[2023年更新]早速ゲットしてトップランクのGoogle Professional-Cloud-DevOps-Engineer試験問題集
パスする秘訣はProfessional-Cloud-DevOps-Engineerをゲットして認証された試験エンジンPDF
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Google Professional-Cloud-Devops-Engineer（Google Cloud Certified-Professional Cloud Devops Engineer）認定試験は、Cloud Devops Engineeringの分野の専門家にとって非常に人気のある認定です。この認定はGoogle Cloudによって提供されており、Google Cloudプラットフォームでアプリケーションの展開、監視、管理における個人のスキルと専門知識を検証するように設計されています。
質問 # 25
You manage several production systems that run on Compute Engine in the same Google Cloud Platform (GCP) project. Each system has its own set of dedicated Compute Engine instances. You want to know how must it costs to run each of the systems. What should you do?
- A. Name each virtual machine (VM) after the system it runs. Set up a usage report export to a Cloud Storage bucket. Configure the bucket as a source in BigQuery to query costs based on VM name.
- B. Enrich all instances with metadata specific to the system they run. Configure Stackdriver Logging to export to BigQuery, and query costs based on the metadata.
- C. Assign all instances a label specific to the system they run. Configure BigQuery billing export and query costs per label.
- D. In the Google Cloud Platform Console, use the Cost Breakdown section to visualize the costs per system.
正解：C
解説：
https://cloud.google.com/billing/docs/how-to/export-data-bigquery
質問 # 26
You have a CI/CD pipeline that uses Cloud Build to build new Docker images and push them to Docker Hub.
You use Git for code versioning. After making a change in the Cloud Build YAML configuration, you notice that no new artifacts are being built by the pipeline. You need to resolve the issue following Site Reliability Engineering practices. What should you do?
- A. Change the CI pipeline to push the artifacts is Container Registry instead of Docker Hub.
- B. Disable the CI pipeline and revert to manually building and pushing the artifacts.
- C. Upload the configuration YAML file to Cloud Storage and use Error Reporting to identify and fix the issue.
- D. Run a Git compare between the previous and current Cloud Build Configuration files to find and fix the bug.
正解：A
質問 # 27
You have a CI/CD pipeline that uses Cloud Build to build new Docker images and push them to Docker Hub. You use Git for code versioning. After making a change in the Cloud Build YAML configuration, you notice that no new artifacts are being built by the pipeline. You need to resolve the issue following Site Reliability Engineering practices. What should you do?
- A. Run a Git compare between the previous and current Cloud Build Configuration files to find and fix the bug.
- B. Disable the CI pipeline and revert to manually building and pushing the artifacts.
- C. Upload the configuration YAML file to Cloud Storage and use Error Reporting to identify and fix the issue.
- D. Change the CI pipeline to push the artifacts to Container Registry instead of Docker Hub.
正解：A
解説：
"After making a change in the Cloud Build YAML configuration, you notice that no new artifacts are being built by the pipeline"- means something wrong on the recent change not with the image registry.
質問 # 28
Your team uses Cloud Build for all CI/CO pipelines. You want to use the kubectl builder for Cloud Build to deploy new images to Google Kubernetes Engine (GKE). You need to authenticate to GKE while minimizing development effort. What should you do?
- A. Specify the Container Developer role for Cloud Build in the cloudbuild.yaml file.
- B. Assign the Container Developer role to the Cloud Build service account.
- C. Create a new service account with the Container Developer role and use it to run Cloud Build.
- D. Create a separate step in Cloud Build to retrieve service account credentials and pass these to kubectl.
正解：B
解説：
Explanation
https://cloud.google.com/build/docs/deploying-builds/deploy-gke
https://cloud.google.com/build/docs/securing-builds/configure-user-specified-service-accounts
質問 # 29
Your team has recently deployed an NGINX-based application into Google Kubernetes Engine (GKE) and has exposed it to the public via an HTTP Google Cloud Load Balancer (GCLB) ingress. You want to scale the deployment of the application's frontend using an appropriate Service Level Indicator (SLI). What should you do?
- A. Expose the NGINX stats endpoint and configure the horizontal pod autoscaler to use the request metrics exposed by the NGINX deployment.
- B. Install the Stackdriver custom metrics adapter and configure a horizontal pod autoscaler to use the number of requests provided by the GCLB.
- C. Configure the horizontal pod autoscaler to use the average response time from the Liveness and Readiness probes.
- D. Configure the vertical pod autoscaler in GKE and enable the cluster autoscaler to scale the cluster as pods expand.
