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Google Professional-Cloud-DevOps-Engineer Exam Syllabus Topics:

SectionWeightObjectives
Implementing observability and troubleshooting20%- 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
- Optimize observability strategy
  • 1. Integrate observability into development
  • 2. Scale monitoring for large environments
  • 3. Reduce noise and prioritize signals
- Troubleshoot complex issues
  • 1. Analyze performance and latency
  • 2. Isolate problems across layers
  • 3. Trace requests end-to-end
Building and implementing CI/CD pipelines25%- Implement and secure pipelines
  • 1. Manage pipeline secrets and credentials
  • 2. Enforce security scanning and compliance checks
  • 3. Automate build, test, and deployment stages
- Design CI/CD pipelines
  • 1. Integrate artifact management
  • 2. Plan pipelines for apps, infrastructure, ML workloads
  • 3. Support hybrid/multi-cloud deployment
- Optimize and maintain pipelines
  • 1. Handle rollbacks and versioning
  • 2. Monitor pipeline performance
  • 3. Improve speed and reliability
Optimizing performance and cost17%- Apply FinOps practices
  • 1. Use spot instances and committed use discounts
  • 2. Right-size resources and eliminate waste
  • 3. Monitor and analyze cloud costs
- Improve system performance
  • 1. Optimize resource allocation
  • 2. Tune applications and infrastructure
  • 3. Use caching and content delivery
- Balance cost, performance, and reliability
  • 1. Make tradeoff decisions based on data
  • 2. Plan capacity and scaling
  • 3. Optimize over time
Applying site reliability engineering practices18%- Manage incidents and outages
  • 1. Detect and respond to issues quickly
  • 2. Implement improvements to prevent recurrence
  • 3. Perform postmortems and root cause analysis
- Design for resilience
  • 1. Test failure scenarios and recovery
  • 2. Automate remediation and self-healing
  • 3. Plan redundancy and fault tolerance
- Define reliability goals
  • 1. Align reliability with business needs
  • 2. Use error budgets to balance change and stability
  • 3. Establish SLIs, SLOs, SLAs
Bootstrapping and maintaining a Google Cloud organization20%- Manage configuration and deployment
  • 1. Use Infrastructure as Code tools
  • 2. Automate resource provisioning
  • 3. Enforce consistency across environments
- Set up governance and compliance
  • 1. Implement organization policies
  • 2. Configure audit logging and monitoring
  • 3. Manage resource quotas and limits
- Design resource hierarchy
  • 1. Plan shared networking and connectivity
  • 2. Organize resources by project/folder/application
  • 3. Define IAM policies and access control

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q27-Q32):

NEW QUESTION # 27
Your company operates in a highly regulated domain that requires you to store all organization logs for seven years You want to minimize logging infrastructure complexity by using managed services You need to avoid any future loss of log capture or stored logs due to misconfiguration or human error What should you do?

Answer: B


NEW QUESTION # 28
Your company runs services by using Google Kubernetes Engine (GKE). The GKE clusters in the development environment run applications with verbose logging enabled. Developers view logs by using the kubect1 logs command and do not use Cloud Logging. Applications do not have a uniform logging structure defined. You need to minimize the costs associated with application logging while still collecting GKE operational logs.
What should you do?

Answer: A


NEW QUESTION # 29
You are building and deploying a microservice on Cloud Run for your organization Your service is used by many applications internally You are deploying a new release, and you need to test the new version extensively in the staging and production environments You must minimize user and developer impact. What should you do?

Answer: B

Explanation:
The best option for deploying a new release of your microservice on Cloud Run and testing it extensively in the staging and production environments with minimal user and developer impact is to deploy the new version of the service to the staging environment with a new-release tag without serving traffic, test the new-release version, and if the test passes, gradually roll out this tagged version. A tag is a label that you can assign to a revision of your service on Cloud Run. You can use tags to create different versions of your service without affecting traffic. You can also use tags to gradually roll out traffic to a new version of your service by using traffic splitting. This way, you can test your new release extensively in both environments and minimize user and developer impact.


NEW QUESTION # 30
You have an application running in Google Kubernetes Engine. The application invokes multiple services per request but responds too slowly. You need to identify which downstream service or services are causing the delay. What should you do?

Answer: A


NEW QUESTION # 31
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?

Answer: A

Explanation:
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.


NEW QUESTION # 32
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