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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.

  • 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.

  • 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.

How much Google Professional Cloud DevOps Engineer Exam cost

Google Professional Cloud DevOps Engineer exam cost is USD 200, for more information related to the Google Professional Cloud DevOps Engineer exam, please visit Google Website. Additional costs of Professional Cloud DevOps Engineer exam dumps pdf and Professional Cloud DevOps Engineer practice test are not included in this price.

The Google Professional Cloud DevOps Engineer certification is designed to equip the specialists with the expertise required to perform the following technical tasks: applying the principles of site reliability engineering to services, optimizing service performance, implementing the strategies for service monitoring, building and implementing CI/CD pipelines for services, as well as managing service incidents. To get the certificate, the candidates need to complete a single exam covering a wide range of knowledge and skills.

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

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

SectionWeightObjectives
Topic 1: Applying site reliability engineering practices18%- Design for resilience
  • 1. Plan redundancy and fault tolerance
  • 2. Test failure scenarios and recovery
  • 3. Automate remediation and self-healing
- Manage incidents and outages
  • 1. Implement improvements to prevent recurrence
  • 2. Detect and respond to issues quickly
  • 3. Perform postmortems and root cause analysis
- Define reliability goals
  • 1. Align reliability with business needs
  • 2. Establish SLIs, SLOs, SLAs
  • 3. Use error budgets to balance change and stability
Topic 2: Optimizing performance and cost17%- Balance cost, performance, and reliability
  • 1. Make tradeoff decisions based on data
  • 2. Plan capacity and scaling
  • 3. Optimize over time
- Improve system performance
  • 1. Use caching and content delivery
  • 2. Optimize resource allocation
  • 3. Tune applications and infrastructure
- Apply FinOps practices
  • 1. Use spot instances and committed use discounts
  • 2. Monitor and analyze cloud costs
  • 3. Right-size resources and eliminate waste
Topic 3: Building and implementing CI/CD pipelines25%- Optimize and maintain pipelines
  • 1. Handle rollbacks and versioning
  • 2. Improve speed and reliability
  • 3. Monitor pipeline performance
- Design CI/CD pipelines
  • 1. Plan pipelines for apps, infrastructure, ML workloads
  • 2. Support hybrid/multi-cloud deployment
  • 3. Integrate artifact management
- Implement and secure pipelines
  • 1. Manage pipeline secrets and credentials
  • 2. Automate build, test, and deployment stages
  • 3. Enforce security scanning and compliance checks
Topic 4: Bootstrapping and maintaining a Google Cloud organization20%- Design resource hierarchy
  • 1. Define IAM policies and access control
  • 2. Plan shared networking and connectivity
  • 3. Organize resources by project/folder/application
- Manage configuration and deployment
  • 1. Automate resource provisioning
  • 2. Enforce consistency across environments
  • 3. Use Infrastructure as Code tools
- Set up governance and compliance
  • 1. Configure audit logging and monitoring
  • 2. Implement organization policies
  • 3. Manage resource quotas and limits
Topic 5: Implementing observability and troubleshooting20%- Build monitoring and logging systems
  • 1. Use Cloud Monitoring, Cloud Logging, Cloud Trace
  • 2. Create dashboards and alerts
  • 3. Collect and analyze metrics, logs, traces
- Troubleshoot complex issues
  • 1. Trace requests end-to-end
  • 2. Isolate problems across layers
  • 3. Analyze performance and latency
- Optimize observability strategy
  • 1. Reduce noise and prioritize signals
  • 2. Integrate observability into development
  • 3. Scale monitoring for large environments

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