Google Cloud Certified - Professional Cloud DevOps Engineer Exam: Professional-Cloud-DevOps-Engineer Exam

"Google Cloud Certified - Professional Cloud DevOps Engineer Exam", also known as Professional-Cloud-DevOps-Engineer exam, is a Google Certification. With the complete collection of questions and answers, Pass4sureCert has assembled to take you through 208 Q&As to your Professional-Cloud-DevOps-Engineer Exam preparation. In the Professional-Cloud-DevOps-Engineer exam resources, you will cover every field and category in Cloud DevOps Engineer Certification helping to ready you for your successful Google Certification.

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  • Updated on: Aug 04, 2026
  • No. of Questions: 208 Questions & Answers

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  • Updated on: Aug 04, 2026
  • No. of Questions: 208 Questions & Answers

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What is the duration, language, and format of Google Professional Cloud DevOps Engineer Exam

  • Length of Examination: 120 minutes
  • Language: English
  • Format: Multiple choices, multiple select
  • Passing score: 80%
  • Number of Questions: 50-60

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.

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

Audience for This Certification Exam

The target audience for the Google Professional Cloud DevOps Engineer test is formed of those individuals who want to learn how they can develop efficient operations and find a balance between the speed in delivering services and its reliability. Also, the candidates who are interested in taking this evaluation want to validate their skills in using the Google Cloud Platform at a professional level. Therefore, thanks to such an exam, applicants will learn how to develop pipelines related to software delivery, as well as become experts at monitoring and deploying services, together with managing and learning from them.

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

SectionWeightObjectives
Optimizing performance and cost17%- Balance cost, performance, and reliability
  • 1. Plan capacity and scaling
  • 2. Make tradeoff decisions based on data
  • 3. Optimize over time
- Improve system performance
  • 1. Use caching and content delivery
  • 2. Tune applications and infrastructure
  • 3. Optimize resource allocation
- Apply FinOps practices
  • 1. Monitor and analyze cloud costs
  • 2. Use spot instances and committed use discounts
  • 3. Right-size resources and eliminate waste
Bootstrapping and maintaining a Google Cloud organization20%- Design resource hierarchy
  • 1. Plan shared networking and connectivity
  • 2. Organize resources by project/folder/application
  • 3. Define IAM policies and access control
- Set up governance and compliance
  • 1. Implement organization policies
  • 2. Manage resource quotas and limits
  • 3. Configure audit logging and monitoring
- Manage configuration and deployment
  • 1. Use Infrastructure as Code tools
  • 2. Automate resource provisioning
  • 3. Enforce consistency across environments
Building and implementing CI/CD pipelines25%- Optimize and maintain pipelines
  • 1. Improve speed and reliability
  • 2. Handle rollbacks and versioning
  • 3. Monitor pipeline performance
- Implement and secure pipelines
  • 1. Enforce security scanning and compliance checks
  • 2. Automate build, test, and deployment stages
  • 3. Manage pipeline secrets and credentials
- Design CI/CD pipelines
  • 1. Plan pipelines for apps, infrastructure, ML workloads
  • 2. Support hybrid/multi-cloud deployment
  • 3. Integrate artifact management
Implementing observability and troubleshooting20%- Troubleshoot complex issues
  • 1. Isolate problems across layers
  • 2. Analyze performance and latency
  • 3. Trace requests end-to-end
- Build monitoring and logging systems
  • 1. Collect and analyze metrics, logs, traces
  • 2. Use Cloud Monitoring, Cloud Logging, Cloud Trace
  • 3. Create dashboards and alerts
- Optimize observability strategy
  • 1. Reduce noise and prioritize signals
  • 2. Scale monitoring for large environments
  • 3. Integrate observability into development
Applying site reliability engineering practices18%- Define reliability goals
  • 1. Align reliability with business needs
  • 2. Establish SLIs, SLOs, SLAs
  • 3. Use error budgets to balance change and stability
- Manage incidents and outages
  • 1. Detect and respond to issues quickly
  • 2. Implement improvements to prevent recurrence
  • 3. Perform postmortems and root cause analysis
- Design for resilience
  • 1. Test failure scenarios and recovery
  • 2. Plan redundancy and fault tolerance
  • 3. Automate remediation and self-healing

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