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Google Professional-Cloud-DevOps-Engineer (Google Cloud Certified - Professional Cloud DevOps Engineer) Certification Exam is a professional-level exam designed to validate the skills and knowledge of individuals in the field of cloud DevOps engineering. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification exam is intended for individuals who have experience in cloud computing, software development, and DevOps practices. Professional-Cloud-DevOps-Engineer Exam assesses the candidate's ability to design, develop, and implement cloud solutions using Google Cloud Platform (GCP) services and tools.

Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q79-Q84):

NEW QUESTION # 79
Your organization recently adopted a container-based workflow for application development. Your team develops numerous applications that are deployed continuously through an automated build pipeline to a Kubernetes cluster in the production environment. The security auditor is concerned that developers or operators could circumvent automated testing and push code changes to production without approval. What should you do to enforce approvals?

A. Leverage Kubernetes Role-Based Access Control (RBAC) to restrict access to only approved users.
B. Configure the build system with protected branches that require pull request approval.
C. Use an Admission Controller to verify that incoming requests originate from approved sources.
D. Enable binary authorization inside the Kubernetes cluster and configure the build pipeline as an attestor.

Answer: D

NEW QUESTION # 80
Your team has recently deployed an NGINX-based application into Google Kubernetes Engine (GKE) and has exposed it to the public via an HTTP Google Cloud Load Balancer (GCLB) ingress. You want to scale the deployment of the application's frontend using an appropriate Service Level Indicator (SLI). What should you do?

A. Configure the vertical pod autoscaler in GKE and enable the cluster autoscaler to scale the cluster as pods expand.
B. Install the Stackdriver custom metrics adapter and configure a horizontal pod autoscaler to use the number of requests provided by the GCLB.
C. Configure the horizontal pod autoscaler to use the average response time from the Liveness and Readiness probes.
D. Expose the NGINX stats endpoint and configure the horizontal pod autoscaler to use the request metrics exposed by the NGINX deployment.

Answer: A

NEW QUESTION # 81
You encountered a major service outage that affected all users of the service for multiple hours. After several hours of incident management, the service returned to normal, and user access was restored. You need to provide an incident summary to relevant stakeholders following the Site Reliability Engineering recommended practices. What should you do first?

A. Call individual stakeholders lo explain what happened.
B. Send the Incident State Document to all the stakeholders.
C. Require the engineer responsible to write an apology email to all stakeholders.
D. Develop a post-mortem to be distributed to stakeholders.

Answer: A

NEW QUESTION # 82
You need to deploy a new service to production. The service needs to automatically scale using a Managed Instance Group (MIG) and should be deployed over multiple regions. The service needs a large number of resources for each instance and you need to plan for capacity. What should you do?

A. Monitor results of Stackdriver Trace to determine the required amount of resources.
B. Deploy the service in one region and use a global load balancer to route traffic to this region.
C. Use the n2-highcpu-96 machine type in the configuration of the MIG.
D. Validate that the resource requirements are within the available quota limits of each region.

Answer: D

NEW QUESTION # 83
You are deploying an application to Cloud Run. The application requires a password to start. Your organization requires that all passwords are rotated every 24 hours, and your application must have the latest password. You need to deploy the application with no downtime. What should you do?

A. Store the password in Secret Manager and mount the secret as a volume within the application.
B. Store the password in Secret Manager and send the secret to the application by using environment variables.
C. Use Cloud Build to add your password into the application container at build time. Ensure that Artifact Registry is secured from public access.
D. Store the password directly in the code. Use Cloud Build to rebuild and deploy the application each time the password changes.

Answer: A

Explanation:
Explanation
The correct answer is B. Store the password in Secret Manager and mount the secret as a volume within the application.
Secret Manager is a service that allows you to securely store and manage sensitive data such as passwords, API keys, certificates, and tokens. You can use Secret Manager to rotate your secrets automatically or manually, and access them from your Cloud Run applications1.
There are two ways to use secrets from Secret Manager in Cloud Run:
As environment variables: You can set environment variables that point to secrets in Secret Manager.
Cloud Run will resolve the secrets at runtime and inject them into the environment of your application.
However, this method has some limitations, such as:
The environment variables are cached for up to 10 minutes, so you may not get the latest version of the secret immediately.
The environment variables are visible in plain text in the Cloud Console and the Cloud SDK, which may expose sensitive information.
The environment variables are limited to 4 KB of data, which may not be enough for some secrets.2 As file system volumes: You can mount secrets from Secret Manager as files in a volume within your application. Cloud Run will create a tmpfs volume and write the secrets as files in it. This method has some advantages, such as:
The files are updated every 30 seconds, so you can get the latest version of the secret faster.
The files are not visible in the Cloud Console or the Cloud SDK, which provides better security.
The files can store up to 64 KB of data, which allows for larger secrets.3 Therefore, for your use case, it is better to use the second method and mount the secret as a file system volume within your application. This way, you can ensure that your application has the latest password, and you can deploy it with no downtime.
To mount a secret as a file system volume in Cloud Run, you can use the following command:
gcloud beta run deploy SERVICE --image IMAGE_URL --update-secrets=/path/to/file=secretName:version where:
SERVICE is the name of your Cloud Run service.
IMAGE_URL is the URL of your container image.
/path/to/file is the path where you want to mount the secret file in your application.
secretName is the name of your secret in Secret Manager.
version is the version of your secret. You can use latest to get the most recent version.3 You can also use the Cloud Console to mount secrets as file system volumes. For more details, see Mounting secrets from Secret Manager.
References:
1: Overview | Secret Manager Documentation | Google Cloud
2: Using secrets as environment variables | Cloud Run Documentation | Google Cloud
3: Mounting secrets from Secret Manager | Cloud Run Documentation | Google Cloud

NEW QUESTION # 84
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