Professional-Cloud-DevOps-EngineerのPDF問題集で2024年05月20日最近更新された問題
Professional-Cloud-DevOps-Engineer試験問題有効なProfessional-Cloud-DevOps-Engineer問題集PDF
Google Professional-Cloud-DevOps-Engineer（Google Cloud Certified - Professional Cloud DevOps Engineer）認定試験は、テクノロジー業界で非常に求められる認定試験です。この認定試験は、クラウドベースのアプリケーション、サービス、インフラストラクチャの開発、展開、管理に関与する専門家を対象としています。この試験は、クラウドアーキテクチャ、自動化、セキュリティ、コンプライアンス、監視など、様々な領域での候補者の知識とスキルをテストするよう設計されています。
質問 # 52
You work for a global organization and are running a monolithic application on Compute Engine You need to select the machine type for the application to use that optimizes CPU utilization by using the fewest number of steps You want to use historical system metncs to identify the machine type for the application to use You want to follow Google-recommended practices What should you do?
- A. Review the Cloud Monitoring dashboard for the VM and choose the machine type with the lowest CPU utilization
- B. Use the Recommender API and apply the suggested recommendations
- C. Create an Agent Policy to automatically install Ops Agent in all VMs
- D. Install the Ops Agent in a fleet of VMs by using the gcloud CLI
正解：B
解説：
The best option for selecting the machine type for the application to use that optimizes CPU utilization by using the fewest number of steps is to use the Recommender API and apply the suggested recommendations. The Recommender API is a service that provides recommendations for optimizing your Google Cloud resources, such as Compute Engine instances, disks, and firewalls. You can use the Recommender API to get recommendations for changing the machine type of your Compute Engine instances based on historical system metrics, such as CPU utilization. You can also apply the suggested recommendations by using the Recommender API or Cloud Console. This way, you can optimize CPU utilization by using the most suitable machine type for your application with minimal effort.
質問 # 53
Your product is currently deployed in three Google Cloud Platform (GCP) zones with your users divided between the zones. You can fail over from one zone to another, but it causes a 10-minute service disruption for the affected users. You typically experience a database failure once per quarter and can detect it within five minutes. You are cataloging the reliability risks of a new real-time chat feature for your product. You catalog the following information for each risk:
* Mean Time to Detect (MUD} in minutes
* Mean Time to Repair (MTTR) in minutes
* Mean Time Between Failure (MTBF) in days
* User Impact Percentage
The chat feature requires a new database system that takes twice as long to successfully fail over between zones. You want to account for the risk of the new database failing in one zone. What would be the values for the risk of database failover with the new system?
- A. MTTD: 5
MTTR: 10
MTBF: 90
Impact: 33% - B. MTTD:5
MTTR: 20
MTBF: 90
Impact: 50% - C. MTTD:5
MTTR: 10
MTBF: 90
Impact 50% - D. MTTD:5
MTTR: 20
MTBF: 90
Impact: 33%
正解：D
解説：
Explanation
https://www.atlassian.com/incident-management/kpis/common-metrics
https://linkedin.github.io/school-of-sre/
質問 # 54
You are performing a semiannual capacity planning exercise for your flagship service. You expect a service user growth rate of 10% month-over-month over the next six months. Your service is fully containerized and runs on Google Cloud Platform (GCP). using a Google Kubernetes Engine (GKE) Standard regional cluster on three zones with cluster autoscaler enabled. You currently consume about 30% of your total deployed CPU capacity, and you require resilience against the failure of a zone. You want to ensure that your users experience minimal negative impact as a result of this growth or as a result of zone failure, while avoiding unnecessary costs. How should you prepare to handle the predicted growth?
- A. Because you are deployed on GKE and are using a cluster autoscaler. your GKE cluster will scale automatically, regardless of growth rate.
- B. Verity the maximum node pool size, enable a horizontal pod autoscaler, and then perform a load test to verity your expected resource needs.
- C. Proactively add 60% more node capacity to account for six months of 10% growth rate, and then perform a load test to make sure you have enough capacity.
