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

Exam Code: Professional-Cloud-DevOps-Engineer日本語
Exam Name: Google Cloud Certified - Professional Cloud DevOps Engineer Exam (Professional-Cloud-DevOps-Engineer日本語版)
Updated: Oct 24, 2026
Q & A: 208 Questions and Answers

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Domains Tested in Final Evaluation

The candidates who succeed in passing the Google Professional Cloud DevOps Engineer validation will add an international designation under their belt that helps them consolidate their position in the company and receive generous offers from their employers. So, if applicants want to differentiate themselves from other colleagues, they should demonstrate the following skills:

Identifying issues related to service performance and implementing solutions to optimize it;
Coordinating teams to identify and manage incidents related to service development.
Implementing and building CI/CD service pipelines;
Identifying the most effective principles related to site reliability engineering and applying them to a definite service;
Checking and implementing strategies related to service monitoring;

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What is the duration, language, and format of Google Professional Cloud DevOps Engineer Exam

Language: English
Format: Multiple choices, multiple select
Length of Examination: 120 minutes
Number of Questions: 50-60
Passing score: 80%

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

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

Section	Weight	Objectives
Topic 1: Applying site reliability engineering practices	18%	- Define reliability goals 1. Align reliability with business needs 2. Use error budgets to balance change and stability 3. Establish SLIs, SLOs, SLAs - Manage incidents and outages 1. Perform postmortems and root cause analysis 2. Detect and respond to issues quickly 3. Implement improvements to prevent recurrence - Design for resilience 1. Plan redundancy and fault tolerance 2. Test failure scenarios and recovery 3. Automate remediation and self-healing
Topic 2: Implementing observability and troubleshooting	20%	- Optimize observability strategy 1. Scale monitoring for large environments 2. Reduce noise and prioritize signals 3. Integrate observability into development - Troubleshoot complex issues 1. Isolate problems across layers 2. Analyze performance and latency 3. Trace requests end-to-end - Build monitoring and logging systems 1. Collect and analyze metrics, logs, traces 2. Create dashboards and alerts 3. Use Cloud Monitoring, Cloud Logging, Cloud Trace
Topic 3: Bootstrapping and maintaining a Google Cloud organization	20%	- Design resource hierarchy 1. Organize resources by project/folder/application 2. Plan shared networking and connectivity 3. Define IAM policies and access control - Set up governance and compliance 1. Implement organization policies 2. Configure audit logging and monitoring 3. Manage resource quotas and limits - Manage configuration and deployment 1. Use Infrastructure as Code tools 2. Enforce consistency across environments 3. Automate resource provisioning
Topic 4: Optimizing performance and cost	17%	- Improve system performance 1. Optimize resource allocation 2. Tune applications and infrastructure 3. Use caching and content delivery - Apply FinOps practices 1. Right-size resources and eliminate waste 2. Monitor and analyze cloud costs 3. Use spot instances and committed use discounts - Balance cost, performance, and reliability 1. Make tradeoff decisions based on data 2. Optimize over time 3. Plan capacity and scaling
Topic 5: Building and implementing CI/CD pipelines	25%	- Implement and secure pipelines 1. Enforce security scanning and compliance checks 2. Manage pipeline secrets and credentials 3. Automate build, test, and deployment stages - Optimize and maintain pipelines 1. Improve speed and reliability 2. Monitor pipeline performance 3. Handle rollbacks and versioning - Design CI/CD pipelines 1. Support hybrid/multi-cloud deployment 2. Integrate artifact management 3. Plan pipelines for apps, infrastructure, ML workloads

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

Question #1

Google Kubernetes Engine (GKE) クラスター全体にいくつかの制約テンプレートを適用する必要があります。制約には、Kubernetes API の制限などのポリシーパラメーターが含まれます。ポリシーパラメーターが GitHub リポジトリに保存され、変更が発生したときに自動的に適用されることを確認する必要があります。あなたは何をするべきか？

A. GitHub リポジトリを使用して Anthos Config Management を構成します。リポジトリに変更があった場合は、Anthos Config Management を使用して変更を適用します。
B. GitHub に変更があった場合、Web フックを使用して Anthos Service Mesh にリクエストを送信し、変更を適用します。
C. パラメータ変更時に Cloud Build をトリガーする GitHub アクションを設定します。Cloud Build で gcloud CLI コマンドを実行して変更を適用します。
D. GitHub リポジトリを使用して Config Connector を構成します。リポジトリに変更があった場合は、Config Connector を使用して変更を適用します。

Reveal Solution Discussion 0

Correct Answer: A 🗳️