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Last Updated: Sep 04, 2026

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Google Professional Cloud DevOps Engineer Certification Path

The Google Professional Cloud DevOps Engineer Certification is the highest level of certification mainly focusing on the Solution Architect Professional. There is no prerequisite for this exam but still, it would be best to follow some sequence to prove immense knowledge as a Google Professional Cloud DevOps Engineer.

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

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.

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.

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.

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

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