- D. Because you are at only 30% utilization, you have significant headroom and you won't need to add any additional capacity for this rate of growth.
正解：B
解説：
Explanation
https://cloud.google.com/kubernetes-engine/docs/concepts/horizontalpodautoscaler The Horizontal Pod Autoscaler changes the shape of your Kubernetes workload by automatically increasing or decreasing the number of Pods in response to the workload's CPU or memory consumption
質問 # 55
You use Cloud Build to build your application. You want to reduce the build time while minimizing cost and development effort. What should you do?
- A. Use Cloud Storage to cache intermediate artifacts.
- B. Run multiple Jenkins agents to parallelize the build.
- C. Use multiple smaller build steps to minimize execution time.
- D. Use larger Cloud Build virtual machines (VMs) by using the machine-type option.
正解：C
解説：
Explanation
https://cloud.google.com/storage/docs/best-practices
https://cloud.google.com/build/docs/speeding-up-builds#caching_directories_with_google_cloud_storage Caching directories with Google Cloud Storage To increase the speed of a build, reuse the results from a previous build. You can copy the results of a previous build to a Google Cloud Storage bucket, use the results for faster calculation, and then copy the new results back to the bucket. Use this method when your build takes a long time and produces a small number of files that does not take time to copy to and from Google Cloud Storage.
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質問 # 56
You support a web application that is hosted on Compute Engine. The application provides a booking service for thousands of users. Shortly after the release of a new feature, your monitoring dashboard shows that all users are experiencing latency at login. You want to mitigate the impact of the incident on the users of your service. What should you do first?
- A. Roll back the recent release.
- B. Review the Stackdriver monitoring.
- C. Upsize the virtual machines running the login services.
- D. Deploy a new release to see whether it fixes the problem.
正解：C
解説：
Explanation
Rollback to previous stable version. Then you need to find what is causing the issue.
質問 # 57
You support an application running on GCP and want to configure SMS notifications to your team for the most critical alerts in Stackdriver Monitoring. You have already identified the alerting policies you want to configure this for. What should you do?
- A. Ensure that your team members set their SMS/phone numbers in their Stackdriver Profile. Select the SMS notification option for each alerting policy and then select the appropriate SMS/phone numbers from the list.
- B. Select the Webhook notifications option for each alerting policy, and configure it to use a third-party integration tool. Ensure that your team members add their SMS/phone numbers to the external tool.
- C. Download and configure a third-party integration between Stackdriver Monitoring and an SMS gateway.
Ensure that your team members add their SMS/phone numbers to the external tool. - D. Configure a Slack notification for each alerting policy. Set up a Slack-to-SMS integration to send SMS messages when Slack messages are received. Ensure that your team members add their SMS/phone numbers to the external integration.
正解：A
解説：
Explanation
https://cloud.google.com/monitoring/support/notification-options#creating_channels To configure SMS notifications, do the following:
In the SMS section, click Add new and follow the instructions. Click Save. When you set up your alerting policy, select the SMS notification type and choose a verified phone number from the list.
質問 # 58
Your applications performance in Google Cloud has degraded since the last release You suspect that downstream dependencies might be causing some requests to take longer to complete You need to investigate the issue with your application to determine the cause What should you do?
- A. Configure Cloud Profiler in your application
- B. Configure Cloud Trace in your application
- C. Configure Error Reporting in your application
- D. Configure Google Cloud Managed Service for Prometheus in your application
正解：B
解説：
The best option for investigating the issue with your application's performance in Google Cloud is to configure Cloud Trace in your application. Cloud Trace is a service that allows you to collect and analyze latency data from your application. You can use Cloud Trace to trace requests across different components of your application, such as downstream dependencies, and identify where they take longer to complete. You can also use Cloud Trace to compare latency data across different versions of your application, and detect any performance degradation or improvement. By using Cloud Trace, you can diagnose and troubleshoot performance issues with your application in Google Cloud.
質問 # 59
You manage an application that is writing logs to Stackdriver Logging. You need to give some team members the ability to export logs. What should you do?
- A. Create and grant a custom IAM role with the permissions logging.sinks.list and logging.sink.get.
