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

Google Professional-Cloud-DevOps-Engineer certification exam is a highly sought-after certification that is designed for IT professionals who want to demonstrate their skills in managing and deploying applications on Google Cloud Platform (GCP). Google Cloud Certified - Professional Cloud DevOps Engineer Exam (Professional-Cloud-DevOps-Engineer日本語版) certification validates the skills and knowledge of individuals in various areas of cloud computing, including DevOps practices, infrastructure automation, continuous delivery, and monitoring and logging.

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

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

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

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