn Capital Expenditures into Operational Expenses, but since this question is instead asking you to prioritize CapEx, we need to consider the remaining options from the perspective of “spending” (or maybe reserving) defined amounts of money up-front for longer-term use. (Fair warning, though: You may still have some trouble classifying some cloud expenses as “capital” expenditures). With that in mind, GCE's Committed Use Discounts do fit: you “buy” (reserve/prepay) some instances ahead of time and then not have to pay (again) for them as you use them (or don't use them; you've already paid). BigQuery Slots are a similar flat-rate pricing model: you pre-purchase a certain amount of BigQuery processing capacity and your queries use that instead of the on-demand capacity. That means you won't pay more than you planned/purchased, but your queries may finish rather more slowly, too. Managed instance group autoscaling and object lifecycle management can help to reduce costs, but they are not really about capex.
Question 51:In your last retrospective, there was significant disagreement voiced by the members of your team about what part of your system should be built next. Your scrum master is currently away, but how should you proceed when she returns, on Monday?
A. The scrum master is the one who decides
B. The lead architect should get the final say
C. The product owner should get the final say
D. You should put it to a vote of key stakeholders
E. You should put it to a vote of all stakeholders
ANSWER51:
C
Notes/References51:
In Scrum, it is the Product Owner's role to define and prioritize (i.e. set order for) the product backlog items that the dev team will work on. If you haven't ever read it, the Scrum Guide is not too long and quite valuable to have read at least once, for context.
Question 52:Your development team needs to evaluate the behavior of a new version of your application for approximately two hours before committing to making it available to all users. Which of the following strategies will you suggest?
A. Split testing
B. Red-Black
C. A/B
D. Canary
E. Rolling
F. Blue-Green
G. Flex downtime
ANSWER52:
D and E
Notes/References52:
A Blue-Green deployment, also known as a Red-Black deployment, entails having two complete systems set up and cutting over from one of them to the other with the ability to cut back to the known-good old one if there’s any problem with the experimental new one. A canary deployment is where a new version of an app is deployed to only one (or a very small number) of the servers, to see whether it experiences or causes trouble before that version is rolled out to the rest of the servers. When the canary looks good, a Rolling deployment can be used to update the rest of the servers, in-place, one after another to keep the overall system running. “Flex downtime” is something I just made up, but it sounds bad, right? A/B testing–also known as Split testing–is not generally used for deployments but rather to evaluate two different application behaviours by showing both of them to different sets of users. Its purpose is to gather higher-level information about how users interact with the application.
Question 53:You are mentoring a Junior Cloud Architect on software projects. Which of the following “words of wisdom” will you pass along?
A. Identifying and fixing one issue late in the product cycle could cost the same as handling a hundred such issues earlier on
B. Hiring and retaining 10X developers is critical to project success
C. A key goal of a proper post-mortem is to identify what processes need to be changed
D. Adding 100% is a safe buffer for estimates made by skilled estimators at the beginning of a project
E. A key goal of a proper post-mortem is to determine who needs additional training
ANSWER53:
A and C
Notes/References53:
There really can be 10X (and even larger!) differences in productivity between individual contributors, but projects do not only succeed or fail because of their contributions. Bugs are crazily more expensive to find and fix once a system has gone into production, compared to identifying and addressing that issue right up front–yes, even 100x. A post-mortem should not focus on blaming an individual but rather on understanding the many underlying causes that led to a particular event, with an eye toward how such classes of problems can be systematically prevented in the future.
Question 54:Your team runs a service with an SLA to achieve p99 latency of 200ms. This month, your service achieved p95 latency of 250ms. What will happen now?
A. The next month’s SLA will be increased.
B. The next month’s SLO will be reduced.
C. Your client(s) will have to pay you extra.
D. You will have to pay your client(s).
E. There is no impact on payments.
F. There is not enough information to make a determination.
ANSWER54:
D
Notes/References54:
It would be highly unusual for clients to have to pay extra, even if the service performs better than agreed by the SLA. SLAs generally set out penalties (i.e. you pay the client) for below-standard performance. While SLAs are external-facing, SLOs are internal-facing and do not generally relate to performance penalties. Neither SLAs nor SLOs are adaptively changed just because of one month’s performance; such changes would have to happen through rather different processes. A p99 metric is a tougher measure than p95, and p95 is tougher than p90–so meeting the tougher measure would surpass a required SLA, but meeting a weaker measure would not give enough information to say.
Question 55:Your team runs a service with an SLO to achieve p90 latency of 200ms. This month, your service achieved p95 latency of 250ms. What will happen now?
A. The next month’s SLA will be increased.
B. There is no impact on payments.
C. There is not enough information to make a determination.
D. Your client(s) will have to pay you extra.
E. The next month’s SLO will be reduced.
F. You will have to pay your client(s).
ANSWER55:
B
Notes/References55:
It would be highly unusual for clients to have to pay extra, even if the service performs better than agreed by the SLA. SLAs generally set out penalties (i.e. you pay the client) for below-standard performance. While SLAs are external-facing, SLOs are internal-facing and do not generally relate to performance penalties. Neither SLAs nor SLOs are adaptively changed just because of one month’s performance; such changes would have to happen through rather different processes. A p99 metric is a tougher measure than p95, and p95 is tougher than p90–so meeting the tougher measure would surpass a required SLA, but meeting a weaker measure would not give enough information to say.
Question 56:For this question, refer to the Company C case study. How would you recommend Company C address their capacity and utilization concerns?
A. Configure the autoscaling thresholds to follow changing load
B. Provision enough servers to handle trough load and offload to Cloud Functions for higher demand
C. Run cron jobs on their application servers to scale down at night and up in the morning
D. Use Cloud Load Balancing to balance the traffic highs and lows
D. Run automated jobs in Cloud Scheduler to scale down at night and up in the morning
E. Provision enough servers to handle peak load and sell back excess on-demand capacity to the marketplace
ANSWER56:
A
Notes/References56:
The case study notes, “Our traffic patterns are highest in the mornings and weekend evenings; during other times, 80% of our capacity is sitting idle.” Cloud Load Balancing could definitely scale itself to handle this type of load fluctuation, but it would not do anything to address the issue of having enough application server capacity. Provisioning servers to handle peak load is generally inefficient, but selling back excess on-demand capacity to the marketplace just isn’t a thing, so that option must be eliminated, too. Using Cloud Functions would require a different architectural approach for their application servers and it is generally not worth the extra work it would take to coordinate workloads across Cloud Functions and GCE–in practice, you’d just use one or the other. It is possible to manually effect scaling via automated jobs like in Cloud Scheduler or cron running somewhere (though cron running everywhere could create a coordination nightmare), but manual scaling based on predefined expected load levels is far from ideal, as capacity would only very crudely match demand. Rather, it is much better to configure the managed instance group’s autoscaling to follow demand curves–both expected and unexpected. A properly-architected system should rise to the occasion of unexpectedly going viral, and not fall over.
Google Cloud Latest News, Questions and Answers online:
Cloud Run vs App Engine: In a nutshell, you give Google’s Cloud Run a Docker container containing a webserver. Google will run this container and create an HTTP endpoint. All the scaling is automatically done for you by Google. Cloud Run depends on the fact that your application should be stateless. This is because Google will spin up multiple instances of your app to scale it dynamically. If you want to host a traditional web application this means that you should divide it up into a stateless API and a frontend app.
With Google’s App Engine you tell Google how your app should be run. The App Engine will create and run a container from these instructions. Deploying with App Engine is super easy. You simply fill out an app.yml file and Google handles everything for you.
