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Google Cloud DevOps Engineer Professional-Cloud-DevOps-Engineer

Professional-Cloud-DevOps-Engineer

Exam Code: Professional-Cloud-DevOps-Engineer

Exam Name: Google Cloud Certified - Professional Cloud DevOps Engineer Exam

Updated: Aug 14, 2026

Q & A: 208 Questions and Answers

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About Google Professional-Cloud-DevOps-Engineer Exam

Who should take the Google Professional Cloud DevOps Engineer exam

Individuals should pursue the Professional Cloud DevOps Engineer practice exam if they want to demonstrate their expertise and ability to design plan, and prototype a GCP DevOps, implement a GCP Virtual Private Cloud (VPC), implement DevOps security. It's perfect for DevOps engineers, systems administrators or operations team members, or simply any professional who wants in on this specific area of IT and cloud.

Reference: https://cloud.google.com/certification/cloud-devops-engineer

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The Google Professional Cloud DevOps Engineer certification is designed to equip the specialists with the expertise required to perform the following technical tasks: applying the principles of site reliability engineering to services, optimizing service performance, implementing the strategies for service monitoring, building and implementing CI/CD pipelines for services, as well as managing service incidents. To get the certificate, the candidates need to complete a single exam covering a wide range of knowledge and skills.

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

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

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