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

Professional-Cloud-DevOps-Engineer real exams

Exam Code: Professional-Cloud-DevOps-Engineer

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

Updated: Jul 28, 2026

Q & A: 208 Questions and Answers

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About Google Professional-Cloud-DevOps-Engineer Exam Collection

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Domains Tested in Final Evaluation

The candidates who succeed in passing the Google Professional Cloud DevOps Engineer validation will add an international designation under their belt that helps them consolidate their position in the company and receive generous offers from their employers. So, if applicants want to differentiate themselves from other colleagues, they should demonstrate the following skills:

  • Coordinating teams to identify and manage incidents related to service development.
  • Identifying issues related to service performance and implementing solutions to optimize it;
  • Checking and implementing strategies related to service monitoring;
  • Identifying the most effective principles related to site reliability engineering and applying them to a definite service;
  • Implementing and building CI/CD service pipelines;

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.

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

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For more info visit:

CCIE to Google Cloud DevOps Engineer Google cloud DevOps engineer practice exam Google Cloud documentation Google Cloud solutions

Test Structure

The candidates who want to take this Google exam will have two hours to answer all questions. Even though the vendor doesn’t give details on the total number of questions that the examinees will receive, they should be prepared to solve multiple-choice and multiple-answer inquiries. Besides, the test is delivered in the English language only. As for the registration fee, the test-takers will need to pay $200 to take it. Additional taxes may apply depending on the candidate’s profile and chosen delivery method. By and large, the applicants have two options to take the official exam. They can choose to take it online from any remote location that they prefer. If they choose this option, the candidates should read carefully what the testing requirements are. In case applicants prefer to be present in a classroom when they take the actual testing, then they can search for a test center that is closest to their location. Also, Google doesn’t have any prerequisites for the candidates to be eligible for the evaluation. Still, it recommends that the candidates for the Professional Cloud DevOps Engineer exam should have at least 3 years of experience in the industry including a minimum of one year of experience in managing and developing solutions on GCP.

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

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

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