- B. Grant the team members the IAM role of logging.configWriter on Cloud IAM.
- C. Configure Access Context Manager to allow only these members to export logs.
- D. Create an Organizational Policy in Cloud IAM to allow only these members to create log exports.
正解：B
解説：
Explanation
https://cloud.google.com/logging/docs/access-control
The logging.configWriter role grants permissions to create, update, and delete log exports. This is the correct role to give team members who need to export logs2.
質問 # 60
Your company runs an ecommerce website built with JVM-based applications and microservice architecture in Google Kubernetes Engine (GKE) The application load increases during the day and decreases during the night Your operations team has configured the application to run enough Pods to handle the evening peak load You want to automate scaling by only running enough Pods and nodes for the load What should you do?
- A. Configure the Horizontal Pod Autoscaler but keep the node pool size static
- B. Configure the Vertical Pod Autoscaler and enable the cluster autoscaler
- C. Configure the Horizontal Pod Autoscaler and enable the cluster autoscaler
- D. Configure the Vertical Pod Autoscaler but keep the node pool size static
正解：C
解説：
Explanation
The best option for automating scaling by only running enough Pods and nodes for the load is to configure the Horizontal Pod Autoscaler and enable the cluster autoscaler. The Horizontal Pod Autoscaler is a feature that automatically adjusts the number of Pods in a deployment or replica set based on observed CPU utilization or custom metrics. The cluster autoscaler is a feature that automatically adjusts the size of a node pool based on the demand for node capacity. By using both features together, you can ensure that your application runs enough Pods to handle the load, and that your cluster runs enough nodes to host the Pods. This way, you can optimize your resource utilization and cost efficiency.
質問 # 61
Your company follows Site Reliability Engineering practices. You are the Incident Commander for a new.
customer-impacting incident. You need to immediately assign two incident management roles to assist you in an effective incident response. What roles should you assign?
Choose 2 answers
- A. Communications Lead
- B. Engineering Lead
- C. External Customer Communications Lead
- D. Customer Impact Assessor
- E. Operations Lead
正解：A、E
解説：
Explanation
https://sre.google/workbook/incident-response/
"The main roles in incident response are the Incident Commander (IC), Communications Lead (CL), and Operations or Ops Lead (OL)." The Operations Lead is responsible for managing the operational aspects of the incident, such as deploying fixes, rolling back changes, or restoring backups. The External Customer Communications Lead is not a standard role in incident response, but it could be delegated by the Communications Lead if needed.
質問 # 62
You currently store the virtual machine (VM) utilization logs in Stackdriver. You need to provide an easy-to- share interactive VM utilization dashboard that is updated in real time and contains information aggregated on a quarterly basis. You want to use Google Cloud Platform solutions. What should you do?
- A. 1. Export VM utilization logs from Stackdriver to Cloud Pub/Sub.
2. From Cloud Pub/Sub, send the logs to a Security Information and Event Management (SIEM) system.
3. Build the dashboards in the SIEM system and share with your stakeholders. - B. 1. Export VM utilization logs from Stackdriver to BigQuery.
2. Create a dashboard in Data Studio.
3. Share the dashboard with your stakeholders. - C. 1. Export VM utilization logs from Stackdriver to BigQuery.
2. From BigQuery, export the logs to a CSV file.
3. Import the CSV file into Google Sheets.
4. Build a dashboard in Google Sheets and share it with your stakeholders. - D. 1. Export VM utilization logs from Stackdriver to a Cloud Storage bucket.
2. Enable the Cloud Storage API to pull the logs programmatically.
3. Build a custom data visualization application.
4. Display the pulled logs in a custom dashboard.
正解：B
質問 # 63
You support a multi-region web service running on Google Kubernetes Engine (GKE) behind a Global HTTP'S Cloud Load Balancer (CLB). For legacy reasons, user requests first go through a third-party Content Delivery Network (CDN). which then routes traffic to the CLB. You have already implemented an availability Service Level Indicator (SLI) at the CLB level. However, you want to increase coverage in case of a potential load balancer misconfiguration. CDN failure, or other global networking catastrophe. Where should you measure this new SLI?
