2023年最新の実際に出るProfessional-Cloud-Architect問題集テストエンジン試験問題はここにある
更新された公式資料はProfessional-Cloud-Architect認証済みのProfessional-Cloud-Architect問題集PDF
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質問 # 74
You need to deploy an application on Google Cloud that must run on a Debian Linux environment. The application requires extensive configuration in order to operate correctly. You want to ensure that you can install Debian distribution updates with minimal manual intervention whenever they become available. What should you do?
- A. Create an instance with the latest available Debian image. Connect to the instance via SSH, and install and configure the application on the instance. Repeat this process whenever a new Google-managed Debian image becomes available.
- B. Create a Debian-based Compute Engine instance, install and configure the application, and use OS patch management to install available updates.
- C. Create a Compute Engine instance template using the most recent Debian image. Create an instance from this template, and install and configure the application as part of the startup script. Repeat this process whenever a new Google-managed Debian image becomes available.
- D. Create a Docker container with Debian as the base image. Install and configure the application as part of the Docker image creation process. Host the container on Google Kubernetes Engine and restart the container whenever a new update is available.
正解：B
解説：
Reference: https://cloud.google.com/compute/docs/os-patch-management
質問 # 75
For this question, refer to the JencoMart case study.
JencoMart wants to move their User Profiles database to Google Cloud Platform. Which Google Database should they use?
- A. Google BigQuery
- B. Cloud Spanner
- C. Google Cloud Datastore
- D. Google Cloud SQL
正解：C
解説：
https://cloud.google.com/datastore/docs/concepts/overview
Common workloads for Google Cloud Datastore:
User profiles
Product catalogs
Game state
References: https://cloud.google.com/storage-options/
https://cloud.google.com/datastore/docs/concepts/overview
質問 # 76
Your customer is moving their corporate applications to Google Cloud Platform. The security team wants
detailed visibility of all projects in the organization. You provision the Google Cloud Resource Manager and
set up yourself as the org admin.
What Google Cloud Identity and Access Management (Cloud IAM) roles should you give to the security
team?
- A. Org viewer, project owner
- B. Project owner, network admin
- C. Org viewer, project viewer
- D. Org admin, project browser
正解：C
質問 # 77
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 a Compute Engine instance with 96 CPUs.
- B. Replace the existing data warehouse with BigQuery. Use table partitioning.
- C. Replace the existing data warehouse with BigQuery. Use federated data sources.
- D. Replace the existing data warehouse with a Compute Engine instance with 96 CPUs. Add an additional Compute Engine pre-emptible instance with 32 CPUs.
正解：C
質問 # 78
You have created several preemptible Linux virtual machine instances using Google Compute Engine. You want to properly shut down your application before the virtual machines are preempted. What should you do?
- A. Create a shutdown script named k99.shutdown in the /etc/rc.6.d/ directory.
- B. Create a shutdown script, registered as a xinetd service in Linux, and use the gcloud compute instances add-metadata command to specify the service URL as the value for a new metadata entry with the key shutdown-script-url
- C. Create a shutdown script registered as a xinetd service in Linux and configure a Stackdnver endpoint check to call the service.
- D. Create a shutdown script and use it as the value for a new metadata entry with the key shutdown-script in the Cloud Platform Console when you create the new virtual machine instance.
正解：A
質問 # 79
Your company just finished a rapid lift and shift to Google Compute Engine for your compute needs. You have another 9 months to design and deploy a more cloud-native solution. Specifically, you want a system that is no-ops and auto-scaling.
Which two compute products should you choose? Choose 2 answers.
- A. Google Container Engine with containers
- B. Compute Engine with custom instance types
- C. Compute Engine with managed instance groups
- D. Google App Engine Standard Environment
- E. Compute Engine with containers
正解：A、D
解説：
Explanation/Reference:
Explanation:
B: With Container Engine, Google will automatically deploy your cluster for you, update, patch, secure the nodes.
Kubernetes Engine's cluster autoscaler automatically resizes clusters based on the demands of the workloads you want to run.
C: Solutions like Datastore, BigQuery, AppEngine, etc are truly NoOps.
App Engine by default scales the number of instances running up and down to match the load, thus providing consistent performance for your app at all times while minimizing idle instances and thus reducing cost.
Note: At a high level, NoOps means that there is no infrastructure to build out and manage during usage of the platform. Typically, the compromise you make with NoOps is that you lose control of the underlying infrastructure.
References: https://www.quora.com/How-well-does-Google-Container-Engine-support-Google-Cloud- Platform%E2%80%99s-NoOps-claim
質問 # 80
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. Use Cloud Dataprep and configure the BigQuery tables as the source. Schedule a daily job to clean the data.
- B. Set up a streaming Cloud Dataflow job, receiving data by the ingestion process. Clean the data in a Cloud Dataflow pipeline.
