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Google Professional-Cloud-DevOps-Engineer-JPN Questions & Answers - in .pdf

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  • Vendor: Google
  • 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)
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Professional-Cloud-DevOps-Engineer-JPN Study Guide
  • Total Q&A: 208
  • Update: Aug 23, 2026
  • Price: $69.99
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  • 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)
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Google Professional-Cloud-DevOps-Engineer日本語 Exam Overview:

Certification Vendor:Google Cloud
Exam Name:Google Cloud Certified - Professional Cloud DevOps Engineer Exam
Exam Number:Professional-Cloud-DevOps-Engineer
Exam Duration:120 minutes
Available Languages:English, Japanese, Spanish, Portuguese
Real Exam Qty:50
Passing Score:70%
Exam Price:$200 USD
Exam Format:Multiple Choice, Multiple Select
Certificate Validity Period:2 years
Related Certifications:Google Cloud Associate Cloud Engineer
Google Cloud Professional Cloud Architect
Google Cloud Professional Cloud Developer
Sample Questions:Google Professional-Cloud-DevOps-Engineer日本語 Sample Questions
Exam Way:Online proctored exam available through Pearson VUE or online proctoring. In-person testing at Kryterion test centers also available.
Pre Condition:Recommended: Associate Cloud Engineer certification and 3+ years industry experience including 1+ years Google Cloud experience. No mandatory prerequisites required.
Official Syllabus URL:https://cloud.google.com/certification/cloud-devops-engineer

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

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

Building and implementing CI/CD pipelines for a service

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

Implementing service monitoring strategies

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

Optimizing service performance

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

Managing service incidents

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

The Google Professional Cloud DevOps Engineer certification is designed to equip the specialists with the expertise required to perform the following technical tasks: applying the principles of site reliability engineering to services, optimizing service performance, implementing the strategies for service monitoring, building and implementing CI/CD pipelines for services, as well as managing service incidents. To get the certificate, the candidates need to complete a single exam covering a wide range of knowledge and skills.

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

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日本語 Exam Syllabus Topics:

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