正解：A
質問 # 30
Your company experiences bugs, outages, and slowness in its production systems. Developers use the production environment for new feature development and bug fixes. Configuration and experiments are done in the production environment, causing outages for users. Testers use the production environment for load testing, which often slows the production systems. You need to redesign the environment to reduce the number of bugs and outages in production and to enable testers to load test new features. What should you do?
- A. Create a development environment with smaller server capacity and give access only to developers and testers.
- B. Secure the production environment to ensure that developers can't change it and set up one controlled update per year.
- C. Create a development environment for writing code and a test environment for configurations, experiments, and load testing.
- D. Create an automated testing script in production to detect failures as soon as they occur.
正解：C
解説：
Explanation
Creating a development environment for writing code and a test environment for configurations, experiments, and load testing is the best practice to reduce the number of bugs and outages in production and to enable testers to load test new features. This way, the production environment is isolated from changes that could affect its stability and performance.
質問 # 31
You support a production service that runs on a single Compute Engine instance. You regularly need to spend time on recreating the service by deleting the crashing instance and creating a new instance based on the relevant image. You want to reduce the time spent performing manual operations while following Site Reliability Engineering principles. What should you do?
- A. File a bug with the development team so they can find the root cause of the crashing instance.
- B. Add a Load Balancer in front of the Compute Engine instance and use health checks to determine the system status.
- C. Create a Stackdriver Monitoring dashboard with SMS alerts to be able to start recreating the crashed instance promptly after it has crashed.
- D. Create a Managed Instance Group with a single instance and use health checks to determine the system status.
正解：B
質問 # 32
You are running an application on Compute Engine and collecting logs through Stackdriver. You discover that some personally identifiable information (Pll) is leaking into certain log entry fields. All Pll entries begin with the text userinfo. You want to capture these log entries in a secure location for later review and prevent them from leaking to Stackdriver Logging. What should you do?
- A. Create an advanced log filter matching userinfo, configure a log export in the Stackdriver console with Cloud Storage as a sink, and then configure a tog exclusion with userinfo as a filter.
- B. Create a basic log filter matching userinfo, and then configure a log export in the Stackdriver console with Cloud Storage as a sink.
- C. Use a Fluentd filter plugin with the Stackdriver Agent to remove log entries containing userinfo, create an advanced log filter matching userinfo, and then configure a log export in the Stackdriver console with Cloud Storage as a sink.
- D. Use a Fluentd filter plugin with the Stackdriver Agent to remove log entries containing userinfo, and then copy the entries to a Cloud Storage bucket.
正解：D
解説：
https://medium.com/google-cloud/fluentd-filter-plugin-for-google-cloud-data-loss-prevention-api-42bbb1308e76
質問 # 33
Your application runs on Google Cloud Platform (GCP). You need to implement Jenkins for deploying application releases to GCP. You want to streamline the release process, lower operational toil, and keep user data secure. What should you do?
- A. Implement Jenkins on Google Cloud Functions.
- B. Implement Jenkins on local workstations.
- C. Implement Jenkins on Compute Engine virtual machines.
- D. Implement Jenkins on Kubernetes on-premises
正解：C
解説：
Explanation
Your application runs on Google Cloud Platform (GCP). You need to implement Jenkins for deploying application releases to GCP. You want to streamline the release process, lower operational toil, and keep user data secure. What should you do?
https://plugins.jenkins.io/google-compute-engine/
質問 # 34
Your team is designing a new application for deployment into Google Kubernetes Engine (GKE). You need to set up monitoring to collect and aggregate various application-level metrics in a centralized location. You want to use Google Cloud Platform services while minimizing the amount of work required to set up monitoring. What should you do?
- A. Install the OpenTelemetry client libraries in the application, configure Stackdriver as the export destination for the metrics, and then observe the application's metrics in Stackdriver.
- B. Publish various melrics from the application directly to the Slackdriver Monitoring API, and then observe these custom metrics in Stackdriver.
- C. Emit all metrics in the form of application-specific log messages, pass these messages from the containers to the Stackdriver logging collector, and then observe metrics in Stackdriver.
- D. Install the Cloud Pub/Sub client libraries, push various metrics from the application to various topics, and then observe the aggregated metrics in Stackdriver.
正解：B
質問 # 35
You support an application that stores product information in cached memory. For every cache miss, an entry is logged in Stackdriver Logging. You want to visualize how often a cache miss happens over time. What should you do?
- A. Configure BigOuery as a sink for Stackdriver Logging. Create a scheduled query to filter the cache miss logs and write them to a separate table
- B. Create a logs-based metric in Stackdriver Logging and a dashboard for that metric in Stackdriver Monitoring.
- C. Link Stackdriver Logging as a source in Google Data Studio. Filler (he logs on the cache misses.
- D. Configure Stackdriver Profiler to identify and visualize when the cache misses occur based on the logs.
