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

Google Professional-Cloud-DevOps-Engineer (Google Cloud Certified - Professional Cloud DevOps Engineer) Exam is designed for professionals who have expertise in DevOps practices and technologies in the Google Cloud Platform. Google Cloud Certified - Professional Cloud DevOps Engineer Exam (Professional-Cloud-DevOps-Engineer日本語版) certification validates the knowledge and skills required to design, develop, and implement DevOps processes and practices on Google Cloud Platform. Professional-Cloud-DevOps-Engineer-JPN exam covers a wide range of topics including continuous integration and delivery, infrastructure as code, monitoring and logging, and site reliability engineering. It is ideal for DevOps engineers, site reliability engineers, automation engineers, and cloud architects who work with Google Cloud Platform.

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

SectionWeightObjectives
Topic 1: Applying site reliability engineering practices18%- Design for resilience
  • 1. Automate remediation and self-healing
  • 2. Plan redundancy and fault tolerance
  • 3. Test failure scenarios and recovery
- Manage incidents and outages
  • 1. Perform postmortems and root cause analysis
  • 2. Detect and respond to issues quickly
  • 3. Implement improvements to prevent recurrence
- Define reliability goals
  • 1. Use error budgets to balance change and stability
  • 2. Align reliability with business needs
  • 3. Establish SLIs, SLOs, SLAs
Topic 2: Building and implementing CI/CD pipelines25%- Design CI/CD pipelines
  • 1. Integrate artifact management
  • 2. Plan pipelines for apps, infrastructure, ML workloads
  • 3. Support hybrid/multi-cloud deployment
- Implement and secure pipelines
  • 1. Enforce security scanning and compliance checks
  • 2. Manage pipeline secrets and credentials
  • 3. Automate build, test, and deployment stages
- Optimize and maintain pipelines
  • 1. Monitor pipeline performance
  • 2. Handle rollbacks and versioning
  • 3. Improve speed and reliability
Topic 3: Implementing observability and troubleshooting20%- Troubleshoot complex issues
  • 1. Isolate problems across layers
  • 2. Trace requests end-to-end
  • 3. Analyze performance and latency
- Optimize observability strategy
  • 1. Scale monitoring for large environments
  • 2. Reduce noise and prioritize signals
  • 3. Integrate observability into development
- Build monitoring and logging systems
  • 1. Collect and analyze metrics, logs, traces
  • 2. Create dashboards and alerts
  • 3. Use Cloud Monitoring, Cloud Logging, Cloud Trace
Topic 4: Bootstrapping and maintaining a Google Cloud organization20%- Design resource hierarchy
  • 1. Define IAM policies and access control
  • 2. Organize resources by project/folder/application
  • 3. Plan shared networking and connectivity
- Manage configuration and deployment
  • 1. Automate resource provisioning
  • 2. Enforce consistency across environments
  • 3. Use Infrastructure as Code tools
- Set up governance and compliance
  • 1. Configure audit logging and monitoring
  • 2. Implement organization policies
  • 3. Manage resource quotas and limits
Topic 5: Optimizing performance and cost17%- Balance cost, performance, and reliability
  • 1. Optimize over time
  • 2. Make tradeoff decisions based on data
  • 3. Plan capacity and scaling
- Improve system performance
  • 1. Use caching and content delivery
  • 2. Optimize resource allocation
  • 3. Tune applications and infrastructure
- Apply FinOps practices
  • 1. Use spot instances and committed use discounts
  • 2. Monitor and analyze cloud costs
  • 3. Right-size resources and eliminate waste

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