- C. 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.
- D. Create a Cloud Function that reads data from BigQuery and cleans it. Trigger it. Trigger the Cloud Function from a Compute Engine instance.
正解：A
質問 # 81
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? Choose 2 answers
- A. Load logs into Google Cloud SQL.
- B. Import logs into Google Stackdriver.
- C. Upload log files into Google Cloud Storage.
- D. Insert logs into Google Cloud Bigtable.
- E. Load logs into Google BigQuery.
正解：B、E
質問 # 82
TerramEarth plans to connect all 20 million vehicles in the field to the cloud. This increases the volume to 20 million 600 byte records a second for 40 TB an hour.
How should you design the data ingestion?
- A. Vehicles stream data directly to Google BigQuery
- B. Vehicles continue to write data using the existing system (FTP)
- C. Vehicles write data directly to GCS
- D. Vehicles write data directly to Google Cloud Pub/Sub
正解：A
質問 # 83
You are building a continuous deployment pipeline for a project stored in a Git source repository and want to ensure that code changes can be verified deploying to production. What should you do?
- A. Use Spinnaker to deploy builds to production and run tests on production deployments.
- B. Use Jenkins to build the staging branches and the master branch. Build and deploy changes to production for 10% of users before doing a complete rollout.
- C. Use Spinnaker to deploy builds to production using the red/black deployment strategy so that changes can easily be rolled back.
- D. Use Jenkins to monitor tags in the repository. Deploy staging tags to a staging environment for testing.
After testing, tag the repository for production and deploy that to the production environment.
正解：D
解説：
Reference: https://github.com/GoogleCloudPlatform/continuous-deployment-on-kubernetes/blob/master/ README.md
質問 # 84
Your company just finished a rapid lift and shift to Google Compute Engine for your compute needs. You have another 9 months to design and deploy a more cloud-native solution. Specifically, you want a system that is no-ops and auto-scaling. Which two compute products should you choose? Choose 2 answers
- A. Google Container Engine with containers
- B. Compute Engine with custom instance types
- C. Compute Engine with managed instance groups
- D. Google App Engine Standard Environment
- E. Compute Engine with containers
正解：A、D
質問 # 85
You have an application that makes HTTP requests to Cloud Storage. Occasionally the requests fail with HTTP status codes of 5xx and 429.
How should you handle these types of errors?
- A. Implement retry logic using a truncated exponential backoff strategy.
- B. Make sure the Cloud Storage bucket is multi-regional for geo-redundancy.
- C. Use gRPC instead of HTTP for better performance.
- D. Monitor https://status.cloud.google.com/feed.atom and only make requests if Cloud Storage is not reporting an incident.
正解：A
解説：
Explanation/Reference: https://cloud.google.com/storage/docs/json_api/v1/status-codes
質問 # 86
You want to enable your running Google Container Engine cluster to scale as demand for your application changes.
What should you do?
- A. Create a new Container Engine cluster with the following command:
gcloud alpha container clusters create mycluster --enable-autocaling --min-nodes=1 --max-nodes=10 and redeploy your application. - B. Update the existing Container Engine cluster with the following command:
gcloud alpha container clusters update mycluster --enable-autoscaling --min-nodes=1 --max-nodes=10 - C. Add a tag to the instances in the cluster with the following command:
gcloud compute instances add-tags INSTANCE --tags enable --autoscaling max-nodes-10 - D. Add additional nodes to your Container Engine cluster using the following command:
gcloud container clusters resize CLUSTER_NAME --size 10
正解：C
解説：
Explanation
https://cloud.google.com/kubernetes-engine/docs/concepts/cluster-autoscaler Cluster autoscaling
--enable-autoscaling
Enables autoscaling for a node pool.
Enables autoscaling in the node pool specified by --node-pool or the default node pool if --node-pool is not provided.
Where:
--max-nodes=MAX_NODES
Maximum number of nodes in the node pool.
Maximum number of nodes to which the node pool specified by --node-pool (or default node pool if unspecified) can scale.
質問 # 87
Your company has an application running on multiple Compute Engine instances. You need to ensure that the application can communicate with an on-premises service that requires high throughput via internal IPs, while minimizing latency. What should you do?
- A. Configure a direct peering connection between the on-premises environment and Google Cloud.
- B. Use OpenVPN to configure a VPN tunnel between the on-premises environment and Google Cloud.
- C. Use Cloud VPN to configure a VPN tunnel between the on-premises environment and Google Cloud.
- D. Configure a Cloud Dedicated Interconnect connection between the on-premises environment and Google Cloud.
正解：C
解説：
Reference https://cloud.google.com/architecture/setting-up-private-access-to-cloud-apis-through-vpn-tunnels
質問 # 88
An application development team believes their current logging tool will not meet their needs for their new cloud-based product. They want a bettor tool to capture errors and help them analyze their historical log data. You want to help them find a solution that meets their needs, what should you do?
