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

Professional-Cloud-DevOps-Engineer日本語 real exams

Exam Code: Professional-Cloud-DevOps-Engineer-JPN

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

Updated: Jul 17, 2026

Q & A: 208 Questions and Answers

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About Google Professional-Cloud-DevOps-Engineer日本語 Exam

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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.

Introduction to Google Professional Cloud DevOps Engineer Exam

Google Professional Cloud DevOps Engineer Exam is a certification exam that is conducted by Google to validates candidate knowledge and skills of working as a Professional Cloud DevOps engineer in the IT industry.

After passing this Professional Cloud DevOps Engineer Exam test, candidates get a certificate from Google that helps them to demonstrate their proficiency in Google Professional Cloud DevOps Engineer to their clients and employers.

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

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:

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

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.

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

SectionWeightObjectives
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. Configuring Cloud Monitoring metrics
  • 3. Creating uptime checks and alerts
- Debugging and troubleshooting
  • 1. Using Cloud Debugger and Error Reporting
  • 2. Analyzing performance profiles with Cloud Profiler
  • 3. Debugging with Cloud Trace distributed tracing
CI/CD Pipeline Development26%- Containerization and Docker
  • 1. Implementing container security best practices
  • 2. Creating optimized Docker images (multi-stage builds)
  • 3. Managing container registries
- 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. Setting up artifact management with Artifact Registry
  • 2. Implementing build automation scripts
  • 3. Configuring build caching strategies
  • 4. Configuring build triggers and webhooks
  • 5. Designing pipeline architecture (Cloud Build, Jenkins, GitLab CI, etc.)
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 with Terraform
  • 2. Managing infrastructure modules and state
  • 3. Implementing immutable infrastructure patterns
- Configuration management
  • 1. Managing secrets with Secret Manager
  • 2. Using Ansible for configuration management
  • 3. Implementing configuration drift detection
Microservices Architecture14%- 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
- Container orchestration with GKE
  • 1. Managing pod lifecycle and resource quotas
  • 2. Implementing workload deployment and scaling
  • 3. Designing Kubernetes cluster architectures
  • 4. Configuring node pools and auto-scaling
Reliability and Site Reliability Engineering (SRE)24%- Incident management
  • 1. Configuring automated incident response
  • 2. Implementing on-call procedures
  • 3. Post-incident reviews and blameless postmortems
- SLOs, SLIs, and SLAs
  • 1. Creating and interpreting Service Level Indicators
  • 2. Defining and implementing Service Level Objectives
  • 3. Setting appropriate Service Level Agreements
  • 4. Error budget policies and management
- Monitoring and observability
  • 1. Configuring Cloud Monitoring and Logging
  • 2. Creating dashboards for service health visibility
  • 3. Setting up alerting policies and incident management
  • 4. Implementing distributed tracing with Cloud Trace

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