Choose 2 answers
- A. Instrumentation coded directly in the client
- B. Metrics exported from the application servers
- C. A synthetic client that periodically sends simulated user requests
- D. GKE health checks for your application servers
- E. Your application servers' logs
正解：A、C
質問 # 64
Your uses Jenkins running on Google Cloud VM instances for CI/CD. You need to extend the functionality to use infrastructure as code automation by using Terraform. You must ensure that the Terraform Jenkins instance is authorized to create Google Cloud resources. You want to follow Google-recommended practices- What should you do?
- A. Create a dedicated service account for the Terraform instance. Download and copy the secret key value to the GOOGLE environment variable on the Jenkins server.
- B. use the Terraform module so that Secret Manager can retrieve credentials.
- C. Confirm that the Jenkins VM instance has an attached service account with the appropriate Identity and Access Management (IAM) permissions.
- D. Add the auth application-default command as a step in Jenkins before running the Terraform commands.
正解：C
解説：
The correct answer is C)
Confirming that the Jenkins VM instance has an attached service account with the appropriate Identity and Access Management (IAM) permissions is the best way to ensure that the Terraform Jenkins instance is authorized to create Google Cloud resources. This follows the Google-recommended practice of using service accounts to authenticate and authorize applications running on Google Cloud1. Service accounts are associated with private keys that can be used to generate access tokens for Google Cloud APIs2. By attaching a service account to the Jenkins VM instance, Terraform can use the Application Default Credentials (ADC) strategy to automatically find and use the service account credentials3.
Answer A is incorrect because the auth application-default command is used to obtain user credentials, not service account credentials. User credentials are not recommended for applications running on Google Cloud, as they are less secure and less scalable than service account credentials1.
Answer B is incorrect because it involves downloading and copying the secret key value of the service account, which is not a secure or reliable way of managing credentials. The secret key value should be kept private and not exposed to any other system or user2. Moreover, setting the GOOGLE environment variable on the Jenkins server is not a valid way of providing credentials to Terraform. Terraform expects the credentials to be either in a file pointed by the GOOGLE_APPLICATION_CREDENTIALS environment variable, or in a provider block with the credentials argument3.
Answer D is incorrect because it involves using the Terraform module for Secret Manager, which is a service that stores and manages sensitive data such as API keys, passwords, and certificates. While Secret Manager can be used to store and retrieve credentials, it is not necessary or sufficient for authorizing the Terraform Jenkins instance. The Terraform Jenkins instance still needs a service account with the appropriate IAM permissions to access Secret Manager and other Google Cloud resources.
質問 # 65
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. tcp_ssl_proxy/new_connections
- C. flex/instance/connections/current
- D. tcp_ssl_proxy/open_connections
正解：C
質問 # 66
You are creating and assigning action items in a postmodern for an outage. The outage is over, but you need to address the root causes. You want to ensure that your team handles the action items quickly and efficiently.
How should you assign owners and collaborators to action items?
- A. Assign the team lead as the owner for all action items because they are in charge of the SRE team.
- B. Assign one owner for each action item and any necessary collaborators.
- C. Assign multiple owners for each item to guarantee that the team addresses items quickly
- D. Assign collaborators but no individual owners to the items to keep the postmortem blameless.
正解：B
解説：
Explanation
https://devops.com/when-it-disaster-strikes-part-3-conducting-a-blameless-post-mortem/
質問 # 67
You support a trading application written in Python and hosted on App Engine flexible environment. You want to customize the error information being sent to Stackdriver Error Reporting. What should you do?
- A. Install the Stackdriver Error Reporting library for Python, and then run your code on a Compute Engine VM.
- B. Install the Stackdriver Error Reporting library for Python, and then run your code on Google Kubernetes Engine.
- C. Install the Stackdriver Error Reporting library for Python, and then run your code on App Engine flexible environment.
- D. Use the Stackdriver Error Reporting API to write errors from your application to ReportedErrorEvent, and then generate log entries with properly formatted error messages in Stackdriver Logging.