With Cloud Run, you have more control. You can go crazy and build a ridiculous custom Docker image, no problem!Cloud Run is made for Devops engineers, App Engine is made for developers.Read more here…
The best choice depends on what you want to optimize, your use-cases and your specific needs.
If your objective is the lowest latency, choose Cloud Run.
Indeed, Cloud Run use always 1 vCPU (at least 2.4Ghz) and you can choose the memory size from 128Mb to 2Gb.
With Cloud Functions, if you want the best processing performance (2.4Ghz of CPU), you have to pay 2Gb of memory. If your memory footprint is low, a Cloud Functions with 2Gb of memory is overkill and cost expensive for nothing.
Cutting cost is not always the best strategy for customer satisfaction, but business reality may require it. Anyway, it highly depends of your use-case
Both Cloud Run and Cloud Function round up to the nearest 100ms. As you could play with the GSheet, the Cloud Functions are cheaper when the processing time of 1 request is below the first 100ms. Indeed, you can slow the Cloud Functions vCPU, with has for consequence to increase the duration of the processing but while staying under 100ms if you tune it well. Thus less Ghz/s are used and thereby you pay less.
the cost comparison between Cloud Functions and Cloud Run goes further than simply comparing a pricing list. Moreover, on your projects, you often will have to use the 2 solutions for taking advantage of their strengths and capabilities.
My first choice for development is Cloud Run. Its portability, its testability, its openess on the libraries, the languages and the binaries confer it too much advantages for, at least, a similar pricing, and often with a real advantage in cost but also in performance, in particular for concurrent requests. Even if you need the same level of isolation of Cloud functions (1 instance per request), simply set the concurrent param to 1!
In addition, the GA of Cloud Run is applied on all containers, whatever the languages and the binaries used. Read more here…
Google Cloud Storage : What bucket class for the best performance?: Multiregional buckets perform significantly better for cross-the-ocean fetches, however the details are a bit more nuanced than that. The performance is dominated by the latency of physical distance between the client and the cloud storage bucket.
If caching is on, and your access volume is high enough to take advantage of caching, there’s not a huge difference between the two offerings (that I can see with the tests). This shows off the power of Google’s Awesome CDN environment.
If caching is off, or the access volume is low enough that you can’t take advantage of caching, then the performance overhead is dominated directly by physics. You should be trying to get the assets as close to the clients as possible, while also considering cost, and the types of redundancy and consistency you’ll need for your data needs.
The Associate Cloud Engineer exam assesses your ability to: Set up a cloud solution environment, Plan and configure a cloud solution, Deploy and implement a cloud solution, Ensure successful operation of a cloud solution, Configure access and security.
Question 1: You are a project owner and need your co-worker to deploy a new version of your application to App Engine. You want to follow Google’s recommended practices. Which IAM roles should you grant your co-worker?
Question 2: Your company has reserved a monthly budget for your project. You want to be informed automatically of your project spend so that you can take action when you approach the limit. What should you do?
A. Link a credit card with a monthly limit equal to your budget.
B. Create a budget alert for 50%, 90%, and 100% of your total monthly budget.
C. In App Engine Settings, set a daily budget at the rate of 1/30 of your monthly budget.
D. In the GCP Console, configure billing export to BigQuery. Create a saved view that queries your total spend.
Question 3: You have a project using BigQuery. You want to list all BigQuery jobs for that project. You want to set this project as the default for the bq command-line tool. What should you do?
A. Use “gcloud config set project” to set the default project.
B. Use “bq config set project” to set the default project.
C. Use “gcloud generate config-url” to generate a URL to the Google Cloud Platform Console to set the default project.
D. Use “bq generate config-url” to generate a URL to the Google Cloud Platform Console to set the default project.
Question 4: Your project has all its Compute Engine resources in the europe-west1 region. You want to set europe-west1 as the default region for gcloud commands. What should you do?
A. Use Cloud Shell instead of the command line interface of your device. Launch Cloud Shell after you navigate to a resource in the europe-west1 region. The europe-west1 region will automatically become the default region.
B. Use “gcloud config set compute/region europe-west1” to set the default region for future gcloud commands.
C. Use “gcloud config set compute/zone europe-west1” to set the default region for future gcloud commands.
D. Create a VPN from on-premises to a subnet in europe-west1, and use that connection when executing gcloud commands.
Question 5: You developed a new application for App Engine and are ready to deploy it to production. You need to estimate the costs of running your application on Google Cloud Platform as accurately as possible. What should you do?
A. Create a YAML file with the expected usage. Pass this file to the “gcloud app estimate” command to get an accurate estimation.
B. Multiply the costs of your application when it was in development by the number of expected users to get an accurate estimation.
C. Use the pricing calculator for App Engine to get an accurate estimation of the expected charges.
D. Create a ticket with Google Cloud Billing Support to get an accurate estimation.
Question 6: Your company processes high volumes of IoT data that are time-stamped. The total data volume can be several petabytes. The data needs to be written and changed at a high speed. You want to use the most performant storage option for your data. Which product should you use?
A. Cloud Datastore
B. Cloud Storage
C. Cloud Bigtable
D. BigQuery
ANSWER 6:
C
Notes/Hint 6:
Cloud Bigtable is the most performant storage option to work with IoT and time series data.
Question 7: Your application has a large international audience and runs stateless virtual machines within a managed instance group across multiple locations. One feature of the application lets users upload files and share them with other users. Files must be available for 30 days; after that, they are removed from the system entirely. Which storage solution should you choose?
A. A Cloud Datastore database.
B. A multi-regional Cloud Storage bucket.
C. Persistent SSD on virtual machine instances.
D. A managed instance group of Filestore servers.
ANSWER 7:
B
Notes/Hint 7:
Buckets can be multi-regional and have lifecycle management.
Question 8: You have a definition for an instance template that contains a web application. You are asked to deploy the application so that it can scale based on the HTTP traffic it receives. What should you do?
A. Create a VM from the instance template. Create a custom image from the VM’s disk. Export the image to Cloud Storage. Create an HTTP load balancer and add the Cloud Storage bucket as its backend service.
B. Create a VM from the instance template. Create an App Engine application in Automatic Scaling mode that forwards all traffic to the VM.
C. Create a managed instance group based on the instance template. Configure autoscaling based on HTTP traffic and configure the instance group as the backend service of an HTTP load balancer.
D. Create the necessary amount of instances required for peak user traffic based on the instance template. Create an unmanaged instance group and add the instances to that instance group. Configure the instance group as the Backend Service of an HTTP load balancer.
Question 9: You are creating a Kubernetes Engine cluster to deploy multiple pods inside the cluster. All container logs must be stored in BigQuery for later analysis. You want to follow Google-recommended practices. Which two approaches can you take?
A. Turn on Stackdriver Logging during the Kubernetes Engine cluster creation.
B. Turn on Stackdriver Monitoring during the Kubernetes Engine cluster creation.
C. Develop a custom add-on that uses Cloud Logging API and BigQuery API. Deploy the add-on to your Kubernetes Engine cluster.
D. Use the Stackdriver Logging export feature to create a sink to Cloud Storage. Create a Cloud Dataflow job that imports log files from Cloud Storage to BigQuery.
E. Use the Stackdriver Logging export feature to create a sink to BigQuery. Specify a filter expression to export log records related to your Kubernetes Engine cluster only.
Answer 9:
A and E
Notes/Hint 9:
Creating a cluster with Stackdriver Logging option will enable all the container logs to be stored in Stackdriver Logging.
Question 10: You need to create a new Kubernetes Cluster on Google Cloud Platform that can autoscale the number of worker nodes. What should you do?
