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Exam Details

The qualifying test for the Google Professional Cloud DevOps Engineer certification has the duration of 2 hours. The candidates will be asked to answer around 50 multiple-select and multiple-choice questions. The exam is available in the English language only. The students can take it either as an online proctored test or an onsite proctored exam at an authorized testing center. You can check the location of the nearest center in your region using the search on the official webpage. Each learner is required to pay the registration fee of $200 to schedule the exam.

If you don’t manage to pass the exam on the first try, you can retake it after 14 days. If you don't complete it for the second time, you will be required to wait for 60 days before you can sit for it for the third time. If you fail the third attempt, you will have to wait for 1 year before taking the test again.

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

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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 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.

  • 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.

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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.

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

SectionWeightObjectives
Topic 1: Reliability and Site Reliability Engineering (SRE)24%- Monitoring and observability
  • 1. Creating dashboards for service health visibility
  • 2. Setting up alerting policies and incident management
  • 3. Configuring Cloud Monitoring and Logging
  • 4. Implementing distributed tracing with Cloud Trace
- Incident management
  • 1. Configuring automated incident response
  • 2. Post-incident reviews and blameless postmortems
  • 3. Implementing on-call procedures
- SLOs, SLIs, and SLAs
  • 1. Defining and implementing Service Level Objectives
  • 2. Setting appropriate Service Level Agreements
  • 3. Error budget policies and management
  • 4. Creating and interpreting Service Level Indicators
Topic 2: Monitoring, Logging, and Debugging12%- Debugging and troubleshooting
  • 1. Analyzing performance profiles with Cloud Profiler
  • 2. Using Cloud Debugger and Error Reporting
  • 3. Debugging with Cloud Trace distributed tracing
- Cloud Operations Suite
  • 1. Creating uptime checks and alerts
  • 2. Implementing Cloud Logging with log sinks
  • 3. Configuring Cloud Monitoring metrics
- Log management
  • 1. Implementing log-based metrics
  • 2. Configuring log retention policies
  • 3. Structuring logs for efficient querying
Topic 3: Microservices Architecture14%- Container orchestration with GKE
  • 1. Managing pod lifecycle and resource quotas
  • 2. Configuring node pools and auto-scaling
  • 3. Designing Kubernetes cluster architectures
  • 4. Implementing workload deployment and scaling
- Service mesh and networking
  • 1. Configuring traffic management and load balancing
  • 2. Implementing service-to-service authentication
  • 3. Implementing Anthos Service Mesh / Istio
- API management
  • 1. Implementing API versioning strategies
  • 2. Exposing APIs with Cloud Endpoints / Apigee
Topic 4: CI/CD Pipeline Development26%- CI/CD best practices
  • 1. Managing secrets in CI/CD pipelines
  • 2. Configuring quality gates and code coverage
  • 3. Implementing shift-left testing
- Containerization and Docker
  • 1. Managing container registries
  • 2. Implementing container security best practices
  • 3. Creating optimized Docker images (multi-stage builds)
- Designing and implementing CI/CD pipelines
  • 1. Designing pipeline architecture (Cloud Build, Jenkins, GitLab CI, etc.)
  • 2. Configuring build triggers and webhooks
  • 3. Setting up artifact management with Artifact Registry
  • 4. Configuring build caching strategies
  • 5. Implementing build automation scripts
Topic 5: Cloud Infrastructure Automation24%- Configuration management
  • 1. Implementing configuration drift detection
  • 2. Managing secrets with Secret Manager
  • 3. Using Ansible for configuration management
- Deployment strategies
  • 1. Feature flags with Firebase Remote Config or LaunchDarkly
  • 2. Rolling updates with Kubernetes
  • 3. Canary releases and progressive rollouts
  • 4. Blue-green deployments
- Infrastructure as Code (IaC)
  • 1. Implementing with Terraform
  • 2. Managing infrastructure modules and state
  • 3. Implementing immutable infrastructure patterns

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