正解：D
解説：
https://cloud.google.com/error-reporting/docs/formatting-error-messages
https://cloud.google.com/error-reporting/docs/reference/libraries#client-libraries-install-python no need to install error reporting library on App Engine Flex.
質問 # 68
You are creating a CI/CD pipeline in Cloud Build to build an application container image The application code is stored in GitHub Your company requires thai production image builds are only run against the main branch and that the change control team approves all pushes to the main branch You want the image build to be as automated as possible What should you do?
Choose 2 answers
- A. Configure a branch protection rule for the main branch on the repository
- B. Enable the Approval option on the trigger
- C. Add the owners file to the Included files filter on the trigger
- D. Create a trigger on the Cloud Build job Set the repository event setting to Pull request'
- E. Create a trigger on the Cloud Build job Set the repository event setting to Push to a branch
正解：A、E
解説：
Explanation
The best options for creating a CI/CD pipeline in Cloud Build to build an application container image and ensuring that production image builds are only run against the main branch and that the change control team approves all pushes to the main branch are to create a trigger on the Cloud Build job, set the repository event setting to Push to a branch, and configure a branch protection rule for the main branch on the repository. A trigger is a resource that starts a build when an event occurs, such as a code change. By creating a trigger on the Cloud Build job and setting the repository event setting to Push to a branch, you can ensure that the image build is only run when code is pushed to a specific branch, such as the main branch. A branch protection rule is a rule that enforces certain policies on a branch, such as requiring reviews, status checks, or approvals before merging code. By configuring a branch protection rule for the main branch on the repository, you can ensure that the change control team approves all pushes to the main branch.
質問 # 69
You have an application that runs in Google Kubernetes Engine (GKE). The application consists of several microservices that are deployed to GKE by using Deployments and Services One of the microservices is experiencing an issue where a Pod returns 403 errors after the Pod has been running for more than five hours Your development team is working on a solution but the issue will not be resolved for a month You need to ensure continued operations until the microservice is fixed You want to follow Google-recommended practices and use the fewest number of steps What should you do?
- A. Add a HTTP liveness probe to the microservice s deployment
- B. Monitor the Pods and terminate any Pods that have been running for more than five hours
- C. Configure an alert to notify you whenever a Pod returns 403 errors
- D. Create a cron job to terminate any Pods that have been running for more than five hours
正解：A
解説：
Explanation
The best option for ensuring continued operations until the microservice is fixed is to add a HTTP liveness probe to the microservice's deployment. A HTTP liveness probe is a type of probe that checks if a Pod is alive by sending an HTTP request and expecting a success response code. If the probe fails, Kubernetes will restart the Pod. You can add a HTTP liveness probe to your microservice's deployment by using a livenessProbe field in your Pod spec. This way, you can ensure that any Pod that returns 403 errors after running for more than five hours will be restarted automatically and resume normal operations.
質問 # 70
You deploy a new release of an internal application during a weekend maintenance window when there is minimal user traffic. After the window ends, you learn that one of the new features isn't working as expected in the production environment. After an extended outage, you roll back the new release and deploy a fix. You want to modify your release process to reduce the mean time to recovery so you can avoid extended outages in the future. What should you do?
Choose 2 answers
- A. Adopt the blue/green deployment strategy when releasing new code via a CD server.
- B. Before merging new code, require 2 different peers to review the code changes.
- C. Configure a CI server. Add a suite of unit tests to your code and have your CI server run them on commit and verify any changes.
- D. Integrate a code linting tool to validate coding standards before any code is accepted into the repository.
- E. Require developers to run automated integration tests on their local development environments before release.
正解：A、C
質問 # 71
Your organization wants to collect system logs that will be used to generate dashboards in Cloud Operations for their Google Cloud project. You need to configure all current and future Compute Engine instances to collect the system logs and you must ensure that the Ops Agent remains up to date. What should you do?
- A. Use the gcloud CLI to create an Agent Policy.