A. Create a cluster on Kubernetes Engine and enable autoscaling on Kubernetes Engine.
B. Create a cluster on Kubernetes Engine and enable autoscaling on the instance group of the cluster.
C. Configure a Compute Engine instance as a worker and add it to an unmanaged instance group. Add a load balancer to the instance group and rely on the load balancer to create additional Compute Engine instances when needed.
D. Create Compute Engine instances for the workers and the master, and install Kubernetes. Rely on Kubernetes to create additional Compute Engine instances when needed.
Question 11: You have an application server running on Compute Engine in the europe-west1-d zone. You need to ensure high availability and replicate the server to the europe-west2-c zone using the fewest steps possible. What should you do?
A. Create a snapshot from the disk. Create a disk from the snapshot in the europe-west2-c zone. Create a new VM with that disk.
B. Create a snapshot from the disk. Create a disk from the snapshot in the europe-west1-d zone and then move the disk to europe-west2-c. Create a new VM with that disk.
C. Use “gcloud” to copy the disk to the europe-west2-c zone. Create a new VM with that disk.
D. Use “gcloud compute instances move” with parameter “–destination-zone europe-west2-c” to move the instance to the new zone.
Answer 11:
A
Notes/Hint 11:
This makes sure the VM gets replicated in the new zone.
Question 12: Your company has a mission-critical application that serves users globally. You need to select a transactional, relational data storage system for this application. Which two products should you consider
A. BigQuery
B. Cloud SQL
C. Cloud Spanner
D. Cloud Bigtable
E. Cloud Datastore
Answer 12:
B
Notes/Hint 12:
Cloud SQL is a relational and transactional database in the list.
Spanner is a relational and transactional database in the list.
Question 13: You have a Kubernetes cluster with 1 node-pool. The cluster receives a lot of traffic and needs to grow. You decide to add a node. What should you do?
A. Use “gcloud container clusters resize” with the desired number of nodes.
B. Use “kubectl container clusters resize” with the desired number of nodes.
C. Edit the managed instance group of the cluster and increase the number of VMs by 1.
D. Edit the managed instance group of the cluster and enable autoscaling.
Answer 13:
A
Notes/Hint 13:
This resizes the cluster to the desired number of nodes.
Question 14: You created an update for your application on App Engine. You want to deploy the update without impacting your users. You want to be able to roll back as quickly as possible if it fails. What should you do?
A. Delete the current version of your application. Deploy the update using the same version identifier as the deleted version.
B. Notify your users of an upcoming maintenance window. Deploy the update in that maintenance window.
C. Deploy the update as the same version that is currently running.
D. Deploy the update as a new version. Migrate traffic from the current version to the new version.
Question 15: You have created a Kubernetes deployment, called Deployment-A, with 3 replicas on your cluster. Another deployment, called Deployment-B, needs access to Deployment-A. You cannot expose Deployment-A outside of the cluster. What should you do?
A. Create a Service of type NodePort for Deployment A and an Ingress Resource for that Service. Have Deployment B use the Ingress IP address.
B. Create a Service of type LoadBalancer for Deployment A. Have Deployment B use the Service IP address.
C. Create a Service of type LoadBalancer for Deployment A and an Ingress Resource for that Service. Have Deployment B use the Ingress IP address.
D. Create a Service of type ClusterIP for Deployment A. Have Deployment B use the Service IP address.
Question 18: You want to create a new role for your colleagues that will apply to all current and future projects created in your organization. The role should have the permissions of the BigQuery Job User and Cloud Bigtable User roles. You want to follow Google’s recommended practices. How should you create the new role?
A. Use “gcloud iam combine-roles –global” to combine the 2 roles into a new custom role.
B. For one of your projects, in the Google Cloud Platform Console under Roles, select both roles and combine them into a new custom role. Use “gcloud iam promote-role” to promote the role from a project role to an organization role.
C. For all projects, in the Google Cloud Platform Console under Roles, select both roles and combine them into a new custom role.
D. For your organization, in the Google Cloud Platform Console under Roles, select both roles and combine them into a new custom role.
Answer 18:
D
Notes/Hint 18:
D is correct because this creates a new role with the combined permissions on the organization level.
Question 19: You work in a small company where everyone should be able to view all resources of a specific project. You want to grant them access following Google’s recommended practices. What should you do?
A. Create a script that uses “gcloud projects add-iam-policy-binding” for all users’ email addresses and the Project Viewer role.
B. Create a script that uses “gcloud iam roles create” for all users’ email addresses and the Project Viewer role.
C. Create a new Google Group and add all users to the group. Use “gcloud projects add-iam-policy-binding” with the Project Viewer role and Group email address.
D. Create a new Google Group and add all members to the group. Use “gcloud iam roles create” with the Project Viewer role and Group email address.
Question 21: Your coworker created a deployment for your application container. You can see the deployment under Workloads in the console. They’re out for the rest of the week, and your boss needs you to complete the setup by exposing the workload. What’s the easiest way to do that?
A. Create a new Service that points to the existing deployment.
B. Create a new DaemonSet.
C. Create a Global Load Balancer that points to the pod in the deployment.
D. Create a Static IP Address Resource for the Deployment.
Question 22: Your team is working on designing an IoT solution. There are thousands of devices that need to send periodic time series data for processing. Which services should be used to ingest and store the data?
A. Pub/Sub, Datastore
B. Pub/Sub, Dataproc
C. Dataproc, Bigtable
D. Pub/Sub, Bigtable
Answer 22:
D
Notes/Hint 22:
Pub/Sub is able to handle the ingestion, and Bigtable is a great solution for time series data.
Question 23: You have an App Engine application running in us-east1. You’ve noticed 90% of your traffic comes from the West Coast. You’d like to change the region. What’s the best way to change the App Engine region?
A. Use the gcloud app region set command and supply the name of the new region.
B. Contact Google Cloud Support and request the change.
C. From the console, under the App Engine page, click edit, and change the region drop-down.
D. Create a new project and create an App Engine instance in us-west2.
Question 24: You’ve uploaded some static web assets to a public storage bucket for the developers. However, they’re not able to see them in the browser due to what they called “CORS errors”. What’s the easiest way to resolve the errors for the developers?
A. Advise the developers to adjust the CORS configuration inside their code.
B. Use the gsutil cors set command to set the CORS configuration on the bucket.
C. Use the gsutil set cors command to set the CORS configuration on the bucket.
D. Use the gsutil set cors command to set the CORS configuration on the object.
Answer 24:
B
Notes/Hint 24:
CORS settings are made to a bucket, not an object.. You can set the CORS configuration on the bucket allowing the objects to be viewable from the required domains.
Question 25: You’ve uploaded some PDFs to a public bucket. When users browse to the documents, they’re downloaded rather than viewed in the browser. How can we ensure that the PDFs are viewed in the browser?
A. This is a browser setting and not something that can be changed.
B. Use the gsutil set file-type pdfcommand.
C. Set the Content metadata for the object to “application/pdf”.
D. Set the Content-Type metadata for the object to “application/pdf”.
Question 26: You’ve been tasked with getting all of your team’s public SSH keys onto all of the instances of a particular project. You’ve collected them all. With the fewest steps possible, what is the simplest way to get the keys deployed?
A. Use the gcloud compute ssh command to upload all the keys
B. Format all of the keys as needed and then, using the user interface, upload each key one at a time.
C. Add all of the keys into a file that’s formatted according to the requirements. Use the gcloud compute project-info add-metadata command to upload the keys.
D. Add all of the keys into a file that’s formatted according to the requirements. Use the gcloud compute instances add-metadata command to upload the keys to each instance
Answer 26:
C
Notes/Hint 26:
This will upload the keys as project metadata which allows SSH access to the user's with uploaded keys
Question 30: Your security team has been reluctant to move to the cloud because they don’t have the level of network visibility they’re used to. Which feature might help them to gain insights into your Google Cloud network?
