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

Exam Code: Professional-Cloud-DevOps-Engineer

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

Updated: Aug 06, 2026

Q & A: 208 Questions and Answers

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About Google Professional-Cloud-DevOps-Engineer Exam

How to study the Google Professional Cloud DevOps Engineer Exam

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Exam Details

The qualifying test for the Google Professional Cloud DevOps Engineer certification has the duration of 2 hours. The candidates will be asked to answer around 50 multiple-select and multiple-choice questions. The exam is available in the English language only. The students can take it either as an online proctored test or an onsite proctored exam at an authorized testing center. You can check the location of the nearest center in your region using the search on the official webpage. Each learner is required to pay the registration fee of $200 to schedule the exam.

If you don’t manage to pass the exam on the first try, you can retake it after 14 days. If you don't complete it for the second time, you will be required to wait for 60 days before you can sit for it for the third time. If you fail the third attempt, you will have to wait for 1 year before taking the test again.

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

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Audience for This Certification Exam

The target audience for the Google Professional Cloud DevOps Engineer test is formed of those individuals who want to learn how they can develop efficient operations and find a balance between the speed in delivering services and its reliability. Also, the candidates who are interested in taking this evaluation want to validate their skills in using the Google Cloud Platform at a professional level. Therefore, thanks to such an exam, applicants will learn how to develop pipelines related to software delivery, as well as become experts at monitoring and deploying services, together with managing and learning from them.

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

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