Google Cloud Certified - Professional Cloud DevOps Engineer : Professional-Cloud-DevOps-Engineer exam

Professional-Cloud-DevOps-Engineer
  • Exam Code: Professional-Cloud-DevOps-Engineer
  • Exam Name: Google Cloud Certified - Professional Cloud DevOps Engineer Exam
  • Updated: Sep 12, 2026
  • Q & A: 208 Questions and Answers

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The Google Professional Cloud DevOps Engineer exam is taken by the specialists who want to obtain international certification and get validated as professional engineers who can manage Cloud DevOps features.

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.

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

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

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

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