A. Routes
B. Subnets
C. Flow Logs
D. Firewall rules
Answer 30:
C
Notes/Hint 30:
Flow logs are great for gaining insights into what's happening on a network. They provide a sample of the flows to and from instances.
Question 31: You’re in charge of setting up a Stackdriver account to monitor 3 separate projects. Which of the following is a Google best practice?
A. Use the existing project with the least resources as the host project for the Stackdriver account.
B. Use the existing project with the most resources as the host project for the Stackdriver account.
C. Create a new, empty project to use as the host project for the Stackdriver account.
D. Use one of the existing projects as the host project for the Stackdriver account.
Question 32: You’re attempting to set up a File based Billing Export. Which of the following components are required?
A. A Cloud Storage bucket.
B. A BigQuery dataset.
C. A report prefix.
D. A Budget and at least one alert.
Answer 32:
A and C
Notes/Hint 32:
A cloud storage bucket is required in order to have a location for the files to be exported to. A report prefix is the portion of the file name that's appended to each file.
Question 33: You’ve installed the Google Cloud SDK natively on your Mac. You’d like to install the kubectl component via the Google Cloud SDK. Which command would accomplish this?
A. sudo apt-get install kubectl
B. gcloud components install kubectl
C. pip install kubectl
D. brew install kubectl
Answer 33:
B
Notes/Hint 33:
For Windows and Mac, you can use the built-in component manager.
Question 34: You’re attempting to set the default Compute Engine zone with the Cloud SDK. Which of the following commands would work?
A. gcloud config set compute/zone us-east1-c
B. gcloud set compute\zone us-east1
C. gcloud set compute/zone us-east1
D. gcloud config set compute\zone us-east1
Answer 34:
A
Notes/Hint 34:
gcloud config set compute/zone us-east1-c works perfectly
Question 35: You’ve been hired as a Cloud Engineer for a 2-year-old startup company. Recently they’ve had a bit of turn over, and several engineers have left the company to pursue different projects. Shortly after one of them leaves, it is found that a core project seems to have been deleted. What is the most likely cause for of the project’s deletion?
A. You’ve been the victim of the latest malware that deletes one project per hour until you pay them to stop.
B. One of the engineers intentionally deleted the project out of spite.
C. The project was created by one of the engineers and not attached to the organization.
D. A failed attempt to pay the bill resulted in Google deleting the project.
Question 36: You’re using Stackdriver to set up some alerts. You want to reuse your existing REST-based notification tools that your ops team has created. You want the setup to be as simple as possible to configure and maintain. Which notification option would be the best option?
A. Use a Slack bot to listen for messages posted by Google.
B. Send it to an email account that is being polled by a custom process that can handle the notification.
C. Send notifications via SMS and use a custom app to forward them to the REST API.
D. Webhooks
Answer 36:
D
Notes/Hint 36:
Webhooks would allow you to easily send the notification to an HTTP(S) endpoint. Given the above scenario, this is the best option for something custom.
Question 37: A member of the finance team informed you that one of the projects is using the old billing account. What steps should you take to resolve the problem?
A. Submit a support ticket requesting the change.
B. Go to the Billing page, locate the list of projects, find the project in question and select Change billing account. Then select the correct billing account and save.
C. Go to the Project page; expand the Billing tile; select the Billing Account option; select the correct billing account and save.
D. Delete the project and recreate it with the correct billing account.
Answer 37:
B
Notes/Hint 37:
Go to the Billing page, locate the list of projects, find the project in question and select Change billing account. Then select the correct billing account and save.
Question 38: You’re using a self-serve Billing Account to pay for your 2 projects. Your billing threshold is set to $1000.00 and between the two projects you’re spending roughly 50 dollars per day. It has been 18 days since you were last charged.Given the above data, when will you likely be charged next?
A. On the first day of the next month.
B. In 2 days when you’ll hit your billing threshold.
C. On the thirtieth day of the month.
D. In 12 days, making it 30 days since the previous payment.
Answer 38:
B
Notes/Hint 38:
With Self-serve, you pay when you hit the billing threshold or every 30 days; whichever happens first. Given the scenario assumes $50 per day, you'll hit the spending threshold in 2 more days.
Question 39: You have 3 Cloud Storage buckets that all store sensitive data. Which grantees should you audit to ensure that these buckets are not public?
A. allUsers
B. allAuthenticatedUsers
C. publicUsers
D. allUsers and allAuthenticatedUsers
Answer 39:
D
Notes/Hint 39:
Either of these tokens represents public users. allAuthenticatedUsers represents a user with a Google account. They don't need to be part of your organization. Neither token should be used to grant permissions unless the bucket is truly public.
Question 40: You’ve been asked to help onboard a new member of the big-data team. They need full access to BigQuery. Which type of role would be the most efficient to set up while following the principle of least privilege?
A. Primitive Role
B. Custom Role
C. Managed Role
D. Predefined Role
Answer 40:
D
Notes/Hint 40:
Predefined roles would work great for this use case because they're specific to resources. BigQuery has several predefined roles including a “BigQuery Admin” role.
Yes, Google App Engine(GAE) , a fully managed PaaS is 100% worthy if :
you want ready and quick platform to build web applications and mobile backends on Cloud scale with very low cost start
want to get rid of the burden managing and provisioning Infrastructure, application security and scale
are fine with almost no control over web server and application software like Database, File storage, Messaging mechanism. You have to live with what GAE offers and choose from choices available. Forget about customization!
can live with fixed set of language runtimes like Node.js, Java, Ruby, C#, Go, Python, ….
Google App Engine is PaaS platform (Platform as a service) that is used to deploy large-scale web and mobile apps. So, the sites are:Disney
Snapchat, YouTube, Accenture, Practo, Samba Tech, Buddy, Kam Bam, Coco Cola, The New York Times, Stack
It is one of the most trusted cloud platform used by top companies. We will get to see many more sites deploying Google App Engine for their web & app hosting.
