PROFESSIONAL-CLOUD-DEVOPS-ENGINEER SURE ANSWERS & PROFESSIONAL-CLOUD-DEVOPS-ENGINEER FREE TORRENT & PROFESSIONAL-CLOUD-DEVOPS-ENGINEER EXAM GUIDE

Professional-Cloud-DevOps-Engineer Sure Answers & Professional-Cloud-DevOps-Engineer Free Torrent & Professional-Cloud-DevOps-Engineer Exam Guide

Professional-Cloud-DevOps-Engineer Sure Answers & Professional-Cloud-DevOps-Engineer Free Torrent & Professional-Cloud-DevOps-Engineer Exam Guide

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q52-Q57):

NEW QUESTION # 52
Your team uses Cloud Build for all CI/CO pipelines. You want to use the kubectl builder for Cloud Build to deploy new images to Google Kubernetes Engine (GKE). You need to authenticate to GKE while minimizing development effort. What should you do?

  • A. Create a new service account with the Container Developer role and use it to run Cloud Build.
  • B. Specify the Container Developer role for Cloud Build in the cloudbuild.yaml file.
  • C. Create a separate step in Cloud Build to retrieve service account credentials and pass these to kubectl.
  • D. Assign the Container Developer role to the Cloud Build service account.

Answer: A


NEW QUESTION # 53
Your company runs services by using Google Kubernetes Engine (GKE). The GKE clusters in the development environment run applications with verbose logging enabled. Developers view logs by using the kubect1 logs command and do not use Cloud Logging. Applications do not have a uniform logging structure defined. You need to minimize the costs associated with application logging while still collecting GKE operational logs. What should you do?

  • A. Run the gcloud logging sinks update _Defau1t --disabled command in the project associated with the development environment.
  • B. Run the gcloud container clusters update --logging-SYSTEM command for the development cluster.
  • C. Add the severity >= DEBUG resource. type "k83 container" exclusion filter to the Default logging sink in the project associated with the development environment.
  • D. Run the gcloud container clusters update logging=WORKLOAD command for the development cluster.

Answer: B


NEW QUESTION # 54
You manage several production systems that run on Compute Engine in the same Google Cloud Platform (GCP) project. Each system has its own set of dedicated Compute Engine instances. You want to know how must it costs to run each of the systems. What should you do?

  • A. Assign all instances a label specific to the system they run. Configure BigQuery billing export and query costs per label.
  • B. Name each virtual machine (VM) after the system it runs. Set up a usage report export to a Cloud Storage bucket. Configure the bucket as a source in BigQuery to query costs based on VM name.
  • C. In the Google Cloud Platform Console, use the Cost Breakdown section to visualize the costs per system.
  • D. Enrich all instances with metadata specific to the system they run. Configure Stackdriver Logging to export to BigQuery, and query costs based on the metadata.

Answer: A

Explanation:
https://cloud.google.com/billing/docs/how-to/export-data-bigquery


NEW QUESTION # 55
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 Ofyour applications. You need to test against the full production load before your applications are launched. What should you do?

  • A. Use A/B testing with blue/green deployment.
  • B. Use canary testing with continuous deployment.
  • C. Use canary testing with rolling updates deployment,
  • D. Use shadow testing with continuous deployment.

Answer: D

Explanation:
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.


NEW QUESTION # 56
You support a web application that runs on App Engine and uses CloudSQL and Cloud Storage for data storage. After a short spike in website traffic, you notice a big increase in latency for all user requests, increase in CPU use, and the number of processes running the application. Initial troubleshooting reveals:
After the initial spike in traffic, load levels returned to normal but users still experience high latency.
Requests for content from the CloudSQL database and images from Cloud Storage show the same high latency.
No changes were made to the website around the time the latency increased.
There is no increase in the number of errors to the users.
You expect another spike in website traffic in the coming days and want to make sure users don't experience latency. What should you do?

  • A. Enable high availability on the CloudSQL instances.
  • B. Upgrade the GCS buckets to Multi-Regional.
  • C. Move the application from App Engine to Compute Engine.
  • D. Modify the App Engine configuration to have additional idle instances.

Answer: A


NEW QUESTION # 57
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These Google Professional-Cloud-DevOps-Engineer Exam questions help you practice theoretical and practical skills in different aspects, making problem-solving easier. Our Google Professional-Cloud-DevOps-Engineer questions PDF is a complete bundle of problems presenting the versatility and correlativity of questions observed in past exam papers. These questions are bundled into Google Professional-Cloud-DevOps-Engineer PDF Questions following the official study guide.

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