Free Access to Google.Professional-Cloud-DevOps-Engineer.v2024-08-12.q133 with Valid Practice Test (Page 14)

Question 61

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.In the Google Cloud Platform Console, use the Cost Breakdown section to visualize the costs per system.
B.Assign all instances a label specific to the system they run. Configure BigQuery billing export and query costs per label.
C.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.
D.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.

Question 62

Your company runs applications in Google Kubernetes Engine (GKE). Several applications rely on ephemeral volumes. You noticed some applications were unstable due to the DiskPressure node condition on the worker nodes. You need to identify which Pods are causing the issue, but you do not have execute access to workloads and nodes. What should you do?

A.Check the node/ephemeral_storage/used_bytes metric by using Metrics Explorer.
B.Check the metric by using Metrics Explorer.
C.Locate all the Pods with emptyDir volumes. use the df-h command to measure volume disk usage.
D.Locate all the Pods with emptyDir volumes. Use the du -sh * command to measure volume disk usage.

Question 63

You support an application deployed on Compute Engine. The application connects to a Cloud SQL instance to store and retrieve dat a. After an update to the application, users report errors showing database timeout messages. The number of concurrent active users remained stable. You need to find the most probable cause of the database timeout. What should you do?

A.Use Cloud Security Scanner to see whether your Cloud SQL is under a Distributed Denial of Service (DDoS) attack.
B.Check the serial port logs of the Compute Engine instance.
C.Determine whether there is an increased number of connections to the Cloud SQL instance.
D.Use Stackdriver Profiler to visualize the resources utilization throughout the application.

Question 64

You are implementing a CI'CD pipeline for your application in your company s multi-cloud environment Your application is deployed by using custom Compute Engine images and the equivalent in other cloud providers You need to implement a solution that will enable you to build and deploy the images to your current environment and is adaptable to future changes Which solution stack should you use'?

A.Cloud Build with Packer
B.Cloud Build with Google Cloud Deploy
C.Google Kubernetes Engine with Google Cloud Deploy
D.Cloud Build with kpt

Correct Answer: B

Cloud Build is a fully managed continuous integration and continuous delivery (CI/CD) service that helps you automate your builds, tests, and deployments. Google Cloud Deploy is a service that automates the deployment of your applications to Google Kubernetes Engine (GKE).
Together, Cloud Build and Google Cloud Deploy can be used to build and deploy your application's custom Compute Engine images to your current environment and to other cloud providers in the future.
Here are the steps involved in using Cloud Build and Google Cloud Deploy to implement a CI/CD pipeline for your application:
Create a Cloud Build trigger that fires whenever a change is made to your application's code.
In the Cloud Build trigger, configure Cloud Build to build your application's Docker image.
Create a Google Cloud Deploy configuration file that specifies how to deploy your application's Docker image to GKE.
In Google Cloud Deploy, create a deployment that uses your configuration file.
Once you have created the Cloud Build trigger and Google Cloud Deploy configuration file, any changes made to your application's code will trigger Cloud Build to build a new Docker image. Google Cloud Deploy will then deploy the new Docker image to GKE.
This solution stack is adaptable to future changes because it uses a cloud-agnostic approach. Cloud Build can be used to build Docker images for any cloud provider, and Google Cloud Deploy can be used to deploy Docker images to any Kubernetes cluster.
The other solution stacks are not as adaptable to future changes. For example, solution stack A (Cloud Build with Packer) is limited to building Docker images for Compute Engine. Solution stack C (Google Kubernetes Engine with Google Cloud Deploy) is limited to deploying Docker images to GKE. Solution stack D (Cloud Build with kpt) is a newer solution that is not yet as mature as Cloud Build and Google Cloud Deploy.
Overall, the best solution stack for implementing a CI/CD pipeline for your application in a multi-cloud environment is Cloud Build with Google Cloud Deploy. This solution stack is fully managed, cloud-agnostic, and adaptable to future changes.

Question 65

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

Question 61

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