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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.

Introduction to Google Professional Cloud DevOps Engineer Exam

Google Professional Cloud DevOps Engineer Exam is a certification exam that is conducted by Google to validates candidate knowledge and skills of working as a Professional Cloud DevOps engineer in the IT industry.

After passing this Professional Cloud DevOps Engineer Exam test, candidates get a certificate from Google that helps them to demonstrate their proficiency in Google Professional Cloud DevOps Engineer to their clients and employers.

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Exam Details

The qualifying test for the Google Professional Cloud DevOps Engineer certification has the duration of 2 hours. The candidates will be asked to answer around 50 multiple-select and multiple-choice questions. The exam is available in the English language only. The students can take it either as an online proctored test or an onsite proctored exam at an authorized testing center. You can check the location of the nearest center in your region using the search on the official webpage. Each learner is required to pay the registration fee of $200 to schedule the exam.

If you don’t manage to pass the exam on the first try, you can retake it after 14 days. If you don't complete it for the second time, you will be required to wait for 60 days before you can sit for it for the third time. If you fail the third attempt, you will have to wait for 1 year before taking the test again.

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

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

SectionWeightObjectives
Topic 1: Microservices Architecture14%- API management
  • 1. Implementing API versioning strategies
  • 2. Exposing APIs with Cloud Endpoints / Apigee
- Service mesh and networking
  • 1. Implementing service-to-service authentication
  • 2. Implementing Anthos Service Mesh / Istio
  • 3. Configuring traffic management and load balancing
- Container orchestration with GKE
  • 1. Configuring node pools and auto-scaling
  • 2. Implementing workload deployment and scaling
  • 3. Designing Kubernetes cluster architectures
  • 4. Managing pod lifecycle and resource quotas
Topic 2: 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. Managing container registries
  • 2. Implementing container security best practices
  • 3. Creating optimized Docker images (multi-stage builds)
- Designing and implementing CI/CD pipelines
  • 1. Configuring build triggers and webhooks
  • 2. Configuring build caching strategies
  • 3. Designing pipeline architecture (Cloud Build, Jenkins, GitLab CI, etc.)
  • 4. Setting up artifact management with Artifact Registry
  • 5. Implementing build automation scripts
Topic 3: Reliability and Site Reliability Engineering (SRE)24%- Monitoring and observability
  • 1. Creating dashboards for service health visibility
  • 2. Setting up alerting policies and incident management
  • 3. Implementing distributed tracing with Cloud Trace
  • 4. Configuring Cloud Monitoring and Logging
- Incident management
  • 1. Post-incident reviews and blameless postmortems
  • 2. Implementing on-call procedures
  • 3. Configuring automated incident response
- SLOs, SLIs, and SLAs
  • 1. Error budget policies and management
  • 2. Creating and interpreting Service Level Indicators
  • 3. Defining and implementing Service Level Objectives
  • 4. Setting appropriate Service Level Agreements
Topic 4: Monitoring, Logging, and Debugging12%- Log management
  • 1. Configuring log retention policies
  • 2. Structuring logs for efficient querying
  • 3. Implementing log-based metrics
- Cloud Operations Suite
  • 1. Implementing Cloud Logging with log sinks
  • 2. Creating uptime checks and alerts
  • 3. Configuring Cloud Monitoring metrics
- Debugging and troubleshooting
  • 1. Using Cloud Debugger and Error Reporting
  • 2. Analyzing performance profiles with Cloud Profiler
  • 3. Debugging with Cloud Trace distributed tracing
Topic 5: Cloud Infrastructure Automation24%- Deployment strategies
  • 1. Blue-green deployments
  • 2. Rolling updates with Kubernetes
  • 3. Feature flags with Firebase Remote Config or LaunchDarkly
  • 4. Canary releases and progressive rollouts
- Configuration management
  • 1. Implementing configuration drift detection
  • 2. Managing secrets with Secret Manager
  • 3. Using Ansible for configuration management
- Infrastructure as Code (IaC)
  • 1. Implementing with Terraform
  • 2. Managing infrastructure modules and state
  • 3. Implementing immutable infrastructure patterns

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