Well, I believe it because I met and discussed it with some of the Google engineers responsible for that area. And I am not special in that respect: it’s not a secret. Here’s the missing link: Google runs KVM in a container. To be crystal clear, a container is not an actual Linux construct. There is no Linux system call you can make to create a container. Instead, it is the term we give to the usage of Linux primitives like namespaces and cgroups to partition applications into their own Linux-level virtual compute space. Except we don’t call it that, we call it a container. So, at the lowest level, Google’s infrastructure schedules containers. To create a virtual machine, google runs KVM in one of those containers. So the document you link to is absolutely valid *and* KVM runs in a containe(more)
No, but to be honest, I think that’s what their gaming system is for. Reverse marketing. They don’t expect it to be a hit, but if they’re almost good enough for gaming, then they’re certainly good enough for me. They’re not aiming for gamers, but everyone else. There is definitely a market for public VDI. I was working on that concept ten years ago, but I didn’t have the resources to pull it off. Back then, watching Youtube videos on the client was not feasible. These days, you could probably kill the whole PC industry if you had the resources. If Google develops something like JackPC that is able to connect to their Stadia and provide a VM, I would recommend it to my father, but I wouldn’t use it, because I still have a long life to live and I’m not giving it to Google. But if they made i(more)
Google runs Linux on its hardware (AKA “Linux on bare metal”). As part of that Linux image, it has its own Linux container implementation based on cgroups and namespaces. In Google Cloud platform, it then runs KVM inside a Linux container, and the VMs run on top of KVM. So the hierarchy is VM->KVM->Linux->Bare metal(more)
i would suggest you to read this document thoroughly, so that you can understand logging into Compute instances is not that tedious… 🙂 Connecting to instances using advanced methods | Compute Engine Documentation | Google Cloud(more)
Lets have two variables (although they can be more): ease of administration, constraints of use. App Engine: from your side there is almost no administration, you write code (with somewhat limited possibilities), upload and basically don’t have other major concerns (well maybe how to lower your bills if your app gets popular)) all the rest (storage, scaling, installing programs etc.) handles app engine Compute Engine is virtual machine with preinstalled OS and you can do with it whatever you want. That means you have to install all programs by yourself but you are not limited with what can you do with it. Container Engine is another level above Compute Engine, i.e. it’s cluster of several Compute Engine instances which can be centrally managed. There is also one level between GAE and GCE:(more)
Both of them have almost the same price but they have different type of discounts. For instance AWS has “Reserved Instance” discount model for 1 or 3 year purchase. You have to pay almost 1/3 of the period as pre-paid and you’ll get %30–60 discounts depends on period you choose and EC2 instance type you have. Google Cloud has a monthly discount model and it applies automatically if you use a compute engine more than 10 days in a month. If you run the compute instance during the month you may have %30 discount without pre-pay anything. So both of them have discounts but in a different financial payment model. As an alternative, you can checkout DigitalOcean for the affordable prices.(more)
They’re three different approaches to running services on virtual machines. AppEngine is designed around automatic scaling of services. There’s actually two different flavors of AppEngine entirely : the “standard environment,” which is a sandbox, and the “flexible environment,” which is a more traditional (though still not traditional!) VM running in a Docker container. Both versions are designed to automatically spawn more instances of your service in response to increases in load, and isolate you from a lot of hard SRE problems. Compute Engine is just plain old virtual machines. If you want to run an instance of a VM with a certain amount of memory and hard drive space, running under a given version of Linux, and not have to worry about physical equipment, Compute Engine is for you. (Mor(more)
I do not understand why the question asks about both EC2/Compute Engine and Cloud-Storage/S3. Cloud-Storage/S3 is used to serve static websites. The EC2/computer engine is typically used to serve dynamic content (However, it can serve static websites too). I would try and figure out which one of these suits your use better. In both the cases, however, GCP is cheaper (You also get credits to use it free for one year) – they even have a page where you can calculate how much you save moving from AWS to GC → Google Cloud Platform Pricing Calculator | Google Cloud Platform | Google Cloud (The only case where I have seen GCP is more expensive is when it comes to hosting proprietary licensed DBs like MS SQL).(more)
We started offering our hadoop service on GCE. We ran hadoop workloads with a root persistent disk(storage over network) and an additional persistent disk of size 500 GB. Consistently, we observed that the performance is better than other leading cloud providers where we used local disks of the instance. Few months back, GCE was offering scratch disks. They decided to replace scratch disks with persistent disk when they went GA. This fact clearly shows that there was enough confidence, that persistent disks were performing well compared to scratch disks. (if thats not the case, Google would not have made this bold move and continued offering scratch disks also like AWS) This performance must partly be attributed to their networking stack. Its considered the best out there in the(more)
Google has been building and using its own private cloud since the start of the company. They have always been known for about setting the standards in many industries, and public cloud is what happening. For years, people would always wanted to use their cloud technology (Colossus, BigTable, GAE, etc..). Strategically, Google knows that if they focus more on providing and marketing their public cloud based on what they currently use, people who look up to them would see it as standard, and it’s all good for business. Another reason is, with recent acquisitions (for instance, Nest), Google realized that those successful startups they acquire use AWS more than GCP. Telling the existing development teams to migrate to GCP will disrupt the team (just like Microsoft’s acquisition of Minecraft(more)
I strongly suggest to move your installation to google app engine instead. It’s easy, it will leverage your maintenance costs, and it will auto scale when needed. As for cdn, you can host static files on google storage that is already managed with google cdn behind the scene. To go with WordPress on google app engine there are simple tutorials like this: GoogleCloudPlatform/php-docs-samples I did this setup many times with great success. I also wrote a small tutorial to speed up your wp installation with memcache (that comes as a free service in google app engine). giona69/wordpress-made-extremely-fast Good work!(more)
I just want to explain in a way that a person who don’t have any prior knowledge on containers and clusters should be able to understand what kubernetes is and what it does. First we understand why container. * Let’s say you want to gift a cycle to your kid on his birthday. Now if the cycle is delivered to you with parts separated and a manual that describes how to attach the parts. Well you may end up screwing things. * Instead what if the cycle itself is ready-made and packed in a container and delivered to your home address, with no manual intervention required? . Ain’t that awesome. * * The individual parts of cycle is the dependencies of the project which may work at one place and not the other. * * The cycle company is the developers hub, and the client here is the one using our product. * * To solve thi(more)
Indeed Kubernetes and Docker are two different things that are related to each other. Let’s have a look; After getting used to Docker, you realize that there should be ‘Docker run’ commands or something like that to run many containers across heterogeneous hosts. Here is when Kubernetes or k8s comes in. It solved many problems that Docker had. Kubernetes is based on Google’s container management system- Borg and language used is Go. It is a COE (Container Orchestration Environment) for Docker containers. The function of COE is to make it sure that application is launched and running properly. If in case a container fails, Kubernetes will spin up another container. It provides a complete system for running so many containers across multiple hosts. It has load balancer integrated and uses etc(more)
Kubernetes is a vendor-agnostic cluster and container management tool, open-sourced by Google in 2014. It provides a “platform for automating deployment, scaling, and operations of application containers across clusters of hosts”. Above all, this lowers the cost of cloud computing expenses and simplifies operations and architecture. Kubernetes and the Need for Containers Before we explain what Kubernetes does, we need to explain what containers are and why people are using those. A container is a mini-virtual machine. It is small, as it does not have device drivers and all the other components of a regular virtual machine. Docker is by far the most popular container and it is written in Linux. Microsoft also has added containers to Windows as well, because they have become so popular. The bes(more)
Despite the little time that Kubernetes has in the market, this tool has become a reference in terms of the management and allocation of service packages (containers) within a cluster. Initially developed by Google, Kubernetes emerged as an open-source alternative to the Borg and Omega systems, being officially launched in 2015. What is Kubernetes? Kubernetes is an open-source tool also designated as an orchestrator, which is used to carry out the distribution and organization of workloads in the form of containers. This, in order to maintain the availability and accessibility of existing resources to customers, as well as stability when carrying out the execution of multiple services simultaneously. Through this action scheme, Kubernetes makes it possible for numerous servers of different typ(more)
