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Google Professional-Cloud-Architect認定は、IT業界で高く評価されており、クラウドアーキテクトのベンチマークとして認識されています。これは、クラウドアーキテクチャでのキャリアを促進し、潜在的な雇用主に専門知識を実証したい専門家にとって貴重な資産です。この認定は、GCPでソリューションを設計および管理する候補者の能力と、クラウドアーキテクチャのベストプラクティスの理解を示しています。
Google認定プロフェッショナル - クラウドアーキテクトになるためには、候補者は厳格な試験に合格する必要があります。この試験は、クラウドソリューションアーキテクチャの設計と計画、クラウドインフラストラクチャの管理とプロビジョニング、クラウドソリューションの最適化とセキュリティ、およびクラウドソリューションの技術的およびビジネスプロセスの分析と最適化など、さまざまなクラウドアーキテクチャコンセプトの理解をテストします。
質問 # 158
TerramEarth has about 1 petabyte (PB) of vehicle testing data in a private data center. You want to move the data to Cloud Storage for your machine learning team. Currently, a 1-Gbps interconnect link is available for you. The machine learning team wants to start using the data in a month. What should you do?
- A. Configure the Storage Transfer service from Google Cloud to send the data from your data center to Cloud Storage
- B. Export files to an encrypted USB device, send the device to Google Cloud, and request an import of the data to Cloud Storage
- C. Request Transfer Appliances from Google Cloud, export the data to appliances, and return the appliances to Google Cloud.
- D. Make sure there are no other users consuming the 1 Gbps link, and use multi-thread transfer to upload the data to Cloud Storage.
正解：C
解説：
Topic 7, Mountkrik Games Case 2
Company Overview
Mountkirk Games makes online, session-based, multiplayer games for mobile platforms. They build all of their games using some server-side integration. Historically, they have used cloud providers to lease physical servers.
Due to the unexpected popularity of some of their games, they have had problems scaling their global audience, application servers, MySQL databases, and analytics tools.
Their current model is to write game statistics to files and send them through an ETL tool that loads them into a centralized MySQL database for reporting.
Solution Concept
Mountkirk Games is building a new game, which they expect to be very popular. They plan to deploy the game's backend on Google Compute Engine so they can capture streaming metrics, run intensive analytics, and take advantage of its autoscaling server environment and integrate with a managed NoSQL database.
Business Requirements
Increase to a global footprint.
Improve uptime - downtime is loss of players.
Increase efficiency of the cloud resources we use.
Reduce latency to all customers.
Technical Requirements
Requirements for Game Backend Platform
Dynamically scale up or down based on game activity.
Connect to a transactional database service to manage user profiles and game state.
Store game activity in a timeseries database service for future analysis.
As the system scales, ensure that data is not lost due to processing backlogs.
Run hardened Linux distro.
Requirements for Game Analytics Platform
Dynamically scale up or down based on game activity
Process incoming data on the fly directly from the game servers
Process data that arrives late because of slow mobile networks
Allow queries to access at least 10 TB of historical data
Process files that are regularly uploaded by users' mobile devices
Executive Statement
Our last successful game did not scale well with our previous cloud provider, resulting in lower user adoption and affecting the game's reputation. Our investors want more key performance indicators (KPIs) to evaluate the speed and stability of the game, as well as other metrics that provide deeper insight into usage patterns so we can adapt the game to target users. Additionally, our current technology stack cannot provide the scale we need, so we want to replace MySQL and move to an environment that provides autoscaling, low latency load balancing, and frees us up from managing physical servers.
質問 # 159
You have been engaged by your client to lead the migration of their application infrastructure to GCP. One of their current problems is that the on-premises high performance SAN is requiring frequent and expensive upgrades to keep up with the variety of workloads that are identified as follows: 20TB of log archives retained for legal reasons; 500 GB of VM boot/data volumes and templates; 500 GB of image thumbnails; 200 GB of customer session state data that allows customers to restart sessions even if off- line for several days.
Which of the following best reflects your recommendations for a cost-effective storage allocation?
- A. Local SSD for customer session state data. Lifecycle-managed Cloud Storage for log archives, thumbnails, and VM boot/data volumes.
- B. Memcache backed by Cloud SQL for customer session state data. Assorted local SSD-backed instances for VM boot/data volumes. Cloud Storage for log archives and thumbnails.
- C. Memcache backed by Cloud Datastore for the customer session state data. Lifecycle- managed Cloud Storage for log archives, thumbnails, and VM boot/data volumes.
- D. Memcache backed by Persistent Disk SSD storage for customer session state data. Assorted local SSD-backed instances for VM boot/data volumes. Cloud Storage for log archives and thumbnails.
