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

  • 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: Sep 04, 2026
  • Q & A: 208 Questions and Answers

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What is the duration, language, and format of Google Professional Cloud DevOps Engineer Exam

  • Format: Multiple choices, multiple select
  • Passing score: 80%
  • Number of Questions: 50-60
  • Length of Examination: 120 minutes
  • Language: English

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

Prerequisites

The Google Professional Cloud DevOps Engineer certification exam is designed for the Application Developers and Programmers who want to learn how to design, develop, and deploy Cloud applications. This test has no formal prerequisites. However, the individuals are recommended to have at least 3 years of industry experience, involving 1 or more years of experience with managing solutions on Google Cloud Platform.

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.

The Google Professional Cloud DevOps Engineer certification is designed to equip the specialists with the expertise required to perform the following technical tasks: applying the principles of site reliability engineering to services, optimizing service performance, implementing the strategies for service monitoring, building and implementing CI/CD pipelines for services, as well as managing service incidents. To get the certificate, the candidates need to complete a single exam covering a wide range of knowledge and skills.

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

SectionWeightObjectives
Topic 1: 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
- Incident management
  • 1. Configuring automated incident response
  • 2. Implementing on-call procedures
  • 3. Post-incident reviews and blameless postmortems
- Monitoring and observability
  • 1. Configuring Cloud Monitoring and Logging
  • 2. Creating dashboards for service health visibility
  • 3. Implementing distributed tracing with Cloud Trace
  • 4. Setting up alerting policies and incident management
Topic 2: Monitoring, Logging, and Debugging12%- Debugging and troubleshooting
  • 1. Debugging with Cloud Trace distributed tracing
  • 2. Analyzing performance profiles with Cloud Profiler
  • 3. Using Cloud Debugger and Error Reporting
- Cloud Operations Suite
  • 1. Configuring Cloud Monitoring metrics
  • 2. Creating uptime checks and alerts
  • 3. Implementing Cloud Logging with log sinks
- Log management
  • 1. Implementing log-based metrics
  • 2. Structuring logs for efficient querying
  • 3. Configuring log retention policies
Topic 3: Cloud Infrastructure Automation24%- Deployment strategies
  • 1. Canary releases and progressive rollouts
  • 2. Blue-green deployments
  • 3. Feature flags with Firebase Remote Config or LaunchDarkly
  • 4. Rolling updates with Kubernetes
- 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
Topic 4: 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. Configuring node pools and auto-scaling
  • 2. Designing Kubernetes cluster architectures
  • 3. Managing pod lifecycle and resource quotas
  • 4. Implementing workload deployment and scaling
- API management
  • 1. Exposing APIs with Cloud Endpoints / Apigee
  • 2. Implementing API versioning strategies
Topic 5: 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. Creating optimized Docker images (multi-stage builds)
  • 2. Managing container registries
  • 3. Implementing container security best practices
- Designing and implementing CI/CD pipelines
  • 1. Implementing build automation scripts
  • 2. Designing pipeline architecture (Cloud Build, Jenkins, GitLab CI, etc.)
  • 3. Configuring build triggers and webhooks
  • 4. Configuring build caching strategies
  • 5. Setting up artifact management with Artifact Registry

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