There are a countless number of debates, discussions and social clatter talking about Kubernetes and Docker. Nevertheless, Kubernetes and Docker Swarm are not rivals! Both have their own pros and cons and can be used depending on your application requirements. Benefits & drawbacks of Kubernetes Benefits of Kubernetes: * Kubernetes is backed by the Cloud Native Computing Foundation (CNCF). * Kubernetes have an impressively huge community among container orchestration tools. Over 50,000 commits and 1200 contributors. * Kubernetes is an open source and modular tool that works with any OS. * Kubernetes provides easy service organization with pods (Start your Kubernetes journey to resilient and highly available deployments – Free consultation on Kubernetes) Drawbacks of Kubernetes * When doing it yourself, K(more)
If you already ‘know’ Docker containers, then spin up a Kubernetes system (Not as hard as you think – check out installing Minikube) read through the docs for Kubernetes and start trying out some of the capabilities for yourself. The (free) Katacoda is a browser-based learning platform has a number of ‘scenarios’ that run on pre-deployed Kubernetes system. Follow this link to Katacoda and then search for “Kubernetes.” Note that you can copy-paste your way through most of the exercises in a minute or two, learning is on you to read and understand what it is you are pasting. Online resources such as the “Awesome Kubernetes” or “Awesome Docker” lists (you do need to have some understanding of Docker to work with Kubernetes) will give you a pile of options – free and paid – to get into greater(more)
When Linux containers appeared at the time of LXC, a lot of people in the IT world saw them as something marvelous, they offered a way of packaging software with all their dependencies and running then in any other Linux machine. Much like virtual machines, but without the performance losses. But the truth was that they weren’t widely used, they required some plumbing to make them work, and there were no standard way to distribute the images. Then docker appeared, adding to existing container technologies a workflow for building and sharing images and a common interface to start containers. This came to popularize these technologies, but they weren’t still widely used for production systems, mainly because it was not so advantageus to have just another packaging system for production. And t(more)
There is no one way to compare because they are mostly different things. That said, I’ll first try and define the need for each one of these and link them together. Let’s start with the bottom of the stack. You need infrastructure to run your servers. What could you go with? You can use a VPS provider like DigitalOcean, or use AWS. What if, for some non-technical reason, you can’t use AWS? For instance, there is a legal compliance that states that the data I store and servers I run are in the same geography as the customers I serve, and AWS does not have a region for the same? This is where OpenStack comes in. It is a platform to manage your infrastructure. Think of it as an open source implementation of AWS which you can run on bare metal data centers. Next, we move up the stack. We want an(more)
Kubernetes (also known as K8s) is a production-grade container orchestration system. It is an open source cluster management system initially developed by three Google employees during the summer of 2014 and grew exponentially and became the first project to get donated to the Cloud Native Computing Foundation(CNCF). It is basically an open source toolkit for building a fault-tolerant, scalable platform designed to automate and centrally manage containerized applications. With Kubernetes you can manage your containerized application more efficiently. Kubernetes is a HUGE project with a lot of code and functionalities. The primary responsibility of Kubernetes is container orchestration. That means making sure that all the containers that execute various workloads are sc(more)
The basic idea of Kubernetes is to further abstract machines, storage, and networks away from their physical implementation. So it is a single interface to deploy containers to all kinds of clouds, virtual machines, and physical machines. Container Orchestration & Kubernetes Containers are virtual machines. They are lightweight, scalable, and isolated. The containers are linked together for setting security policies, limiting resource utilization, etc. If your application infrastructure is similar to the image shared below, then container orchestration is necessary. It might be Nginx/Apache + PHP/Python/Ruby/Node.js app running on a few containers, communicating with the replicated database. Container orchestration wi(more)
As seen in the following diagram, Kubernetes follows client-server architecture. Wherein, we have master installed on one machine and the node on separate Linux machines. The key components of master and node are defined in the following section. Kubernetes – Master Machine Components Following are the components of Kubernetes Master Machine. etcd It stores the configuration information which can be used by each of the nodes in the cluster. It is a high availability key value store that can be distributed among multiple nodes. It is accessible only by Kubernetes API server as it may have some sensitive information. It is a distributed key value Store which is accessible to all. API Server Kubernetes is an API server which provides all the operation on cluster usi(more)
Kubernetes service discovery find services through two approaches: 1. Using the environment variables that use the same conventions as those created by Docker links. 2. Using DNS to resolve the service names to the service’s IP address. Environment Variables Kubernetes injects environment variables for each service and each port exposed by the service. This makes it easy to deploy containers that use Docker links to find their dependencies. For example, if we are exposing a RabbitMQ service, we can locate it using the RABBITMQ_SERVICE_SERVICE_HOST and RABBIT_MP_SERVICE_SERVICE_PORTvariables. Other environment variables are also exposed to support this. The easiest way to find out what environment variables are exposed are(more)
Docker is open source tool has been designed to create applications as small container on any machine. By using docker development , deployment is too easy is for developers . We can say this are very light-weight in size which includes minimal OS and your application . In a way, Docker is a bit like a virtual machine. But unlike a virtual machine, rather than creating a whole virtual operating system, Docker allows applications to use the same Linux kernel as the system that they’re running on and only requires applications be shipped with things not already running on the host computer. This gives a significant performance boost and reduces the size of the application. Kubernets : Kubernetes is a powerful system, developed by Google, for managing containerized applications in a clustered e(more)
Container cluster management system is called Kubernetes. After getting used to Docker, you realize that there should be ‘Docker run’ commands or something like that to run many containers across heterogeneous hosts. Here is when Kubernetes comes in. It provides a complete system for running different containers across multiple hosts. Kubernetes is based on Google container management system Borg and language used is Go.Basically, Google uses three languages; 1. C/C++ 2. Java 3. Python C and C++ might be little tough for new users. Java is less attractive as compared to Go for Kubernetes because of its heavy runtime download. Python is great but dynamic typing of Python is challenging for system software. Go is the best choice as it has great sets of system libraries. It has fast testing and building too(more)
Hi there, I believe container orchestration is one of the best features of Kubernetes. I will tell you why? I am sharing a section of my recently posted article on Level Up. For complete article, please visit : The Kubernetes Bible for Beginners & Developers – Level Up So here is my answer : How Kubernetes Solves the Problem? After discussing the deployment part of Kubernetes, it is necessary to understand the importance of Kubernetes. Container Orchestration & Kubernetes Containers are virtual machines. They are lightweight, scalable, and isolated. The containers are linked together for setting security policies, limiting resource utilization, etc. If your application infrastructure is similar to the image shared below, then container orchestration is necessary. It might be Nginx/Apache + PHP/(more)
Hi, I found this cheat sheet on Kubernetes. Kubernetes kubectl CLI Cheat Sheet This cheat sheet encloses first-aid commands to configure the CLI, manage a cluster, and gather information from it. On downloading the cheat sheet, you will find out how to:Create, group, update, and delete cluster resources Debug Kubernetes pods—a group of one or more containers with shared storage/network and a specification for running the containers Manage config maps, a primitive to store a pod’s configuration, and secrets, a primitive to store such sensitive data as passwords, keys, certificates, etc. You will learn how to use Helm—a package manager to define, install, and upgrade complex Kubernetes apps. Moreover, here you can find the Kubernetes training courses – Custom Hands-On IT Training Courses… Plus -(more)
