Google Cloud Certified - Professional Cloud DevOps Engineer의 출제 기준은 시험 주관사의 정책에 따라 수시로 조정됩니다. Fast2test은 2026년에도 Professional-Cloud-DevOps-Engineer 연습문제를 꾸준히 검토하고 갱신하여, 208문항 전체가 최신 시험 기준을 반영하도록 관리하고 있습니다.

Google Professional-Cloud-DevOps-Engineer 시험 개요:

Google Professional-Cloud-DevOps-Engineer 시험 요강 주제:

Professional-Cloud-DevOps-Engineer 수험생을 위한 핵심 질문과 답변

최신 Cloud DevOps Engineer Professional-Cloud-DevOps-Engineer 무료샘플문제

문제 #1

You are running a real-time gaming application on Compute Engine that has a production and testing environment. Each environment has their own Virtual Private Cloud (VPC) network. The application frontend and backend servers are located on different subnets in the environment's VPC. You suspect there is a malicious process communicating intermittently in your production frontend servers. You want to ensure that network traffic is captured for analysis. What should you do?

A. Enable VPC Flow Logs on the testing and production VPC network frontend and backend subnets with a volume scale of 1.0. Apply changes in testing before production.
B. Enable VPC Flow Logs on the testing and production VPC network frontend and backend subnets with a volume scale of 0.5. Apply changes intesting before production.
C. Enable VPC Flow Logs on the production VPC network frontend and backend subnets only with a sample volume scale of 1.0.
D. Enable VPC Flow Logs on the production VPC network frontend and backend subnets only with a sample volume scale of 0.5.

문제 #2

You recently migrated an ecommerce application to Google Cloud. You now need to prepare the application for the upcoming peak traffic season. You want to follow Google-recommended practices. What should you do first to prepare for the busy season?

A. Pre-provision the additional compute power that was used last season, and expect growth.
B. Load test the application to profile its performance for scaling.
C. Migrate the application to Cloud Run, and use autoscaling.
D. Create a Terraform configuration for the application's underlying infrastructure to quickly deploy to additional regions.

문제 #3

You support a production service that runs on a single Compute Engine instance. You regularly need to spend time on recreating the service by deleting the crashing instance and creating a new instance based on the relevant image. You want to reduce the time spent performing manual operations while following Site Reliability Engineering principles. What should you do?

A. Create a Managed Instance Group with a single instance and use health checks to determine the system status.
B. File a bug with the development team so they can find the root cause of the crashing instance.
C. Add a Load Balancer in front of the Compute Engine instance and use health checks to determine the system status.
D. Create a Stackdriver Monitoring dashboard with SMS alerts to be able to start recreating the crashed instance promptly after it has crashed.

문제 #4

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

문제 #5

The new version of your containerized application has been tested and is ready to be deployed to production on Google Kubernetes Engine (GKE) You could not fully load-test the new version in your pre-production environment and you need to ensure that the application does not have performance problems after deployment Your deployment must be automated What should you do?

A. Deploy the application through a continuous delivery pipeline by using blue/green deployments Migrate traffic to the new version of the application and use Cloud Monitoring to look for performance issues
B. Deploy the application through a continuous delivery pipeline by using canary deployments Use Cloud Monitoring to look for performance issues, and ramp up traffic as supported by the metrics
C. Deploy the application by using kubectl and use Config Connector to slowly ramp up traffic between versions. Use Cloud Monitoring to look for performance issues
D. Deploy the application by using kubectl and set the spec. updatestrategy. type field to RollingUpdate Use Cloud Monitoring to look for performance issues, and run the kubectl rollback command if there are any issues.

질문과 대답: