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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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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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Test Structure

The candidates who want to take this Google exam will have two hours to answer all questions. Even though the vendor doesn’t give details on the total number of questions that the examinees will receive, they should be prepared to solve multiple-choice and multiple-answer inquiries. Besides, the test is delivered in the English language only. As for the registration fee, the test-takers will need to pay $200 to take it. Additional taxes may apply depending on the candidate’s profile and chosen delivery method. By and large, the applicants have two options to take the official exam. They can choose to take it online from any remote location that they prefer. If they choose this option, the candidates should read carefully what the testing requirements are. In case applicants prefer to be present in a classroom when they take the actual testing, then they can search for a test center that is closest to their location. Also, Google doesn’t have any prerequisites for the candidates to be eligible for the evaluation. Still, it recommends that the candidates for the Professional Cloud DevOps Engineer exam should have at least 3 years of experience in the industry including a minimum of one year of experience in managing and developing solutions on GCP.

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

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

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