Both Kubernetes and Docker are DevOps tools. Docker was started in 2013 and is developed by Docker, Inc. Kubernetes was introduced as a project at Google in 2014, and it was a successor of Google Borg. Kubernetes can run without docker, and docker can run without kubernetes. But kubernetes has great benefits in running along with docker. What is Kubernetes Kubernetes is a container management system developed by Google. It is an open-source, portable system for automatic container deployment and management. It eliminates many of the manual processes involved in deploying and scaling containerized applications. In practice, Kubernetes is most commonly used alongside Docker for better control and implementation of containerized applications. Features of Kubernetes * Automates various manual proces(more)
Yes and no. Especially for Kubernetes (which is not THAT hard, but has a steep learning curve in the beginning), I doubt that there is any certification that can tell you stuff you cannot learn for free. You can set up a Kubernetes cluster on DO for $20/month or even on you laptop to actually try out things. Create a few Helm charts for your pet applications and you have a good working knowledge of Kubernetes. BUT: How can an employer judge your level of knowledge? And this is where certifications get interesting. So basically, you are trading money for an increased chance of employment, all other things equal. Furthermore, at a certain size of projects, customers require their suppliers to have a certain number of people certified in the relevant technologies — so that they can rest assure(more)
This is a good question. I would like to say that Borg and Kubernetes both have the same kind of tasks. But Google is promoting Kubernetes for now. As such, it offering good features as well. The most important thing of all, Kubernetes has an active online community. The members of this community meet-up online as well as in person, in major cities of the world. An international conference “KubeCon” has proved to be a huge success. There is also an official Slack group for Kubernetes. Major cloud providers like Google Cloud Platform, AWS, Azure, DigitalOcean, etc also offer their support channels. For more details on Kubernetes, please visit my articles : https://www.level-up.one/kubernetes-bible-beginners/ How Does The Kubernetes Networking Work? : Part 1 – Level Up How Does The Kubernetes Ne(more)
Kubernetes is infrastructure abstraction for container manipulation. In Kubernetes there are many terms that conceptualize the execution environment. A pod is the smallest unit deployable in kubernetes. You can see it as an application that runs one container or multiple that work together. Pods have volumes, memory and networking requirements. Pods have a unique Id and can die at any minute so kubernetes provides a higher hierarchy abstraction called Service. A Service is a logical set of pods that are permanent in the cluster and offer functionality. Pods are accesible through the service names in the network of the cluster. When a pod dies, kubernetes automatically runs a new pod of the service (depending on replica configuration) to keep the service offering functionality. There are man(more)
Kubernetes’ increased adoption is showcased by a number of influential companies which have integrated the technology into their services. Let us take a look at how some of the most successful companies of our time are successfully using Kubernetes. Tinder’s move to Kubernetes Due to high traffic volume, Tinder’s engineering team faced challenges of scale and stability. What did they do? Kubernetes – Yes, the answer is Kubernetes. Tinder’s engineering team solved interesting challenges to migrate 200 services and run a Kubernetes cluster at scale totaling 1,000 nodes, 15,000 pods, and 48,000 running containers. Reddit’s Kubernetes story Reddit is one of the top busiest sites in the world. Kubernetes forms the core of Reddit’s internal Infrastructure. From many years, the Reddit infrastructure tea(more)
Here is a way you could convince him. Docker is dead. It’s not technically dead, but in reality, it’s a walking zombie. I’ll explain why. AWS is one of the best platforms for infrastructure and there is GCE and Azure, but AWS is the standard, the most capable platform from all the cloud architectures. AWS is integrating Kubernetes into it’s system and you might ask what are the benefits and why would it do that. Kubernetes is basically a competitor to AWS. It allows you to write infrastructure using YAML files and deploy them on a cluster. The only drawback right now is that you cannot provision servers using Kubernetes because it sits at a higher level in the abstraction stack. The servers are below it. However, with EKS (elastic kubernetes service). AWS has integrated all sorts of primativ(more)
If the developer put together a working solution then keep using it, thank them for the effort, and provide some private coaching on how to get buy-in so things go more smoothly in the future. Startups spawn serious problems that don’t end up on the roadmap as they should, and you’re better off with people taking initiative then fixing them. Otherwise the stake holders need to decide on a containerization solution, preferably coming to that conclusion by themselves or at least believing they did. That’s probably Kubernetes (from Google which knows how to build and run things) and docker where you already have one enthusiastic engineer willing to own the project, although they should be able to provide reasonable arguments on why that’s the best option for containerization and deployment. Peo(more)
Kubernetes is meant to simplify things and this article is meant to simplify Kubernetes for you! Kubernetes is a powerful open-source system that was developed by Google. It was developed for managing containerized applications in a clustered environment. Kubernetes has gained popularity and is becoming the new standard for deploying software in the cloud. Learning Kubernetes is not difficult (if the tutor is good) and it offers great power. The learning curve is a little steep. So let us learn Kubernetes in a simplified way. The article covers Kubernetes’ basic concepts, architecture, how it solves the problems, etc. What Is Kubernetes? Kubernetes offers or in fact, it itself is a system that is used for running and coordinating applications across numerous machines. The system manages the(more)
Kubernetes and Docker are two different tools used for DevOps. Let me explain each in brief. Kubernetes is an open-source platform used for maintaining and deploying a group of containers. In practice, Kubernetes is most commonly used alongside Docker for better control and implementation of containerized applications. Docker is a tool that is used to automate the deployment of applications in lightweight containers so that applications can work efficiently in different environments. Features of docker – Multiple containers run on the same hardware High productivity Maintains isolated applications Quick and easy configuration Differences between Kubernetes and Docker 1. In Kubernetes, applications are deployed as a combination of pods, deployments, and services. In Docker, applications are deployed i(more)
Kubernetes is built in three layers with each higher layer hiding the complexity found in a lower layer -Application Layer(Pool and Services), Kubernetes Layer and Infrastructure Layer. Pods are a part of Kubernetes layer. A pod is one or more containers controlled as a single application It encapsulates application containers, storage resources, a unique network ID and other configuration on how to run the containers A Pod represents a group of one or more application containers bundled up together and are highly scalable If a pod fails, Kubernetes automatically deploys new replicas of the pod to the cluster Pods provide two different types of shared resources -networking and storage You can also get a good understanding of content quality by watching Simplilearn’s youtube videos. Here are some(more)
Kubernetes, also sometimes called K8S (K – eight characters – S), is an open source orchestration framework for containerized applications that was born from the Google data centers.(more)
Docker, absolutely learn that first. Docker Docker is a tool designed to make it easier to create, deploy, and run applications by using containers. Containers allow a developer to package up an application with all of the parts it needs, such as libraries and other dependencies, and deploy it as one package. And here comes the race between choosing an orchestration tool : Overview of Kubernetes Kubernetes is based on years of Google’s experience of running workloads at a huge scale in production. As per Kubernetes website, “Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications.” Overview of Docker Swarm Docker swarm is Docker’s own container’s orchestration. It uses the standard Docker API and networking, making it easy to drop into(more)
A node is the smallest unit of hardware in Kubernetes, also known as a minion. It is a representation of a single machine in the cluster. It is a physical machine in a data center or virtual machine hosted on a cloud provider like Google Cloud Platform. Each node has the services required to run a pod and is managed by the master components in Kubernetes architecture. The services given by a Kubernetes Node include the container runtime(Docker), Kubelet, and Kube-proxy. To know more about Node in Kubernetes, watch this video on Kubernetes Architecture: Hope this helps!(more)
They’re both good technologies with huge opportunities and potential ahead) Docker is overhyped for its relative youth, and is really a moderate set of wrapper capabilities around the Linux kernel. Operational understanding is scarse and conflicting. Requires a lot of deep street knowledge to use effectively in production. Lots of subtle performance and reliability challenges with eg. Networking, storage. Often subtle breaking changes beteeen releases. Installing and operating Kubernetes is not for the faint of heart. Assumes you can “bring your own cluster”. Pace of change and improvement on core k8s is astounding (good and bad). Using Kubernetes is relatively white box, ie. you really need to know what’s going on under the covers to a degree especially if you’re not using GKE.(more)