正解：C
質問 # 160
You deploy your custom Java application to Google App Engine. It fails to deploy and gives you the following stack trace.
What should you do?
- A. Upload missing JAR files and redeploy your application.
- B. Digitally sign all of your JAR files and redeploy your application
正解：B
質問 # 161
For this question, refer to the TerramEarth case study. You need to implement a reliable, scalable GCP solution for the data warehouse for your company, TerramEarth. Considering the TerramEarth business and technical requirements, what should you do?
- A. Replace the existing data warehouse with BigQuery. Use table partitioning.
- B. Replace the existing data warehouse with a Compute Engine instance with 96 CPUs.
- C. Replace the existing data warehouse with a Compute Engine instance with 96 CPUs. Add an additional Compute Engine pre-emptible instance with 32 CPUs.
- D. Replace the existing data warehouse with BigQuery. Use federated data sources.
正解：D
質問 # 162
Your company acquired a healthcare startup and must retain its customers' medical information for up to 4 more years, depending on when it was created. Your corporate policy is to securely retain this data, and then delete it as soon as regulations allow.
Which approach should you take?
- A. Store the data in Cloud Storage and use lifecycle management to delete files when they expire.
- B. Store the data in Cloud Storage and run a nightly batch script that deletes all expired data.
- C. Store the data in Google Drive and manually delete records as they expire.
- D. Anonymize the data using the Cloud Data Loss Prevention API and store it indefinitely.
正解：A
質問 # 163
The application reliability team at your company has added a debug feature to their backend service to send all server events to Google Cloud Storage for eventual analysis. The event records are at least 50 KB and at most
15 MB and are expected to peak at 3,000 events per second. You want to minimize data loss.
Which process should you implement?
- A. * Append metadata to file body.
* Compress individual files.
* Name files with a random prefix pattern.
* Save files to one bucket - B. * Append metadata to file body.
* Compress individual files.
* Name files with serverName-Timestamp.
* Create a new bucket if bucket is older than 1 hour and save individual files to the new bucket.
Otherwise, save files to existing bucket - C. * Batch every 10,000 events with a single manifest file for metadata.
* Compress event files and manifest file into a single archive file.
* Name files using serverName-EventSequence.
* Create a new bucket if bucket is older than 1 day and save the single archive file to the new bucket.
Otherwise, save the single archive file to existing bucket. - D. * Compress individual files.
* Name files with serverName-EventSequence.
* Save files to one bucket
* Set custom metadata headers for each object after saving.
正解：A
質問 # 164
You are deploying an application to Google Cloud. The application is part of a system. The application in Google Cloud must communicate over a private network with applications in a non-Google Cloud environment. The expected average throughput is 200 kbps. The business requires:
* 99.99% system availability
* cost optimization
You need to design the connectivity between the locations to meet the business requirements. What should you provision?
- A. Two HA Cloud VPN gateways connected to two on-premises VPN gateways. Configure each HA Cloud VPN gateway to have two tunnels, each connected to different on-premises VPN gateways.
- B. A Classic Cloud VPN gateway connected with one tunnel to an on-premises VPN gateway.
- C. An HA Cloud VPN gateway connected with two tunnels to an on-premises VPN gateway.
- D. A Classic Cloud VPN gateway connected with two tunnels to an on-premises VPN gateway.
正解：C
解説：
Explanation
https://cloud.google.com/network-connectivity/docs/vpn/concepts/topologies#configurations_that_support_9999
質問 # 165
For this question, refer to the TerramEarth case study. A new architecture that writes all incoming data to BigQuery has been introduced. You notice that the data is dirty, and want to ensure data quality on an automated daily basis while managing cost.
What should you do?
- A. Set up a streaming Cloud Dataflow job, receiving data by the ingestion process. Clean the data in a Cloud Dataflow pipeline.
- B. Create a Cloud Function that reads data from BigQuery and cleans it. Trigger it. Trigger the Cloud Function from a Compute Engine instance.
- C. Use Cloud Dataprep and configure the BigQuery tables as the source. Schedule a daily job to clean the data.
- D. Create a SQL statement on the data in BigQuery, and save it as a view. Run the view daily, and save the result to a new table.
正解：A
質問 # 166
Your company has a support ticketing solution that uses App Engine Standard. The project that contains the App Engine application already has a Virtual Private Cloud(VPC) network fully connected to the company's on-premises environment through a Cloud VPN tunnel. You want to enable App Engine application to communicate with a database that is running in the company's on-premises environment.
What should you do?
