GCP DevOps Engineer study guide
GCP DevOps Engineer · Work through your exam, one topic at a time.
The Professional Cloud DevOps Engineer is a Google Cloud certification for practitioners who implement processes and capabilities across the systems development lifecycle using Google-recommended methodologies and tools, enabling efficient software and infrastructure delivery while balancing reliability with delivery speed. It suits engineers with 3+ years of industry experience, including at least 1+ year designing and managing production systems on Google Cloud; there are no prerequisites. The GCP DevOps Engineer study guide has 5 sections and about 1,898 words.
01Bootstrap and Maintain a Google Cloud Organization
Every Google Cloud tenant has a single organization node tied to a Cloud Identity or Workspace domain. Below it, folders model business units or environments (prod/non-prod, sandbox), and projects are the unit of API enablement, billing linkage, and quota.
394 words, about 2 min02Apply Site Reliability Engineering Practices
An SLI is a measured ratio of good events to valid events: availability, latency under a threshold, freshness, correctness. An SLO is the target for that SLI over a window, such as 99.9% of requests succeeding over 28 days.
394 words, about 2 min03Build and Implement CI/CD Pipelines, Including Continuous Testing
A pipeline is trigger → build and test → artifact → deploy → verify. The Google Cloud primitives are Cloud Build (triggers on Cloud Source Repositories, GitHub, GitLab, or Bitbucket; build steps as containers; private pools for VPC access; substitutions and Secret Manager for secrets - never bake credentials into build config), Artifact Registry (container images, language packages, and ML artifacts, with vulnerability scanning and cleanup policies), and Cloud Deploy (delivery pipelines → targets → releases → rollouts → promotions, with approval gates and canary or blue/green strategies driven by Skaffold render and manifest steps).
366 words, about 2 min04Implement Observability Practices and Troubleshoot Issues
Know which tool answers which question. Cloud Monitoring covers metrics, dashboards, uptime checks, alerting policies, and SLO monitoring.
380 words, about 2 min05Optimize Performance and Cost
Cost work starts with visibility. Label every resource by team, environment, and cost center, enforce label presence with org policy, export billing to BigQuery, and set budgets with alerts - budgets notify, they do not cap spend.
364 words, about 2 min