GCP-DevOpsProfessional LevelGoogle Cloud Platform

Google Cloud Professional Cloud DevOps Engineer

Google's premier certification built directly around Site Reliability Engineering (SRE) principles. Tests your ability to build delivery pipelines, deploy to Google Kubernetes Engine (GKE), configure Cloud Operations Suite, and manage error budgets.

Recommended Prerequisites: Three or more years of industry experience including one or more years managing Google Cloud solutions.

Exam Duration

120 Minutes (2 Hours)

Passing Score

70% (Scaled scoring)

Registration Cost

$200 USD

Exam Format

Multiple Choice / Multiple Select (50-60 Questions)

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Complete Exam Blueprint & Tested Competencies

Total 100% Weight

1. Applying Site Reliability Engineering (SRE) Principles

Weight: 22%

Key Exam Topics Tested:

Defining Service Level Indicators (SLIs), Service Level Objectives (SLOs), and SLAs
Calculating and managing Error Budgets to balance feature velocity with stability
Implementing incident management protocols: Blameless Postmortems, On-Call rotations
Capacity planning, load testing, and chaos engineering

Practical Competencies & Skills Required:

✓Convert business reliability requirements into quantifiable Prometheus/Cloud Monitoring SLIs
✓Halt deployments when an error budget is exhausted and focus sprints on stability

2. Building and Implementing CI/CD Pipelines

Weight: 22%

Key Exam Topics Tested:

Cloud Build (cloudbuild.yaml), Artifact Registry, and Google Cloud Deploy
Deployment strategies on GKE: Blue/Green, Canary, Rolling updates
Automated rollbacks via Cloud Monitoring metric alerting
Infrastructure as Code on GCP using Terraform and Config Connector

Practical Competencies & Skills Required:

✓Author cloudbuild.yaml build steps with caching and secret substitution
✓Promote releases across Dev, Staging, and Production targets with Cloud Deploy

3. Managing Service Availability & Performance

Weight: 20%

Key Exam Topics Tested:

Cloud Monitoring (Stackdriver): custom metrics, uptime checks, alerting policies, MQL
Cloud Logging: log routing, log sinks to BigQuery / PubSub, log-based metrics
Cloud Trace and Cloud Profiler for identifying CPU and memory performance regressions
GKE autoscaling: Cluster Autoscaler, Horizontal Pod Autoscaler (HPA), Vertical Pod Autoscaler (VPA)

Practical Competencies & Skills Required:

✓Configure log sinks routing critical application audit logs into BigQuery for security analytics
✓Tune HPA targets on custom metrics exposed by Cloud Monitoring

4. Managing Service Incidents & Mitigating Outages

Weight: 18%

Key Exam Topics Tested:

Incident response coordination, role assignment (Incident Commander, Operations Lead)
Rollback procedures, traffic draining with Cloud Load Balancing and Cloud Armor
Emergency break-glass access protocols and root-cause discovery

Practical Competencies & Skills Required:

✓Drain regional traffic using global external HTTP(S) load balancer backends during datacenter anomalies
✓Facilitate structured, psychological-safety-focused blameless postmortems

5. Ensuring Security and Compliance

Weight: 18%

Key Exam Topics Tested:

Binary Authorization: requiring cryptographic attestation signatures before GKE pod admission
Workload Identity: mapping Kubernetes ServiceAccounts to GCP IAM Service Accounts
Secret Manager integration, Cloud KMS, and Secret scanning
VPC Service Controls and Service Account least-privilege scoping

Practical Competencies & Skills Required:

✓Block unverified container images using Binary Authorization policies
✓Eliminate static JSON service account keys using GKE Workload Identity

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