Used on GCP and Physical ServersA Kubernetes cluster is a group of ‘machines’ that are either on the same network segment or set up to communicate with each other over the network with low latency, and run Kubernetes software. Kubernetes software runs as a ‘service’ or ‘daemon’ on each machine in the cluster and this causes the host machine to either act as a ‘master’ or a ‘slave’ node within the cluster. During the Kubernetes cluster set up process, the master is created first and toward the end of the install process a connection command is displayed or logged to the system. This should then be run on each additional node once the base Kubernetes software has been installed. Some ‘magic’ then takes place and the new node links up with the master node to form a logical cluster. Commands can then be run on the master node t(more)
I think containers are the model of potential delivery now. We make packaging an application with their required infrastructure much easier. Tools like Docker provide containers, but also software are needed to handle items such as replication, failures and APIs for automating deployment on multiple machines. At the beginning of 2015, the status of clustering platforms such as Kubernetes and Docker Swarm was highly unstable. We tried to use them and began with Docker Swarm. Amid the news in recent weeks, several businesses have purchased container or micro-service firms to boost their portfolio for what lies ahead. What is this a really important topic now ? Amid the news in recent weeks, several businesses have purchased container or micro-service firms to boost their portfolio for what lie(more)
Lets forget all about technical stuff, lets discuss this in a way that a non-technical guy understands. * You are owner of a building and you have 5 spots where people can enter your building and you want 5 security guards guarding the spots. All good till now. * * Now consider one of the guard was out of service for 2 hours due to some personal reasons. Now as a building owner its your responsibility to guard or employ another guard replacing the existing. Do you like to be manually interrupted from your task to look after who is out and whom to replace. * * No, no one likes to be. Now the solution could be, go to a third party vendor who provides 24*7 availability of the guards. Its the responsibility of the vendor to make 24*7 availability based on the configuration set(in this case guards guarding(more)
While researching for a project, I looked into all of the available books on Kubernetes. Here’s a quick roundup. (Feel free to suggest more!) * Golden Guide to Kubernetes Application Development This book’s for web app developers who just want a short, sharp guide to grok Kubernetes. It’s also really great for people trying to get their CKAD certification. (Disclaimer: I wrote this. Yeah, this is one of those Quora answers… but I hope it’s still useful.) * The Kubernetes Book Probably the most popular and established book on Kubernetes. It’s great for new developers trying to learn Kubernetes. The author is known for his video courses as well. * Kubernetes: Up and Running Definitely written by the most authoritative authors of any book here. Kelsey Hightower is a Google dev advocate for Kubernetes(more)
It is indeed possible to use Kubernetes with out Docker. The Kubernetes community has long recognized the problem with being tied to Docker’s quasi-proprietary (and somewhat arbitrarily developed) container runtime. Early on there was support for an alternative runtime called rkt (pronounced like rocket). However, going down the path of creating separate solutions for any and every new container runtime that might get developed would be a lot of work and a bit like reinventing the wheel for each runtime. To break free of the Docker runtime constraint, the CRI (Container Runtime Interface) that allows you to use other container runtimes (e.g. ContainerD, CRI-O, etc.). The CRI plugin is a shim sits between the Kubernetes kubelet and container runtime and acts as a universal translator. Read more…
I’m not sure how to explain Kubernetes to a 10-year-old. Yet when I’m allowed to expand to older people who are not technology savvy I can come up with an example which might resonate. It will inside my company: I will use the analogy of our call center. My company services some 2 million people, we manage their pensions and the necessary administration. Every year we send out the latest status of the pensions to the participants, and sure enough people will follow up. Many follow up online – the pension fund websites – yet there is a significant number who call or send an e-mail. We measure the amount of outstanding messages, as well as the amount of unanswered calls (I recall the service level is at 80% answered within 10 seconds). These are displayed on monitors so those who work in the(more)
Assuming a basic understanding of Docker and containers, I’ll describe the Kubernetes specifics. This is from a general user point of view. Kubelet: A process which runs on each node in the cluster. Kubelet talks to the master server and gets a list of containers to run and then runs, manages, and reports container status back to the master server. Pod: The primary unit of Kubernetes scheduling and management. A Pod is list of containers that are always run together on one node. The containers in a pod share an IP address and a network stack, but are otherwise isolated from each other. Container: A Docker container, it has an isolated process space, can expose ports, can define environment variables and a run command. Read more ….
Kubernetes has a strong feature set for microservice architectures. Things like service discovery, automatic failover, rescheduling, and support for overlay networks make it the best choice in dynamic environments with many small, frequently changing applications tied together. If your application needs to start hundreds of containers quickly and will terminate them just as quickly, then Kubernetes is a good option. The converse of this is that it is not as well designed for more static, highly efficient workloads. Containerization is great for flexibility, but doesn’t come for free. There is a performance penalty for using it, somewhere between a few to high single digit percentage penalty, depending on the type of operations. Read more ….
DATA AND ANALYTICS BigQuery: Data warehouse/analytics BigQuery BI Engine: In-memory analytics engine BigQuery ML: BigQuery model training/serving Cloud Composer: Managed workflow orchestration service Cloud Data Fusion: Graphically manage data pipelines Cloud Dataflow: Stream/batch data processing Cloud Dataprep: Visual data wrangling Cloud Dataproc: Managed Spark and Hadoop
NETWORKING Carrier Peering: Peer through a carrier Direct Peering: Peer with GCP Dedicated Interconnect: Dedicated private network connection Partner Interconnect: Connect on-prem network to VPC Cloud Armor: DDoS protection and WAF Cloud CDN: Content delivery network Cloud DNS: Programmable DNS serving Cloud Load Balancing: Multi-region load distribution/balancing Cloud NAT: Network address translation service Cloud Router: VPC/on-prem network route exchange (BGP) Cloud VPN (HA): VPN (Virtual private network connection) Network Service Tiers: Price vs performance tiering Network Telemetry: Network telemetry service Traffic Director: Service mesh traffic management Google Cloud Service Mesh: Service-aware network management Virtual Private Cloud: Software defined networking VPC Service Controls: Security perimeters for API-based services Network Intelligence Center: Network monitoring and topology
GOOGLE MAPS PLATFORM Directions API: Get directions between locations Distance Matrix API: Multi-origin/destination travel times Geocoding API: Convert address to/from coordinates Geolocation API: Derive location without GPS Maps Embed API: Display iframe embedded maps Maps JavaScript API: Dynamic web maps Maps SDK for Android: Maps for Android apps Maps SDK for iOS: Maps for iOS apps Maps Static API: Display static map images Maps SDK for Unity: Unity SDK for games Maps URLs: URL scheme for maps Places API: Rest-based Places features Places Library, Maps JS API: Places features for web Places SDK for Android: Places features for Android Places SDK for iOS: Places feature for iOS Roads API: Convert coordinates to roads Street View Static API: Static street view images Street View Service: Street view for JavaScript Time Zone API: Convert coordinates to timezone
G SUITE (WORKSPACE) PLATFORM Admin SDK: Manage G Suite resources AMP for Email: Dynamic interactive email Apps Script: Extend and automate everything Calendar API: Create and manage calendars Classroom API: Provision and manage classrooms Cloud Search: Unified search for enterprise Docs API: Create and edit documents Drive Activity API: Retrieve Google Drive activity Drive API: Read and write files Drive Picker: Drive file selection widget Email Markup: Interactive email using schema.org G Suite Add-ons: Extend G Suite apps G Suite Marketplace: Storefront for integrated applications Gmail API: Enhance Gmail Hangouts Chat Bots: Conversational bots in chat People API: Manage user’s Contacts Sheets API: Read and write spreadsheets Slides API: Create and edit presentations Task API: Search, read & update Tasks Vault API: Manage your organization’s eDiscovery
MIGRATION TO GCP BigQuery Data Transfer: Service Bulk import analytics data Cloud Data Transfer: Data migration tools/CLI Google Transfer Appliance: Rentable data transport box Migrate for Anthos: Migrate VMs to GKE containers Migrate for Compute Engine: Compute Engine migration tools Migrate from Amazon Redshift: Migrate from Redshift to BigQuery Migrate from Teradata: Migrate from Teradata to BigQuery Storage Transfer Service: Online/on-premises data transfer VM Migration: VM migration tools Cloud Foundation Toolkit: Infrastructure as Code templates
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?
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.
Tags: #AlexaSkillsKit, #MicrosoftBotFramework, #GoogleAssistant Differences: One major advantage Google gets over Alexa is that Google Assistant is available to almost all Android devices.
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).
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.
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.
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.
