Professional-Cloud-DevOps-Engineerキャリアパス、Professional-Cloud-DevOps-Engineer模擬問題

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立派な生活を送るために、彼らはこの試験に関する専門知識の厳密な研究を行いました。 Google Cloud Certified - Professional Cloud DevOps Engineer Examのトレーニング資料がありますので、完璧な練習資料の検索に時間をかけないでください。 Professional-Cloud-DevOps-Engineer試験準備の熟練度を保証できます。 ですから、これは決定的な選択です。つまり、Professional-Cloud-DevOps-Engineer実践教材は、あなたが成功の成果を得るのに役立つことを意味します。
Google Professional-Cloud-Devops-Enginer認定を取得するには、候補者は、Kubernetes、クラウド機能、クラウドビルドなどのGoogleクラウド固有のテクノロジーなど、さまざまなDevOpsツールやプラクティスの知識をテストする厳格な試験に合格する必要があります。この試験は、候補者が実際のコンテキストでDevOpsワークフローを設計、実装、および管理する能力を実証することを要求する多肢選択とシナリオベースの質問で構成されています。成功した候補者は、Google Cloudを使用して、スケーラブルで信頼性の高いアプリケーションを構築、展開、および管理する専門知識を実証することができます。
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Professional-Cloud-DevOps-Engineer試験の準備中に常に楽観的な心を持ち続けている場合、Professional-Cloud-DevOps-Engineer試験に合格し、関連するProfessional-Cloud-DevOps-Engineer認定を取得することは非常に簡単だと深く信じています。近い将来。もちろん、楽観的な心を保つ方法は多くの人が答えるのが非常に難しい質問であることも知っています。私たちに知られているように、意志があるところには方法があります。この分野の専門家であるため、Professional-Cloud-DevOps-Engineer試験問題の助けを借りて素晴らしい結果が得られると信じています。
この試験は、Google Cloud Platformを使用してDevOpsプロセスとプラクティスを設計および実装する能力を評価するように設計されています。これには、継続的な統合とデリバリーパイプラインの開発と管理、監視および警告戦略の構成、自動化テストフレームワークの実装、およびインフラストラクチャのコードの管理などのスキルが含まれます。
Google Professional-Cloud-Devops-Engineer(Google Cloud Certified-Professional Cloud Devops Engineer)認定試験は、Cloud Devops Engineeringの分野の専門家にとって非常に人気のある認定です。この認定はGoogle Cloudによって提供されており、Google Cloudプラットフォームでアプリケーションの展開、監視、管理における個人のスキルと専門知識を検証するように設計されています。
Google Cloud Certified - Professional Cloud DevOps Engineer Exam 認定 Professional-Cloud-DevOps-Engineer 試験問題 (Q78-Q83):
質問 # 78
Some of your production services are running in Google Kubernetes Engine (GKE) in the eu-west-1 region.
Your build system runs in the us-west-1 region. You want to push the container images from your build system to a scalable registry to maximize the bandwidth for transferring the images to the cluster. What should you do?
- A. Push the images to Google Container Registry (GCR) using the gcr.io hostname.
- B. Push the images to Google Container Registry (GCR) using the eu.gcr.io hostname.
- C. Push the images to Google Container Registry (GCR) using the us.gcr.io hostname.
- D. Push the images to a private image registry running on a Compute Engine instance in the eu-west-1 region.
正解:B
解説:
Explanation
Hostname Storage location gcr.io Stores images in data centers in the United States asia.gcr.io Stores images in data centers in Asia eu.gcr.io Stores images in data centers within member states of the European Union us.gcr.io Stores images in data centers in the United States
質問 # 79
You are developing a strategy for monitoring your Google Cloud Platform (GCP) projects in production using Stackdriver Workspaces. One of the requirements is to be able to quickly identify and react to production environment issues without false alerts from development and staging projects. You want to ensure that you adhere to the principle of least privilege when providing relevant team members with access to Stackdriver Workspaces. What should you do?
- A. Choose an existing GCP production project to host the monitoring workspace. Attach the production projects to this workspace. Grant relevant team members read access to the Stackdriver Workspace.
- B. Grant relevant team members read access to all GCP production projects. Create Stackdriver workspaces inside each project.
- C. Create a new GCP monitoring project, and create a Stackdriver Workspace inside it. Attach the production projects to this workspace. Grant relevant team members read access to the Stackdriver Workspace.
- D. Grant relevant team members the Project Viewer IAM role on all GCP production projects. Create Slackdriver workspaces inside each project.
正解:C
解説:
Explanation
"A Project can host many Projects and appear in many Projects, but it can only be used as the scoping project once. We recommend that you create a new Project for the purpose of having multiple Projects in the same scope."
質問 # 80
Your company is developing applications that are deployed on Google Kubernetes Engine (GKE) Each team manages a different application You need to create the development and production environments for each team while you minimize costs Different teams should not be able to access other teams environments You want to follow Google-recommended practices What should you do?
- A. Create one Google Cloud project per team In each project create a cluster for development and one forproduction Grant the teams Identity and Access Management (1AM) access to their respective clusters
- B. Create one Google Cloud project per team In each project create a cluster with a Kubernetes namespacefor development and one for production Grant the teams Identity and Access Management (1AM) access to their respective clusters.
- C. Create a development and a production GKE cluster in separate projects In each cluster create a Kubernetes namespace per team and then configure Identity-Aware Proxy so that each team can onlyaccess its own namespace
- D. Create a development and a production GKE cluster in separate projects In each cluster create a Kubernetes namespace per team and then configure Kubernetes role-based access control (RBAC) so that each team can only access its own namespace
正解:D
解説:
The best option for creating the development and production environments for each team while minimizing costs and ensuring isolation is to create a development and a production GKE cluster in separate projects, in each cluster create a Kubernetes namespace per team, and then configure Kubernetes role-based access control (RBAC) so that each team can only access its own namespace. This option allows you to use fewer clusters and projects than creating one project or cluster per team, which reduces costs and complexity. It also allows you to isolate each team's environment by using namespaces and RBAC, which prevents teams from accessing other teams' environments.
質問 # 81
You have a CI/CD pipeline that uses Cloud Build to build new Docker images and push them to Docker Hub. You use Git for code versioning. After making a change in the Cloud Build YAML configuration, you notice that no new artifacts are being built by the pipeline. You need to resolve the issue following Site Reliability Engineering practices. What should you do?
- A. Upload the configuration YAML file to Cloud Storage and use Error Reporting to identify and fix the issue.
- B. Run a Git compare between the previous and current Cloud Build Configuration files to find and fix the bug.
- C. Change the CI pipeline to push the artifacts to Container Registry instead of Docker Hub.
- D. Disable the CI pipeline and revert to manually building and pushing the artifacts.
正解:B
質問 # 82
You are designing a deployment technique for your applications on Google Cloud. As part Of your deployment planning, you want to use live traffic to gather performance metrics for new versions Of your applications. You need to test against the full production load before your applications are launched. What should you do?
- A. Use shadow testing with continuous deployment.
- B. Use A/B testing with blue/green deployment.
- C. Use canary testing with rolling updates deployment,
- D. Use canary testing with continuous deployment.
正解:A
解説:
The correct answer is B, Use shadow testing with continuous deployment.
Shadow testing is a deployment technique that involves routing a copy of the live traffic to a new version of the application, without affecting the production environment. This way, you can gather performance metrics and compare them with the current version, without exposing the new version to the users. Shadow testing can help you test against the full production load and identify any issues or bottlenecks before launching the new version. You can use continuous deployment to automate the process of deploying the new version after it passes the shadow testing.
Reference:
Application deployment and testing strategies, Testing strategies, Shadow test pattern.
質問 # 83
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