- A. Configure private Google access for on-premises hosts only
- B. Configure private services access
- C. Configure serverless VPC access
- D. Configure private Google access
正解：B
解説：
Explanation
https://cloud.google.com/appengine/docs/standard/python3/connecting-vpc
https://cloud.google.com/appengine/docs/flexible/python/using-third-party-databases#on_premises
質問 # 167
Your company's test suite is a custom C++ application that runs tests throughout each day on Linux virtual machines. The full test suite takes several hours to complete, running on a limited number of on-premises servers reserved for testing. Your company wants to move the testing infrastructure to the cloud, to reduce the amount of time it takes to fully test a change to the system, while changing the tests as little as possible.
Which cloud infrastructure should you recommend?
- A. Google Cloud Dataproc to run Apache Hadoop jobs to process each test
- B. Google Compute Engine managed instance groups with auto-scaling
- C. Google App Engine with Google StackDriver for logging
- D. Google Compute Engine unmanaged instance groups and Network Load Balancer
正解：B
解説：
Explanation/Reference:
Explanation:
Google Compute Engine enables users to launch virtual machines (VMs) on demand. VMs can be launched from the standard images or custom images created by users.
Managed instance groups offer autoscaling capabilities that allow you to automatically add or remove instances from a managed instance group based on increases or decreases in load. Autoscaling helps your applications gracefully handle increases in traffic and reduces cost when the need for resources is lower.
Incorrect Answers:
B: There is no mention of incoming IP data traffic for the custom C++ applications.
C: Apache Hadoop is not fit for testing C++ applications. Apache Hadoop is an open-source software framework used for distributed storage and processing of datasets of big data using the MapReduce programming model.
D: Google App Engine is intended to be used for web applications.
Google App Engine (often referred to as GAE or simply App Engine) is a web framework and cloud computing platform for developing and hosting web applications in Google-managed data centers.
References: https://cloud.google.com/compute/docs/autoscaler/
質問 # 168
For this question, refer to the Dress4Win case study.
As part of their new application experience, Dress4Wm allows customers to upload images of themselves. The customer has exclusive control over who may view these images. Customers should be able to upload images with minimal latency and also be shown their images quickly on the main application page when they log in.
Which configuration should Dress4Win use?
- A. Store image files in a Google Cloud Storage bucket. Use Google Cloud Datastore to maintain metadata that maps each customer's ID and their image files.
- B. Use a distributed file system to store customers' images. As storage needs increase, add more persistent disks and/or nodes. Use a Google Cloud SQL database to maintain metadata that maps each customer's ID to their image files.
- C. Use a distributed file system to store customers' images. As storage needs increase, add more persistent disks and/or nodes. Assign each customer a unique ID, which sets each file's owner attribute, ensuring privacy of images.
- D. Store image files in a Google Cloud Storage bucket. Add custom metadata to the uploaded images in Cloud Storage that contains the customer's unique ID.
正解：A
質問 # 169
The Dress4Win security team has disabled external SSH access into production virtual machines (VMs) on Google Cloud Platform (GCP).
The operations team needs to remotely manage the VMs, build and push Docker containers, and manage Google Cloud Storage objects.
What can they do?
- A. Develop a new access request process that grants temporary SSH access to cloud VMs when an operations engineer needs to perform a task.
- B. Grant the operations engineer access to use Google Cloud Shell.
- C. Configure a VPN connection to GCP to allow SSH access to the cloud VMs.
- D. Have the development team build an API service that allows the operations team to execute specific remote procedure calls to accomplish their tasks.
正解：B
質問 # 170
Your company has an application running on a deployment in a GKE cluster. You have a separate cluster for development, staging and production. You have discovered that the team is able to deploy a Docker image to the production cluster without first testing the deployment in development and then staging. You want to allow the team to have autonomy but want to prevent this from happening. You want a Google Cloud solution that can be implemented quickly with minimal effort. What should you do?
- A. Configure a Kubernetes lifecycle hook to prevent the container from starting if it is not approved for usage in the given environment
- B. Create a Kubernetes admission controller to prevent the container from starting if it is not approved for usage in the given environment
- C. Implement a corporate policy to prevent teams from deploying Docker image to an environment unless the Docker image was tested in an earlier environment
- D. Configure the binary authorization policies for the development, staging and production clusters.Create attestations as part of the continuous integration pipeline"
正解：D
解説：
https://cloud.google.com/architecture/prep-kubernetes-engine-for-prod#binary-authorization The most common Binary Authorization use cases involve attestations. An attestation certifies that a specific image has completed a previous stage, as described previously. You configure the Binary Authorization policy to verify the attestation before allowing the image to be deployed. At deploy time, instead of redoing activities that were completed in earlier stages, Binary Authorization only needs to verify the attestation.
https://cloud.google.com/binary-authorization/docs/overview
質問 # 171
Case Study: 7 - Mountkirk Games
Company Overview
Mountkirk Games makes online, session-based, multiplayer games for mobile platforms. They build all of their games using some server-side integration. Historically, they have used cloud providers to lease physical servers.