正解：B
解説：
https://cloud.google.com/logging/docs/logs-based-metrics#counter-metric
質問 # 36
Your organization recently adopted a container-based workflow for application development. Your team develops numerous applications that are deployed continuously through an automated build pipeline to the production environment. A recent security audit alerted your team that the code pushed to production could contain vulnerabilities and that the existing tooling around virtual machine (VM) vulnerabilities no longer applies to the containerized environment. You need to ensure the security and patch level of all code running through the pipeline. What should you do?
- A. Configure the containers in the build pipeline to always update themselves before release.
- B. Reconfigure the existing operating system vulnerability software to exist inside the container.
- C. Set up Container Analysis to scan and report Common Vulnerabilities and Exposures.
- D. Implement static code analysis tooling against the Docker files used to create the containers.
正解：C
質問 # 37
You are designing a new Google Cloud organization for a client. Your client is concerned with the risks associated with long-lived credentials created in Google Cloud. You need to design a solution to completely eliminate the risks associated with the use of JSON service account keys while minimizing operational overhead. What should you do?
- A. Grant the roles/ iam.serviceAccountKeyAdmin IAM role to organization administrators only.
- B. Apply the constraints/iam.disableserviceAccountKeycreation constraint to the organization.
- C. Use custom versions of predefined roles to exclude all iam.serviceAccountKeys. * service account role permissions.
- D. Apply the constraints/iam.disableServiceAccountKeyUp10ad constraint to the organization.
正解：B
解説：
Explanation
The correct answer is B. Apply the constraints/iam.disableServiceAccountKeyCreation constraint to the organization.
According to the Google Cloud documentation, the constraints/iam.disableServiceAccountKeyCreation constraint is an organization policy constraint that prevents the creation of user-managed service account keys1. User-managed service account keys are long-lived credentials that can be downloaded as JSON or P12 files and used to authenticate as a service account2. These keys pose severe security risks if they are leaked, stolen, or misused by unauthorized entities34. By applying this constraint to the organization, you can completely eliminate the risks associated with the use of JSON service account keys and enforce a more secure alternative for authentication, such as Workload Identity or short-lived access tokens12. This also minimizes operational overhead by avoiding the need to manage, rotate, or revoke user-managed service account keys.
The other options are incorrect because they do not completely eliminate the risks associated with the use of JSON service account keys. Option A is incorrect because it only restricts the IAM permissions to create, list, get, delete, or sign service account keys, but it does not prevent existing keys from being used or leaked.
Option C is incorrect because it only disables the upload of user-managed service account keys, but it does not prevent the creation or download of such keys. Option D is incorrect because it only limits the IAM role that can create and manage service account keys, but it does not prevent the keys from being distributed or exposed to unauthorized entities.
質問 # 38
You support an application deployed on Compute Engine. The application connects to a Cloud SQL instance to store and retrieve dat a. After an update to the application, users report errors showing database timeout messages. The number of concurrent active users remained stable. You need to find the most probable cause of the database timeout. What should you do?
- A. Use Stackdriver Profiler to visualize the resources utilization throughout the application.
- B. Use Cloud Security Scanner to see whether your Cloud SQL is under a Distributed Denial of Service (DDoS) attack.
- C. Check the serial port logs of the Compute Engine instance.
- D. Determine whether there is an increased number of connections to the Cloud SQL instance.
正解：C
質問 # 39
You are designing a deployment technique for your applications on Google Cloud. As part Of your deployment planning, you want to use live traffic to gather performance metrics for new versions Of your applications. You need to test against the full production load before your applications are launched. What should you do?
- A. Use shadow testing with continuous deployment.
- B. Use canary testing with rolling updates deployment,
- C. Use canary testing with continuous deployment.
- D. Use A/B testing with blue/green deployment.
正解：A
解説：
Explanation
The correct answer is B. Use shadow testing with continuous deployment.
Shadow testing is a deployment technique that involves routing a copy of the live traffic to a new version of the application, without affecting the production environment. This way, you can gather performance metrics and compare them with the current version, without exposing the new version to the users. Shadow testing can help you test against the full production load and identify any issues or bottlenecks before launching the new version. You can use continuous deployment to automate the process of deploying the new version after it passes the shadow testing.
質問 # 40
You are developing a strategy for monitoring your Google Cloud Platform (GCP) projects in production using Stackdriver Workspaces. One of the requirements is to be able to quickly identify and react to production environment issues without false alerts from development and staging projects. You want to ensure that you adhere to the principle of least privilege when providing relevant team members with access to Stackdriver Workspaces. What should you do?
