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

Google Professional-Cloud-DevOps-Engineer exam
  • Exam Code: Professional-Cloud-DevOps-Engineer
  • Exam Name: Google Cloud Certified - Professional Cloud DevOps Engineer Exam
  • Updated: Aug 01, 2026
  • Q & A: 208 Questions and Answers
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Google Professional Cloud DevOps Engineer Certification Path

The Google Professional Cloud DevOps Engineer Certification is the highest level of certification mainly focusing on the Solution Architect Professional. There is no prerequisite for this exam but still, it would be best to follow some sequence to prove immense knowledge as a Google Professional Cloud DevOps Engineer.

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Exam Topics

To achieve good results in the Google Professional Cloud DevOps Engineer certification exam, the candidates need to develop a comprehensive understanding of its domains. The detailed outline of the topics and subtopics covered in the test is available on the official platform. Their brief overview is provided below:

  • Implementation of Strategies for Service Monitoring

    Here the applicants will be asked to show that they have the capacity to manage the Stackdriver Logging and Stackdriver Monitoring platforms. They should also know how to manage application logs as well as application metrics using Stackdriver Monitoring. Additionally, the individuals will require the competency in implementing logging & monitoring access control.

  • Management of Service Incidents

    To answer the questions related to this part of the certification test, the students need to have the skills in coordinating roles and implementing the channels of communication in the course of the service incident. In addition, they need to have an understanding of how to perform the analysis of incident symptoms affecting the users. The test takers should also know how to mitigate the impact of an incident on the users. Finally, they need to have the sufficient competency in resolving issues (for example, Cloud Build, Jenkins, etc.) and documenting an issue in the postmortem.

  • Optimization of Service Performance

    Within this module, the learners need to show that they are capable of optimizing resource utilization, including determining resource costs, defining resource utilization levels, developing a plan to optimize areas of the lowest utilization/greatest cost, managing preemptible Virtual Machines, considering network pricing, and so on. They must also possess the skills in debugging application code as well as determining service performance issues.

  • Application of Site Reliability Engineering Principles to Services

    This subject area measures the skills of the professionals in ensuring healthy collaboration for operations, including preventing burnout (for example, setting up automation procedures to prevent burnout) as well as fostering a learning culture & culture of blamelessness. Besides that, the candidates need to possess the expertise in managing the service life cycle as well as balancing the service change, velocity, and reliability.

  • Building & Implementation of CI/CD Pipelines for Services

    The second topic focuses on the ability of the examinees to manage various development environments (for instance, staging, production, etc.), manage infrastructure as code, as well as manage configuration & secrets. Moreover, the test takers are required to demonstrate their proficiency in designing & implementing CI/CD pipelines, deploying CI/CD tooling, and securing the deployment pipeline.

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

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

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