- A. Help them upgrade their current tool to take advantage of any new features.
- B. Help them define their requirements and assess viable logging tools.
- C. Direct them to download and install the Google StackDriver logging agent.
- D. Send them a list of online resources about logging best practices.
正解：B
解説：
Help them define their requirements and assess viable logging tools. They know the requirements and the existing tools' problems. While it's true StackDriver Logging and Error Reporting possibly meet all their requirements, there might be other tools also meet their need. They need you to provide expertise to make assessment for new tools, specifically, logging tools that can "capture errors and help them analyze their historical log data".
References:
https://cloud.google.com/logging/docs/agent/installation
質問 # 89
For this question, refer to the JencoMart case study.
The JencoMart security team requires that all Google Cloud Platform infrastructure is deployed using a least privilege model with separation of duties for administration between production and development resources. What Google domain and project structure should you recommend?
- A. Create a single G Suite account to manage users with each stage of each application in its own project.
- B. Create two G Suite accounts to manage users: one with a single project for all development applications and one with a single project for all production applications.
- C. Create two G Suite accounts to manage users: one for development/test/staging and one for production. Each account should contain one project for every application.
- D. Create a single G Suite account to manage users with one project for the development/test/staging environment and one project for the production environment.
正解：C
質問 # 90
The operations manager asks you for a list of recommended practices that she should consider when migrating a J2EE application to the cloud. Which three practices should you recommend? Choose 3 answers
- A. Instrument the application with a monitoring tool like Stackdriver Debugger.
- B. Integrate Cloud Dataflow into the application to capture real-time metrics.
- C. Port the application code to run on Google App Engine.
- D. Migrate from MySQL to a managed NoSQL database like Google Cloud Datastore or Bigtable.
- E. Select an automation framework to reliably provision the cloud infrastructure.
- F. Deploy a continuous integration tool with automated testing in a staging environment.
正解：C、D、F
解説：
References: https://cloud.google.com/appengine/docs/standard/java/tools/uploadinganapp
https://cloud.google.com/appengine/docs/standard/java/building-app/cloud-sql
質問 # 91
One of your primary business objectives is being able to trust the data stored in your application.
You want to log all changes to the application data. How can you design your logging system to verify authenticity of your logs?
- A. Create a JSON dump of each log entry and store it in Google Cloud Storage.
- B. Write the log concurrently in the cloud and on premises.
- C. Use a SQL database and limit who can modify the log table.
- D. Digitally sign each timestamp and log entry and store the signature.
正解：A
解説：
Write a log entry. If the log does not exist, it is created. You can specify a severity for the log entry, and you can write a structured log entry by specifying --payload-type=json and writing your message as a JSON string:
gcloud logging write LOG STRING
gcloud logging write LOG JSON-STRING --payload-type=json
References: https://cloud.google.com/logging/docs/reference/tools/gcloud-logging
質問 # 92
Your customer is moving an existing corporate application to Google Cloud Platform from an on-premises data center. The business owners require minimal user disruption. There are strict security team requirements for storing passwords. What authentication strategy should they use?
- A. Ask users to set their Google password to match their corporate password.
- B. Use G Suite Password Sync to replicate passwords into Google.
- C. Provision users in Google using the Google Cloud Directory Sync tool.
- D. Federate authentication via SAML 2.0 to the existing Identity Provider.
正解：C
解説：
Explanation
https://support.google.com/a/answer/2611859?hl=en
Provision users to Google's directory
The global Directory is available to both Cloud Platform and G Suite resources and can be provisioned by a number of means. Provisioned users can take advantage of rich authentication features including single sign-on (SSO), OAuth, and two-factor verification.
You can provision users automatically using one of the following tools and services:
Google Cloud Directory Sync (GCDS)
Google Admin SDK
A third-party connector
GCDS is a connector that can provision users and groups on your behalf for both Cloud Platform and G Suite.
Using GCDS, you can automate the addition, modification, and deletion of users, groups, and non-employee contacts. You can synchronize the data from your LDAP directory server to your Cloud Platform domain by using LDAP queries. This synchronization is one-way: the data in your LDAP directory server is never modified.
References:
https://cloud.google.com/docs/enterprise/best-practices-for-enterprise-organizations#authentication-and-identity
質問 # 93
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Google Professional-Cloud-Architect 認定は、IT プロフェッショナルやクラウドアーキテクトが、GCP を使用したクラウドソリューションの設計、開発、管理における専門知識を証明するための貴重な資格です。認定試験は、さまざまなトピックをカバーし、候補者が組織のニーズに合わせてスケーラブルで信頼性の高く、コスト効果の高いクラウドソリューションを設計、展開できる能力を評価するように設計されています。
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