Professional Cloud DevOps Engineer exam
50-60 multiple choice and multiple select questions.
- Type
- Written
- Delivery
- Both
- Duration
- 120 min
Exam sections
Section 1: Bootstrapping and maintaining a Google Cloud organization
Design the organization’s resource hierarchy, define shared networking, IAM policies, and service-account strategy. Manage infrastructure with IaC tools like Terraform and Helm. Build CI/CD stacks for various environments and handle lifecycle stages including GKE fleet management.
Preparation tips
Focus on Infrastructure as Code (IaC) tools like Terraform, Config Connector, and Helm for resource management and bootstrapping organizations.
Section 2: Building and implementing CI/CD pipelines, including continuous testing
Architect pipelines for application and infrastructure workloads, covering artifact management and approval flows. Implement pipelines with Cloud Build and Cloud Deploy, applying strategies like canary or blue/green. Manage secrets and enforce supply-chain security compliance.
Preparation tips
Understand CI/CD tools such as Cloud Build and Cloud Deploy, along with deployment strategies like canary, blue/green, and traffic splitting.
Section 3: Applying site reliability engineering practices
Balance change velocity with reliability by defining SLIs, SLOs, and error budgets. Oversee service lifecycle from planning to retirement, incorporating capacity planning and autoscaling. Mitigate incidents through traffic draining and rollback techniques.
Preparation tips
Study SRE concepts including SLIs, SLOs, SLAs, and error budgets to effectively balance service velocity with reliability.
Section 4: Implementing observability practices and troubleshooting
Instrument services to collect logs, metrics, and traces. Manage and analyze logs via Logs Explorer, build dashboards, and set alerts. Use tracing frameworks and AI-driven analysis for troubleshooting across infrastructure, pipelines, and applications.
Preparation tips
Learn to use Google Cloud observability tools like Logs Explorer, Cloud Monitoring, and tracing frameworks for instrumentation and troubleshooting.
Section 5: Optimizing performance and cost
Gather performance data and apply FinOps techniques like right-sizing resources and using spot VMs or committed-use discounts. Optimize costs for workloads such as GKE, Cloud Run, and Compute Engine while maintaining performance and reliability.
Preparation tips
Familiarize yourself with FinOps practices, including resource right-sizing, spot VMs, and various discount models available on Google Cloud.