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

SectionWeightObjectives
Topic 1: Cloud Infrastructure Automation24%- Infrastructure as Code (IaC)
  • 1. Managing infrastructure modules and state
  • 2. Implementing immutable infrastructure patterns
  • 3. Implementing with Terraform
- Configuration management
  • 1. Using Ansible for configuration management
  • 2. Managing secrets with Secret Manager
  • 3. Implementing configuration drift detection
- Deployment strategies
  • 1. Canary releases and progressive rollouts
  • 2. Blue-green deployments
  • 3. Rolling updates with Kubernetes
  • 4. Feature flags with Firebase Remote Config or LaunchDarkly
Topic 2: Reliability and Site Reliability Engineering (SRE)24%- SLOs, SLIs, and SLAs
  • 1. Creating and interpreting Service Level Indicators
  • 2. Setting appropriate Service Level Agreements
  • 3. Error budget policies and management
  • 4. Defining and implementing Service Level Objectives
- Incident management
  • 1. Configuring automated incident response
  • 2. Implementing on-call procedures
  • 3. Post-incident reviews and blameless postmortems
- Monitoring and observability
  • 1. Implementing distributed tracing with Cloud Trace
  • 2. Creating dashboards for service health visibility
  • 3. Setting up alerting policies and incident management
  • 4. Configuring Cloud Monitoring and Logging
Topic 3: Monitoring, Logging, and Debugging12%- Cloud Operations Suite
  • 1. Configuring Cloud Monitoring metrics
  • 2. Creating uptime checks and alerts
  • 3. Implementing Cloud Logging with log sinks
- Log management
  • 1. Structuring logs for efficient querying
  • 2. Implementing log-based metrics
  • 3. Configuring log retention policies
- Debugging and troubleshooting
  • 1. Debugging with Cloud Trace distributed tracing
  • 2. Using Cloud Debugger and Error Reporting
  • 3. Analyzing performance profiles with Cloud Profiler
Topic 4: Microservices Architecture14%- Service mesh and networking
  • 1. Implementing Anthos Service Mesh / Istio
  • 2. Configuring traffic management and load balancing
  • 3. Implementing service-to-service authentication
- Container orchestration with GKE
  • 1. Designing Kubernetes cluster architectures
  • 2. Implementing workload deployment and scaling
  • 3. Managing pod lifecycle and resource quotas
  • 4. Configuring node pools and auto-scaling
- API management
  • 1. Exposing APIs with Cloud Endpoints / Apigee
  • 2. Implementing API versioning strategies
Topic 5: CI/CD Pipeline Development26%- Designing and implementing CI/CD pipelines
  • 1. Configuring build triggers and webhooks
  • 2. Implementing build automation scripts
  • 3. Setting up artifact management with Artifact Registry
  • 4. Designing pipeline architecture (Cloud Build, Jenkins, GitLab CI, etc.)
  • 5. Configuring build caching strategies
- Containerization and Docker
  • 1. Implementing container security best practices
  • 2. Managing container registries
  • 3. Creating optimized Docker images (multi-stage builds)
- CI/CD best practices
  • 1. Managing secrets in CI/CD pipelines
  • 2. Implementing shift-left testing
  • 3. Configuring quality gates and code coverage

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q53-Q58):

NEW QUESTION # 53
You are developing reusable infrastructure as code modules. Each module contains integration tests that launch the module in a test project. You are using GitHub for source control. You need to Continuously test your feature branch and ensure that all code is tested before changes are accepted. You need to implement a solution to automate the integration tests. What should you do?

Answer: A

Explanation:
Explanation
Cloud Build is a service that executes your builds on Google Cloud Platform infrastructure. Cloud Build can import source code from Google Cloud Storage, Cloud Source Repositories, GitHub, or Bitbucket, execute a build to your specifications, and produce artifacts such as Docker containers or Java archives1. Cloud Build can also run integration tests as part of your build steps2.
You can use Cloud Build to run tests in a specific folder by specifying the path to the folder in the dir field of your build step3. For example, if you have a folder named tests that contains your integration tests, you can use the following build step to run them:
steps:
- name: 'gcr.io/cloud-builders/go'
args: ['test', '-v']
dir: 'tests'
Copy
You can use Cloud Build to trigger builds for every GitHub pull request by using the Cloud Build GitHub app. The app allows you to automatically build on Git pushes and pull requests and view your build results on GitHub and Google Cloud console4. You can configure the app to run builds on specific branches, tags, or paths5. For example, if you want to run builds on pull requests that target the master branch, you can use the following trigger configuration:
includedFiles:
- '**'
name: 'pull-request-trigger'
github:
name: 'my-repo'
owner: 'my-org'
pullRequest:
branch: '

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