Due to the unexpected popularity of some of their games, they have had problems scaling their global audience, application servers, MySQL databases, and analytics tools.
Their current model is to write game statistics to files and send them through an ETL tool that loads them into a centralized MySQL database for reporting.
Solution Concept
Mountkirk Games is building a new game, which they expect to be very popular. They plan to deploy the game's backend on Google Compute Engine so they can capture streaming metrics, run intensive analytics, and take advantage of its autoscaling server environment and integrate with a managed NoSQL database.
Business Requirements
Increase to a global footprint.
* Improve uptime - downtime is loss of players.
* Increase efficiency of the cloud resources we use.
* Reduce latency to all customers.
* Technical Requirements
Requirements for Game Backend Platform
Dynamically scale up or down based on game activity.
* Connect to a transactional database service to manage user profiles and game state.
* Store game activity in a timeseries database service for future analysis.
* As the system scales, ensure that data is not lost due to processing backlogs.
* Run hardened Linux distro.
* Requirements for Game Analytics Platform
Dynamically scale up or down based on game activity
* Process incoming data on the fly directly from the game servers
* Process data that arrives late because of slow mobile networks
* Allow queries to access at least 10 TB of historical data
* Process files that are regularly uploaded by users' mobile devices
* Executive Statement
Our last successful game did not scale well with our previous cloud provider, resulting in lower user adoption and affecting the game's reputation. Our investors want more key performance indicators (KPIs) to evaluate the speed and stability of the game, as well as other metrics that provide deeper insight into usage patterns so we can adapt the game to target users.
Additionally, our current technology stack cannot provide the scale we need, so we want to replace MySQL and move to an environment that provides autoscaling, low latency load balancing, and frees us up from managing physical servers.
For this question, refer to the Mountkirk Games case study. You need to analyze and define the technical architecture for the compute workloads for your company, Mountkirk Games.
Considering the Mountkirk Games business and technical requirements, what should you do?
- A. Create a global load balancer with managed instance groups and autoscaling policies. Use preemptible Compute Engine instances.
- B. Create network load balancers. Use preemptible Compute Engine instances.
- C. Create a global load balancer with managed instance groups and autoscaling policies. Use non- preemptible Compute Engine instances.
- D. Create network load balancers. Use non-preemptible Compute Engine instances.
正解：A
質問 # 172
For this question, refer to the JencoMart case study.
JencoMart has built a version of their application on Google Cloud Platform that serves traffic to Asia.
You want to measure success against their business and technical goals. Which metrics should you track?
- A. Error rates for requests from Asia
- B. Latency difference between US and Asia
- C. Total visits, error rates, and latency from Asia
- D. Total visits and average latency for users in Asia
- E. The number of character sets present in the database
正解：D
質問 # 173
Your marketing department wants to send out a promotional email campaign. The development team wants to minimize direct operation management. They project a wide range of possible customer responses, from 100 to 500,000 click-throughs per day. The link leads to a simple website that explains the promotion and collects user information and preferences. Which infrastructure should you recommend? (CHOOSE TWO)
- A. Use a single compute Engine virtual machine (VM) to host a web server, backed by Google Cloud SQL.
- B. Use a managed instance group to serve the website and Google Cloud Bigtable to store user data.
- C. Use a Google Container Engine cluster to serve the website and store data to persistent disk.
- D. Use Google App Engine to serve the website and Google Cloud Datastore to store user data.
正解：B、D
解説：
Reference:
References: https://cloud.google.com/storage-options/
質問 # 174
Your organization requires that metrics from all applications be retained for 5 years for future analysis in possible legal proceedings. Which approach should you use?
- A. Grant the security team access to the logs in each Project.
- B. Configure Stackdriver Monitoring for all Projects, and export to Google Cloud Storage.
- C. Configure Stackdriver Monitoring for all Projects with the default retention policies.
- D. Configure Stackdriver Monitoring for all Projects, and export to BigQuery.
正解：D
解説：
Stackdriver Logging provides you with the ability to filter, search, and view logs from your cloud and open source application services. Allows you to define metrics based on log contents that are incorporated into dashboards and alerts. Enables you to export logs to BigQuery, Google Cloud Storage, and Pub/Sub.
References: https://cloud.google.com/stackdriver/
質問 # 175
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