Free Access Google.Professional-Cloud-DevOps-Engineer.v2026-09-16.q209 Practice Test (Page 42)

Question 201

You have a set of applications running on a Google Kubernetes Engine (GKE) cluster, and you are using Stackdriver Kubernetes Engine Monitoring. You are bringing a new containerized application required by your company into production. This application is written by a third party and cannot be modified or reconfigured. The application writes its log information to /var/log/app_messages.log, and you want to send these log entries to Stackdriver Logging. What should you do?

A.Write a script to tail the log file within the pod and write entries to standard output. Run the script as a sidecar container with the application's pod. Configure a shared volume between the containers to allow the script to have read access to /var/log in the application container.

B.Install Kubernetes on Google Compute Engine (GCE> and redeploy your applications. Then customize the built-in Stackdriver Logging configuration to tail the log file in the application's pods and write to Stackdriver Logging.

C.Use the default Stackdriver Kubernetes Engine Monitoring agent configuration.

D.Deploy a Fluentd daemonset to GKE. Then create a customized input and output configuration to tail the log file in the application's pods and write to Slackdriver Logging.

Question 202

You support an e-commerce application that runs on a large Google Kubernetes Engine (GKE) cluster deployed on-premises and on Google Cloud Platform. The application consists of microservices that run in containers. You want to identify containers that are using the most CPU and memory. What should you do?

A.Use Stackdriver Kubernetes Engine Monitoring.

B.Use Prometheus to collect and aggregate logs per container, and then analyze the results in Grafana.

C.Use the Stackdriver Monitoring API to create custom metrics, and then organize your containers using groups.

D.Use Stackdriver Logging to export application logs to BigOuery. aggregate logs per container, and then analyze CPU and memory consumption.

Question 203

You are creating a CI/CD pipeline to perform Terraform deployments of Google Cloud resources Your CI/CD tooling is running in Google Kubernetes Engine (GKE) and uses an ephemeral Pod for each pipeline run You must ensure that the pipelines that run in the Pods have the appropriate Identity and Access Management (1AM) permissions to perform the Terraform deployments You want to follow Google-recommended practices for identity management What should you do?
Choose 2 answers

A.Create a new Kubernetes service account, and assign the service account to the Pods Use Workload Identity to authenticate as the Google service account

B.Create a new JSON service account key for the Google service account store the key as a Kubernetes secret, inject the key into the Pods, and set the boogle_application_credentials environment variable

C.Create a new Google service account, and assign the appropriate 1AM permissions

D.Create a new JSON service account key for the Google service account store the key in the secret management store for the CI/CD tool and configure Terraform to use this key for authentication

E.Assign the appropriate 1AM permissions to the Google service account associated with the Compute Engine VM instances that run the Pods

Question 204

You support an application that stores product information in cached memory. For every cache miss, an entry is logged in Stackdriver Logging. You want to visualize how often a cache miss happens over time. What should you do?

A.Link Stackdriver Logging as a source in Google Data Studio. Filler (he logs on the cache misses.

B.Create a logs-based metric in Stackdriver Logging and a dashboard for that metric in Stackdriver Monitoring.

C.Configure BigOuery as a sink for Stackdriver Logging. Create a scheduled query to filter the cache miss logs and write them to a separate table

D.Configure Stackdriver Profiler to identify and visualize when the cache misses occur based on the logs.

Question 205

Your organization is running multiple Google Kubernetes Engine (GKE) clusters in a project. You need to design a highly-available solution to collect and query both domain-specific workload metrics and GKE default metrics across all clusters, while minimizing operational overhead. What should you do?

A.Use Prometheus Operator to install Prometheus in every cluster and scrape the metrics. Ensure that a Thanos sidecar is enabled on every Prometheus instance. Configure Thanos in the central cluster. Query the central Thanos instance.

B.Use Prometheus Operator to install Prometheus in every cluster and scrape the metrics. Configure remote-write to one central Prometheus. Query the central Prometheus instance.

C.Enable managed collection on every GKE cluster. Query the metrics in Cloud Monitoring.

D.Enable managed collection on every GKE cluster. Query the metrics in BigQuery.

Other Version: 983Google.Professional-Cloud-DevOps-Engineer.v2026-03-30.q189; 2958Google.Professional-Cloud-DevOps-Engineer.v2025-09-27.q141; 1261Google.Professional-Cloud-DevOps-Engineer.v2023-01-21.q29; 2522Google.Professional-Cloud-DevOps-Engineer.v2022-06-30.q61; 2690Google.Professional-Cloud-DevOps-Engineer.v2022-04-13.q62; 65Google.Pass4surecert.Professional-Cloud-DevOps-Engineer.v2021-09-22.by.horace.37q.pdf

Latest Upload: 165Google.Professional-Cloud-DevOps-Engineer.v2026-09-16.q209; 148AAPC.CPC.v2026-09-16.q132; 116HP.HPE0-J82.v2026-09-16.q26; 178F5.303.v2026-09-16.q147; 169PaloAltoNetworks.NGFW-Engineer.v2026-09-16.q105; 127Workday.Workday-Pro-Recruiting.v2026-09-15.q19; 141ACAMS.CAMS-FCI.v2026-09-15.q36; 157VMware.250-614.v2026-09-15.q42; 184IAPP.CIPM.v2026-09-15.q217; 170VMware.2V0-13.25.v2026-09-14.q122

Question 201

Question 202

Question 203

Question 204

Question 205

Download PDF File