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Google Professional-Cloud-DevOps-Engineer certification exam is intended for professionals who have experience in software development, systems operations, and infrastructure management. Professional-Cloud-DevOps-Engineer exam covers a wide range of topics, including building and deploying applications, managing services, monitoring and logging, and optimizing performance. Successful candidates will have a solid understanding of DevOps principles and practices, as well as the ability to design and implement cloud-based solutions using Google Cloud Platform.

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

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Google Professional-Cloud-DevOps-Engineer exam is a certification program designed to validate the skills and knowledge of professionals in the field of DevOps engineering on the Google Cloud Platform. Professional-Cloud-DevOps-Engineer exam is intended for individuals who are experienced in DevOps practices and have expertise in designing, building, and maintaining scalable and reliable cloud solutions.

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

SectionWeightObjectives
Cloud Infrastructure Automation24%- Configuration management
  • 1. Implementing configuration drift detection
  • 2. Using Ansible for configuration management
  • 3. Managing secrets with Secret Manager
- Deployment strategies
  • 1. Rolling updates with Kubernetes
  • 2. Blue-green deployments
  • 3. Canary releases and progressive rollouts
  • 4. Feature flags with Firebase Remote Config or LaunchDarkly
- Infrastructure as Code (IaC)
  • 1. Implementing immutable infrastructure patterns
  • 2. Implementing with Terraform
  • 3. Managing infrastructure modules and state
Reliability and Site Reliability Engineering (SRE)24%- Monitoring and observability
  • 1. Setting up alerting policies and incident management
  • 2. Implementing distributed tracing with Cloud Trace
  • 3. Configuring Cloud Monitoring and Logging
  • 4. Creating dashboards for service health visibility
- SLOs, SLIs, and SLAs
  • 1. Defining and implementing Service Level Objectives
  • 2. Setting appropriate Service Level Agreements
  • 3. Creating and interpreting Service Level Indicators
  • 4. Error budget policies and management
- Incident management
  • 1. Implementing on-call procedures
  • 2. Configuring automated incident response
  • 3. Post-incident reviews and blameless postmortems
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. Implementing Cloud Logging with log sinks
  • 2. Configuring Cloud Monitoring metrics
  • 3. Creating uptime checks and alerts
- Log management
  • 1. Implementing log-based metrics
  • 2. Structuring logs for efficient querying
  • 3. Configuring log retention policies
Microservices Architecture14%- Container orchestration with GKE
  • 1. Configuring node pools and auto-scaling
  • 2. Designing Kubernetes cluster architectures
  • 3. Implementing workload deployment and scaling
  • 4. Managing pod lifecycle and resource quotas
- Service mesh and networking
  • 1. Implementing service-to-service authentication
  • 2. Configuring traffic management and load balancing
  • 3. Implementing Anthos Service Mesh / Istio
- API management
  • 1. Implementing API versioning strategies
  • 2. Exposing APIs with Cloud Endpoints / Apigee
CI/CD Pipeline Development26%- Designing and implementing CI/CD pipelines
  • 1. Configuring build triggers and webhooks
  • 2. Configuring build caching strategies
  • 3. Implementing build automation scripts
  • 4. Setting up artifact management with Artifact Registry
  • 5. Designing pipeline architecture (Cloud Build, Jenkins, GitLab CI, etc.)
- 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. Implementing shift-left testing
  • 3. Managing secrets in CI/CD pipelines

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