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

Professional-Cloud-DevOps-Engineer日本語 testking pdf

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: Oct 02, 2026

Q & A: 208 Questions and Answers

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Topics of Google Professional Cloud DevOps Engineer Exam

Candidates must know the exam topics before they start preparation because it will help them in hitting the core. Our Professional Cloud DevOps Engineer Dumps will include the following topics:

Applying site reliability engineering principles to a service

  • Construct feedback loops to decide what to build next
  • 1.2 Manage service life cycle:
  • Toil automation
  • Agree to consequences of not meeting the error budget
  • Discover SLIs (availability, latency, etc.)
  • Manage a service (e.g., introduce a new service, deploy it, maintain and retire it)
  • Balance change, velocity, and reliability of the service:
  • Define SLOs and understand SLAs

Building and implementing CI/CD pipelines for a service

  • Artifact repositories with Container Registry
  • Testing a new version with Spinnaker
  • Deployment strategies with Cloud Build, Spinnaker
  • CI/CD pipeline triggers with Cloud Source Repositories, Cloud Build GitHub App, Cloud Pub/Sub
  • Configure deployment processes (e.g., approval flows)
  • Immutable artifacts with Container Registry
  • Deployment to hybrid and multi-cloud environments with Anthos, Spinnaker, Kubernetes
  • Artifact versioning strategy with Cloud Build, Container Registry
  • Design CI/CD pipelines:

Implementing service monitoring strategies

  • Set ACL to allow metric writing for custom metrics with IAM, Stackdriver Monitoring
  • Set ACL to restrict export configuration with IAM, Stackdriver Logging
  • Enabling VPC flow logs
  • Set ACL to restrict access to audit logs with IAM, Stackdriver Logging
  • Using basic vs. advanced logging filters
  • Collecting logs from Compute Engine, GKE with Stackdriver Logging, Fluentd
  • Understanding the logging exclusion vs. logging export
  • Selecting the options for logging export
  • Implementing logs-based metrics
  • Collecting third-party and structured logs with Stackdriver Logging, Fluentd
  • Manage application logs:
  • Enabling data access logs (e.g., Cloud Audit Logs)
  • Sending application logs directly to Stackdriver API with Stackdriver Logging
  • Collecting metrics from Compute Engine
  • Use metric explorer for ad hoc metric analysis
  • Viewing logs in the GCP Console
  • Sending logs to an external logging platform
  • Viewing export logs in Cloud Storage and BigQuery
  • Implementing a project-level / org-level export
  • Collecting GKE/Kubernetes metrics

Optimizing service performance

  • Develop a plan to optimize areas of greatest cost or lowest utilization
  • Interpret service mesh telemetry
  • Consider network pricing
  • Utilize Stackdriver to identify cloud resource utilization
  • TCO considerations
  • Work with committed-use discounts
  • identify resource costs
  • Identify resource utilization levels
  • Manage preemptible VMs
  • Troubleshoot issues with the image/OS
  • Utilize Stackdriver Trace/Profiler to profile performance characteristics
  • Troubleshoot network issues (e.g., VPC flow logs, firewall logs, latency, view network details)
  • Evaluate and understand user impact (Stackdriver Service Monitoring for App Engine, Istio)
  • Identify service performance issues:

Managing service incidents

  • Perform an investigation to isolate the most likely actual cause
  • Manage stakeholder relationships
  • Handle requests for impact assessment
  • Establish communications channels (email, IRC, Hangouts, Slack, phone, etc.)
  • Rotate/hand over roles
  • Avoid exhaustion/burnout
  • Scaling response team and delegation
  • Identify alternatives to mitigate the issue
  • Evaluate symptoms against probable causes; the rank probability of cause based on observed behavior
  • Record major changes in incident state (When mitigated? When all clear? etc.)
  • Provide regular status updates, internal and external
  • Coordinate roles and implement communication channels during a service incident:
  • Identify probable causes of service failure
  • Define roles (incident commander, communication lead, operations lead)

Google Professional Cloud DevOps Engineer Certified Professional salary

The average salary of a Google Professional Cloud DevOps Engineer Certified Expert in different regions is as follows:

  • United State: 151,00 USD
  • England: 130,500 POUND
  • Europe: 144,000 EURO
  • India: 25,00,000 INR

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

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.

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

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

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