Google Cloud Professional Cloud DevOps Engineer Certification Logo

Google Cloud Professional Cloud DevOps Engineer Certification

The Professional Cloud DevOps Engineer certification validates your ability to design, build, and maintain robust CI/CD pipelines, apply site reliability engineering (SRE) practices, ensure observability, and optimize the performance of applications and infrastructure on Google Cloud Platform (GCP).

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What is Google Cloud Professional Cloud DevOps Engineer Certification about?

  • Implementing DevOps processes across the full software lifecycle using recommended practices and tools
  • Balancing delivery speed with system reliability
  • Building and maintaining CI/CD pipelines (for apps and infrastructure)
  • Applying SRE principles (SLIs, SLOs, error budgets, incident management)
  • Observability: logging, monitoring, alerting, dashboards
  • Performance tuning, troubleshooting, and operational excellence on GCP

What are the objectives of Google Cloud Professional Cloud DevOps Engineer Certification ?

  • Bootstrap & Maintain a GCP Organization for DevOps — design resource hierarchies, set up IAM, manage infrastructure as code
  • Build and Implement CI/CD Pipelines — design, deploy, and manage software & infrastructure pipelines with GCP and hybrid tools
  • Apply SRE/DevOps Principles — define SLIs/SLOs, manage error budgets, handle incidents, adopt reliability best practices
  • Implement Observability & Monitoring — use logging, metrics, dashboards, alerts across services
  • Optimize and Troubleshoot Performance — identify bottlenecks, tune resource usage, address issues in deployed systems
  • Ensure the Security and Integrity of the Pipeline — manage secrets, enforce least privilege, ensure supply chain security

Who is Google Cloud Professional Cloud DevOps Engineer Certification for?

  • DevOps engineers or site reliability engineers working on Google Cloud
  • Cloud engineers who own CI/CD, deployment, and operations responsibilities
  • Professionals who maintain production systems and want to validate expertise
  • Architects or engineers bridging development and operations
  • Anyone aiming to lead cloud-based operational excellence

What are the prerequisites for Google Cloud Professional Cloud DevOps Engineer Certification?

  • 3+ years of IT / industry experience 
  • 1+ year designing and managing production systems on GCP 
  • Familiarity with DevOps and SRE practices, scripting, infrastructure as code, monitoring tools
  • Prepare for the exam by completing this course: Professional Cloud DevOps Engineer
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Google Cloud Professional Cloud DevOps Engineer Certification - Certification & Exam

Certification Outline:

Section 1 - Bootstrapping & Maintaining a Google Cloud Organization  

  • Designing overall resource hierarchy (projects, folders, shared networking) 
  • Shared logging & monitoring across projects (multi-project logging) 
  • IAM roles, organization-level policies, service accounts 
  • Infrastructure management via IaC / automation (Terraform, Config Connector, scripting) 
  • Designing CI/CD stack for hybrid & multi-cloud environments (Cloud Build, Cloud Deploy, Skaffold, etc.) 
  • Managing multiple environments (staging, prod, ephemeral)
  • Enabling secure dev environments (Cloud Shell, Cloud Workstations, bootstrapping tools) 

Section 2 - Building & Implementing CI/CD Pipelines  

  • Designing and managing CI/CD pipelines, triggers, artifact management (Artifact Registry) 
  • Deployment to hybrid / multi-cloud, serverless, containerized environments
  • Implementing deployment strategies (canary, blue/green, rolling, traffic splitting)
  • CI/CD of infrastructure (IaC)
  • Managing pipeline secrets & configuration (Secret Manager, KMS)
  • Auditing pipeline executions, troubleshooting deployment failures
  • Security practices for the pipeline

Section 3 - Applying Site Reliability Engineering (SRE) Practices    

  • Defining and using SLIs, SLOs, error budgets
  • Incident handling, response, and postmortems
  • Change management, reliability engineering practices
  • Balancing velocity vs stability

Section 4 - Implementing Observability Practices 

  • Logging, monitoring, metrics, dashboards
  • Alerting, uptime checks, custom metrics
  • Tracing & debugging
  • Integrating observability across services and environments

Section 5 - Optimizing Performance & Troubleshooting 

  • Identifying bottlenecks, tuning applications & infrastructure
  • Autoscaling, resource optimization
  • Network, storage, compute performance tuning
  • Root-cause analysis, incident debugging
  • Cost efficiency, resource right-sizing