Google Professional-Cloud-DevOps-Engineer日本語 real exam prep : Google Cloud Certified - Professional Cloud DevOps Engineer Exam (Professional-Cloud-DevOps-Engineer日本語版)

  • Exam Code: Professional-Cloud-DevOps-Engineer-JPN
  • Exam Name: Google Cloud Certified - Professional Cloud DevOps Engineer Exam (Professional-Cloud-DevOps-Engineer日本語版)
  • Updated: Aug 11, 2026
  • Q&As: 208 Questions and Answers

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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.

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

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Writing Google Professional Cloud DevOps Engineer could be very difficult for you if you don't have any experience in terms of on-premises DevOps engineering, still, this certification can be cracked by following some tips and tricks. This exam may go hard for you if you had not done its preparation properly. Many websites are offering the latest Google Professional Cloud DevOps Engineer questions and answers, but these questions are not verified by Google certified experts and that is why many are failed in their just first attempt. Real4Prep is the best platform which provides the candidate with the necessary Google Professional Cloud DevOps Engineer practice exam questions that will help him to pass the Google Professional Cloud DevOps Engineer on the first time.

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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 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.

The Google Professional Cloud DevOps Engineer exam is taken by the specialists who want to obtain international certification and get validated as professional engineers who can manage Cloud DevOps features.

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

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

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