- A. Create a new GCP monitoring project, and create a Stackdriver Workspace inside it. Attach the production projects to this workspace. Grant relevant team members read access to the Stackdriver Workspace.
- B. Grant relevant team members the Project Viewer IAM role on all GCP production projects. Create Slackdriver workspaces inside each project.
- C. Choose an existing GCP production project to host the monitoring workspace. Attach the production projects to this workspace. Grant relevant team members read access to the Stackdriver Workspace.
- D. Grant relevant team members read access to all GCP production projects. Create Stackdriver workspaces inside each project.
正解：A
解説：
Explanation
"A Project can host many Projects and appear in many Projects, but it can only be used as the scoping project once. We recommend that you create a new Project for the purpose of having multiple Projects in the same scope."
質問 # 41
Your team is running microservices in Google Kubernetes Engine (GKE) You want to detect consumption of an error budget to protect customers and define release policies What should you do?
- A. Create SLIs from metrics Enable Alert Policies if the services do not pass
- B. Use the metrics from Anthos Service Mesh to measure the health of the microservices
- C. Create a SLO and configure uptime checks for your services Enable Alert Policies if the services do not pass
- D. Create a SLO Create an Alert Policy on select_slo_bum_rate
正解：D
解説：
Explanation
The best option for detecting consumption of an error budget to protect customers and define release policies is to create a service level objective (SLO) and create an alert policy on select_slo_burn_rate. A SLO is a target value or range of values for a service level indicator (SLI) that measures some aspect of the service quality, such as availability or latency. An error budget is the amount of time or number of errors that a service can tolerate while still meeting its SLO. A select_slo_burn_rate is a metric that indicates how fast the error budget is being consumed by the service. By creating an alert policy on select_slo_burn_rate, you can trigger notifications or actions when the error budget consumption exceeds a certain threshold. This way, you can balance change, velocity, and reliability of the service by adjusting the release policies based on the error budget status.
質問 # 42
You encounter a large number of outages in the production systems you support. You receive alerts for all the outages that wake you up at night. The alerts are due to unhealthy systems that are automatically restarted within a minute. You want to set up a process that would prevent staff burnout while following Site Reliability Engineering practices. What should you do?
- A. Redefine the related Service Level Objective so that the error budget is not exhausted.
- B. Create an incident report for each of the alerts.
- C. Distribute the alerts to engineers in different time zones.
- D. Eliminate unactionable alerts.
正解：D
解説：
Explanation
Eliminate bad monitoring : Unactionable alerts (i.e., spam)
https://cloud.google.com/blog/products/management-tools/meeting-reliability-challenges-with-sre-principles agree with kyubiblaze about having to remove unactionable items aka spam: "good monitoring alerts on actionable problems" @
https://cloud.google.com/blog/products/management-tools/meeting-reliability-challenges-with-sre-principles
質問 # 43
You manage several production systems that run on Compute Engine in the same Google Cloud Platform (GCP) project. Each system has its own set of dedicated Compute Engine instances. You want to know how must it costs to run each of the systems. What should you do?
- A. Name each virtual machine (VM) after the system it runs. Set up a usage report export to a Cloud Storage bucket. Configure the bucket as a source in BigQuery to query costs based on VM name.
- B. Enrich all instances with metadata specific to the system they run. Configure Stackdriver Logging to export to BigQuery, and query costs based on the metadata.
- C. Assign all instances a label specific to the system they run. Configure BigQuery billing export and query costs per label.
- D. In the Google Cloud Platform Console, use the Cost Breakdown section to visualize the costs per system.
正解：C
解説：
Explanation
https://cloud.google.com/billing/docs/how-to/export-data-bigquery
質問 # 44
You support an application running on App Engine. The application is used globally and accessed from various device types. You want to know the number of connections. You are using Stackdriver Monitoring for App Engine. What metric should you use?
- A. flex/connections/current
- B. flex/instance/connections/current
- C. tcp_ssl_proxy/open_connections
- D. tcp_ssl_proxy/new_connections
正解：B
解説：
Explanation/Reference: https://cloud.google.com/monitoring/api/metrics_gcp
質問 # 45
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この試験は、クラウドコンピューティング、DevOps、およびソフトウェア開発の経験がある専門家向けに設計されています。インフラストラクチャの自動化、構成管理、継続的な統合と配信、監視とロギングなどの幅広いトピックをカバーしています。この試験には、Kubernetes、クラウドビルド、クラウド監視などのGoogleクラウドプラットフォームツールやサービスでの実践的なエクスペリエンスも含まれています。
Professional-Cloud-DevOps-Engineer試験問題は練習は2023年最新の164問題：https://www.passtest.jp/Google/Professional-Cloud-DevOps-Engineer-shiken.html
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