Google Cloud Certified - Professional Cloud DevOps Engineer Exam (Professional-Cloud-DevOps-Engineer日本語版) : Professional-Cloud-DevOps-Engineer日本語

  • Exam Code: Professional-Cloud-DevOps-Engineer日本語
  • Exam Name: Google Cloud Certified - Professional Cloud DevOps Engineer Exam (Professional-Cloud-DevOps-Engineer日本語版)
  • Updated: Sep 11, 2026
  • Q & A: 208 Questions and Answers

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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.

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

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How much Google Professional Cloud DevOps Engineer Exam cost

Google Professional Cloud DevOps Engineer exam cost is USD 200, for more information related to the Google Professional Cloud DevOps Engineer exam, please visit Google Website. Additional costs of Professional Cloud DevOps Engineer exam dumps pdf and Professional Cloud DevOps Engineer practice test are not included in this price.

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.

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

SectionWeightObjectives
CI/CD Pipeline Development26%- CI/CD best practices
  • 1. Configuring quality gates and code coverage
  • 2. Managing secrets in CI/CD pipelines
  • 3. Implementing shift-left testing
- Designing and implementing CI/CD pipelines
  • 1. Configuring build caching strategies
  • 2. Configuring build triggers and webhooks
  • 3. Designing pipeline architecture (Cloud Build, Jenkins, GitLab CI, etc.)
  • 4. Implementing build automation scripts
  • 5. Setting up artifact management with Artifact Registry
- Containerization and Docker
  • 1. Managing container registries
  • 2. Creating optimized Docker images (multi-stage builds)
  • 3. Implementing container security best practices
Reliability and Site Reliability Engineering (SRE)24%- SLOs, SLIs, and SLAs
  • 1. Creating and interpreting Service Level Indicators
  • 2. Setting appropriate Service Level Agreements
  • 3. Defining and implementing Service Level Objectives
  • 4. Error budget policies and management
- Monitoring and observability
  • 1. Creating dashboards for service health visibility
  • 2. Setting up alerting policies and incident management
  • 3. Implementing distributed tracing with Cloud Trace
  • 4. Configuring Cloud Monitoring and Logging
- Incident management
  • 1. Configuring automated incident response
  • 2. Implementing on-call procedures
  • 3. Post-incident reviews and blameless postmortems
Cloud Infrastructure Automation24%- Infrastructure as Code (IaC)
  • 1. Implementing immutable infrastructure patterns
  • 2. Managing infrastructure modules and state
  • 3. Implementing with Terraform
- Configuration management
  • 1. Using Ansible for configuration management
  • 2. Implementing configuration drift detection
  • 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
Monitoring, Logging, and Debugging12%- Log management
  • 1. Structuring logs for efficient querying
  • 2. Implementing log-based metrics
  • 3. Configuring log retention policies
- 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. Analyzing performance profiles with Cloud Profiler
  • 2. Using Cloud Debugger and Error Reporting
  • 3. Debugging with Cloud Trace distributed tracing
Microservices Architecture14%- API management
  • 1. Implementing API versioning strategies
  • 2. Exposing APIs with Cloud Endpoints / Apigee
- 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. Implementing workload deployment and scaling
  • 2. Managing pod lifecycle and resource quotas
  • 3. Configuring node pools and auto-scaling
  • 4. Designing Kubernetes cluster architectures

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