- B. Use the gcloud CLI to install the Ops Agent on each VM listed in the Cloud Asset Inventory
- C. Install the Ops Agent on the Compute Engine image by using a startup script
- D. Select all VMs with an Agent status of Not detected on the Cloud Operations VMs dashboard Then select Install agents
正解：A
解説：
Explanation
The best option for configuring all current and future Compute Engine instances to collect system logs and ensure that the Ops Agent remains up to date is to use the gcloud CLI to create an Agent Policy. An Agent Policy is a resource that defines how Ops Agents are installed and configured on VM instances that match certain criteria, such as labels or zones. Ops Agents are software agents that collect metrics and logs from VM instances and send them to Cloud Operations products, such as Cloud Monitoring and Cloud Logging. By creating an Agent Policy, you can ensure that all current and future VM instances that match the policy criteria will have the Ops Agent installed and updated automatically. This way, you can collect system logs from all VM instances and use them to generate dashboards in Cloud Operations.
質問 # 72
Your company processes IOT data at scale by using Pub/Sub, App Engine standard environment, and an application written in GO. You noticed that the performance inconsistently degrades at peak load. You could not reproduce this issue on your workstation. You need to continuously monitor the application in production to identify slow paths in the code. You want to minimize performance impact and management overhead. What should you do?
- A. Use Cloud Monitoring to assess the App Engine CPU utilization metric.
- B. Configure Cloud Profiler, and initialize the [email protected]/go/profiler library in the application.
- C. Install a continuous profiling tool into Compute Engine. Configure the application to send profiling data to the tool.
- D. Periodically run the go tool pprof command against the application instance. Analyze the results by using flame graphs.
正解：B
解説：
The correct answer is C. Configure Cloud Profiler, and initialize the cloud.google.com/go/profiler library in the application.
According to the Google Cloud documentation, Cloud Profiler is a statistical, low-overhead profiler that continuously gathers CPU usage and memory-allocation information from your production applications1. Cloud Profiler can help you identify slow paths in your code and optimize the performance of your applications. Cloud Profiler supports applications written in Go that run on App Engine standard environment2. To use Cloud Profiler, you need to configure it in your Google Cloud project and initialize the cloud.google.com/go/profiler library in your application code3. You can then use the Cloud Profiler interface to analyze the profiling data and visualize the results by using flame graphs4. Cloud Profiler has minimal performance impact and management overhead, as it only samples a small fraction of the application activity and does not require any additional infrastructure or agents.
The other options are incorrect because they do not meet the requirements of minimizing performance impact and management overhead. Option A is incorrect because it requires installing a continuous profiling tool into Compute Engine, which is an additional infrastructure that needs to be managed and maintained. Option B is incorrect because it requires periodically running the go tool pprof command against the application instance, which is a manual and disruptive process that can affect the application performance. Option D is incorrect because it only uses Cloud Monitoring to assess the App Engine CPU utilization metric, which is not enough to identify slow paths in the code or optimize the application performance.
Reference:
Cloud Profiler documentation, Overview. Profiling Go applications, Supported environments. Profiling Go applications, Using Cloud Profiler. Analyzing data, Analyzing data.
質問 # 73
You are currently planning how to display Cloud Monitoring metrics for your organization's Google Cloud projects. Your organization has three folders and six projects:
You want to configure Cloud Monitoring dashboards lo only display metrics from the projects within one folder You need to ensure that the dashboards do not display metrics from projects in the other folders You want to follow Google-recommended practices What should you do?
- A. Use the current app-one-dev, app-one-staging and app-one-prod projects as the scoping project for each folder
- B. Create new scoping projects for each folder
- C. Use the current app-one-prod project as the scoping project
- D. Create a single new scoping project
正解：B
解説：
The best option for configuring Cloud Monitoring dashboards to only display metrics from the projects within one folder is to create new scoping projects for each folder. A scoping project is a project that defines which resources are monitored by Cloud Monitoring. You can create new scoping projects for each folder by using the gcloud monitoring register-project command. This way, you can associate each scoping project with a folder and only monitor the resources within that folder. You can then configure Cloud Monitoring dashboards to use the scoping projects as data sources and only display metrics from the projects within one folder.
質問 # 74
......
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。
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