Professional-Cloud-DevOps-Engineer受験対策 & Professional-Cloud-DevOps-Engineer試験時間

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Google Professional-Cloud-DevOps-Engineer Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|
| Topic 1: Optimizing performance and cost | 17% | - Apply FinOps practices
- 1. Right-size resources and eliminate waste
- 2. Monitor and analyze cloud costs
- 3. Use spot instances and committed use discounts
- Balance cost, performance, and reliability
- 1. Make tradeoff decisions based on data
- 2. Plan capacity and scaling
- 3. Optimize over time
- Improve system performance
- 1. Optimize resource allocation
- 2. Use caching and content delivery
- 3. Tune applications and infrastructure
|
| Topic 2: Bootstrapping and maintaining a Google Cloud organization | 20% | - Set up governance and compliance
- 1. Configure audit logging and monitoring
- 2. Manage resource quotas and limits
- 3. Implement organization policies
- Manage configuration and deployment
- 1. Use Infrastructure as Code tools
- 2. Automate resource provisioning
- 3. Enforce consistency across environments
- Design resource hierarchy
- 1. Plan shared networking and connectivity
- 2. Define IAM policies and access control
- 3. Organize resources by project/folder/application
|
| Topic 3: Applying site reliability engineering practices | 18% | - Define reliability goals
- 1. Align reliability with business needs
- 2. Establish SLIs, SLOs, SLAs
- 3. Use error budgets to balance change and stability
- Design for resilience
- 1. Automate remediation and self-healing
- 2. Plan redundancy and fault tolerance
- 3. Test failure scenarios and recovery
- Manage incidents and outages
- 1. Detect and respond to issues quickly
- 2. Perform postmortems and root cause analysis
- 3. Implement improvements to prevent recurrence
|
| Topic 4: Building and implementing CI/CD pipelines | 25% | - Optimize and maintain pipelines
- 1. Handle rollbacks and versioning
- 2. Improve speed and reliability
- 3. Monitor pipeline performance
- Implement and secure pipelines
- 1. Enforce security scanning and compliance checks
- 2. Automate build, test, and deployment stages
- 3. Manage pipeline secrets and credentials
- Design CI/CD pipelines
- 1. Plan pipelines for apps, infrastructure, ML workloads
- 2. Support hybrid/multi-cloud deployment
- 3. Integrate artifact management
|
| Topic 5: Implementing observability and troubleshooting | 20% | - Troubleshoot complex issues
- 1. Trace requests end-to-end
- 2. Isolate problems across layers
- 3. Analyze performance and latency
- Optimize observability strategy
- 1. Reduce noise and prioritize signals
- 2. Integrate observability into development
- 3. Scale monitoring for large environments
- Build monitoring and logging systems
- 1. Create dashboards and alerts
- 2. Use Cloud Monitoring, Cloud Logging, Cloud Trace
- 3. Collect and analyze metrics, logs, traces
|
>> Professional-Cloud-DevOps-Engineer受験対策 <<
Professional-Cloud-DevOps-Engineer試験時間、Professional-Cloud-DevOps-Engineer学習教材
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Google Cloud Certified - Professional Cloud DevOps Engineer Exam 認定 Professional-Cloud-DevOps-Engineer 試験問題 (Q108-Q113):
質問 # 108
You manage an application that runs in Google Kubernetes Engine (GKE) and uses the blue/green deployment methodology Extracts of the Kubernetes manifests are shown below

The Deployment app-green was updated to use the new version of the application During post-deployment monitoring you notice that the majority of user requests are failing You did not observe this behavior in the testing environment You need to mitigate the incident impact on users and enable the developers to troubleshoot the issue What should you do?
- A. Change the selector on the Service app-svc to app: my-app, version: blue
- B. Change the selector on the Service app-2vc to app: my-app.
- C. Update the Deployment ape-green to use the previous version of the application
- D. Update the Deployment app-blue to use the new version of the application
正解:A
解説:
Explanation
The best option for mitigating the incident impact on users and enabling the developers to troubleshoot the issue is to change the selector on the Service app-svc to app: my-app, version: blue. A Service is a resource that defines how to access a set of Pods. A selector is a field that specifies which Pods are selected by the Service. By changing the selector on the Service app-svc to app: my-app, version: blue, you can ensure that the Service only routes traffic to the Pods that have both labels app: my-app and version: blue. These Pods belong to the Deployment app-blue, which uses the previous version of the application. This way, you can mitigate the incident impact on users by switching back to the working version of the application. You can also enable the developers to troubleshoot the issue with the new version of the application in the Deployment app-green without affecting users.
質問 # 109
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. Create new scoping projects for each folder
- B. Use the current app-one-prod project as the scoping project
- C. Use the current app-one-dev, app-one-staging and app-one-prod projects as the scoping project for each folder
- D. Create a single new scoping project
正解:A
解説:
Explanation
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 # 110
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. 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.
- B. 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.
- 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:B
質問 # 111
Your application images are built and pushed to Google Container Registry (GCR). You want to build an automated pipeline that deploys the application when the image is updated while minimizing the development effort. What should you do?
- A. Use Cloud Pub/Sub to trigger a custom deployment service running in Google Kubernetes Engine (GKE).
- B. Use Cloud Pub/Sub to trigger a Spinnaker pipeline.
- C. Use a custom builder in Cloud Build to trigger a Jenkins pipeline.
- D. Use Cloud Build to trigger a Spinnaker pipeline.
正解:B
解説:
Explanation
https://cloud.google.com/architecture/continuous-delivery-toolchain-spinnaker-cloud
https://spinnaker.io/guides/user/pipeline/triggers/pubsub/
The most efficient way to build an automated pipeline that deploys the application when the image is updated is to use Cloud Pub/Sub to trigger a Spinnaker pipeline. This way, you can leverage the built-in integration between GCR and Cloud Pub/Sub, and use Spinnaker as a continuous delivery platform for deploying your application .
質問 # 112
You are configuring a CI pipeline. The build step for your CI pipeline integration testing requires access to APIs inside your private VPC network. Your security team requires that you do not expose API traffic publicly. You need to implement a solution that minimizes management overhead. What should you do?
- A. Use Cloud Build to create a Compute Engine instance in the private VPC. Run the integration tests on the VM by using a startup script.
- B. Use Cloud Build as a pipeline runner. Configure a global external Application Load Balancer with a Google Cloud Armor policy for API access.
- C. Use Cloud Build private pools to connect to the private VPC.
- D. Use Cloud Build as a pipeline runner. Configure a cross-region internal Application Load Balancer for API access.
正解:C
解説:
Cloud Build Private Pools allow your builds to run in a secure, isolated environment with direct access to resources inside your private VPC network, without exposing them to the public internet. This is the Google- recommended approach for minimizing management overhead while maintaining strong security boundaries.
From the official documentation:
"Private pools run your builds in a dedicated and secure environment that can connect to private network resources."
- Cloud Build Private Pools Overview
"You can configure private pools to access resources in a VPC network, which enables secure access to services without using public IPs."
- Accessing Private Resources
This method eliminates the need to create and manage additional compute instances or complex load balancing setups, providing seamless integration with your private services during CI pipeline execution.
質問 # 113
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