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Prerequisites

The Google Professional Cloud DevOps Engineer certification exam is designed for the Application Developers and Programmers who want to learn how to design, develop, and deploy Cloud applications. This test has no formal prerequisites. However, the individuals are recommended to have at least 3 years of industry experience, involving 1 or more years of experience with managing solutions on Google Cloud Platform.

Preparation Resources for Certification Test

Passing this Google exam is possible from the first attempt if you combine different preparation resources such as the ones offered by the vendor and the books available on Amazon. In case you’re on the lookout for the most effective revision materials, here’s our choice:

  • Google Cloud Professional Cloud DevOps Engineer Exam – All in One Guide: Get Certified Efficiently in Google Cloud! (Google Cloud Certification Series Book 7)

    This book is available on Amazon in Kindle format and has been published by Joseph Holbrook. Also, the candidates can buy it for almost $12. This guide follows all the topics tested in the certification exam and helps the applicants sharpen their skills in managing Google Cloud DevOps Engineer features. Besides, it helps entrants to fully prepare for the designation test as it includes more than 100 questions and detailed answers for each of them. Thus, the exam-takers will get used to the test structure and difficulty level. Plus, anyone who buys this guide will receive free access to additional learning resources that will consolidate their knowledge of Google Cloud apps and features.

  • Google Cloud DevOps Engineer Learning Path

    The vendor has developed a comprehensive learning path for candidates who want to pass the Professional Cloud DevOps Engineer exam. It includes several courses that will take the applicants through all the steps necessary to validate the necessary abilities to get the passing score from the first attempt. In particular, this learning kit includes the following training sessions:

    • The Google Cloud Fundamentals: Core Infrastructure class focuses on helping the candidates learn about storage and computing services which are included in Google Cloud Pack. Therefore, the exam-takers will learn how to use the BigQuery, App Engine, Cloud SQL and Storage, and Google Kubernetes Engine features.
    • The training dedicated to the development of a Google SRE culture helps the candidates gain advanced skills in providing production support and minimizing the gap between operations and development. During this course, applicants will learn the secrets of Site Reliability Engineering and how they can benefit from creating a Google SRE culture.
    • The Architecting with Google Cloud: Design and Process class helps the test-takers learn how to deploy Google Cloud features in a cost-effective and performant way.
    • The final training session included in this learning path is dedicated to monitoring, logging, and observability in Google Cloud. It teaches the candidates how to troubleshoot and improve Google Cloud infrastructure performance.

    Once the candidates go through the courses mentioned above, they will gain several skill badges that consolidate their skills in DevOps engineering. These badges are as follows:

    • The skill badge that validates the ability to use Google Cloud for performing foundational infrastructure tasks. It helps the candidates learn how to manage important application services such as Cloud Functions or Stackdriver.
    • The second badge is related to the implementation of DevOps features in Google Cloud. In particular, it will help the candidates improve their software delivery capacity with the help of Google Cloud and achieve a higher speed, availability, and stability.
    • The last badge helps the candidates understand how to use the Google Cloud Operations Suite for monitoring and logging. Thus, the applicants will learn how to use Google Cloud’s ins and outs for generating healthier and improved applications.

    Without doubt, a candidate who goes through this learning process provided by Google will have significantly higher chances to get certified in one go.

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.

Reference: https://cloud.google.com/certification/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:

  • 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.

  • 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.

  • 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.

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

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