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

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The target audience for the Google Professional Cloud DevOps Engineer test is formed of those individuals who want to learn how they can develop efficient operations and find a balance between the speed in delivering services and its reliability. Also, the candidates who are interested in taking this evaluation want to validate their skills in using the Google Cloud Platform at a professional level. Therefore, thanks to such an exam, applicants will learn how to develop pipelines related to software delivery, as well as become experts at monitoring and deploying services, together with managing and learning from them.

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

SectionWeightObjectives
Topic 1: Monitoring, Logging, and Debugging12%- 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. 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
Topic 2: 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. Implementing immutable infrastructure patterns
  • 2. Managing infrastructure modules and state
  • 3. Implementing with Terraform
- Deployment strategies
  • 1. Rolling updates with Kubernetes
  • 2. Feature flags with Firebase Remote Config or LaunchDarkly
  • 3. Canary releases and progressive rollouts
  • 4. Blue-green deployments
Topic 3: CI/CD Pipeline Development26%- Designing and implementing CI/CD pipelines
  • 1. Configuring build caching strategies
  • 2. Implementing build automation scripts
  • 3. Setting up artifact management with Artifact Registry
  • 4. Designing pipeline architecture (Cloud Build, Jenkins, GitLab CI, etc.)
  • 5. Configuring build triggers and webhooks
- Containerization and Docker
  • 1. Creating optimized Docker images (multi-stage builds)
  • 2. Managing container registries
  • 3. Implementing container security best practices
- CI/CD best practices
  • 1. Implementing shift-left testing
  • 2. Configuring quality gates and code coverage
  • 3. Managing secrets in CI/CD pipelines
Topic 4: Microservices Architecture14%- Service mesh and networking
  • 1. Implementing service-to-service authentication
  • 2. Implementing Anthos Service Mesh / Istio
  • 3. Configuring traffic management and load balancing
- API management
  • 1. Exposing APIs with Cloud Endpoints / Apigee
  • 2. Implementing API versioning strategies
- Container orchestration with GKE
  • 1. Configuring node pools and auto-scaling
  • 2. Managing pod lifecycle and resource quotas
  • 3. Implementing workload deployment and scaling
  • 4. Designing Kubernetes cluster architectures
Topic 5: Reliability and Site Reliability Engineering (SRE)24%- Incident management
  • 1. Post-incident reviews and blameless postmortems
  • 2. Configuring automated incident response
  • 3. Implementing on-call procedures
- SLOs, SLIs, and SLAs
  • 1. Defining and implementing Service Level Objectives
  • 2. Creating and interpreting Service Level Indicators
  • 3. Setting appropriate Service Level Agreements
  • 4. Error budget policies and management
- Monitoring and observability
  • 1. Implementing distributed tracing with Cloud Trace
  • 2. Configuring Cloud Monitoring and Logging
  • 3. Setting up alerting policies and incident management
  • 4. Creating dashboards for service health visibility

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