Google edusum cloud Devops Engineer Changed Professional-cloud-devops-engineer Questions by Junior q65 vce pdf

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Exam Name:	Google Cloud Certified - Professional Cloud DevOps Engineer Exam
Exam Code:	Professional-Cloud-DevOps-Engineer Dumps
Vendor:	Google	Certification:	Cloud DevOps Engineer
Questions:	194 Q&A's	Shared By:	junior

Question 12

You need to enforce several constraint templates across your Google Kubernetes Engine (GKE) clusters. The constraints include policy parameters, such as restricting the Kubernetes API. You must ensure that the policy parameters are stored in a GitHub repository and automatically applied when changes occur. What should you do?

Options:

Set up a GitHub action to trigger Cloud Build when there is a parameter change. In Cloud Build, run a gcloud CLI command to apply the change.

When there is a change in GitHub, use a webhook to send a request to Cloud Service Mesh, and apply the change.

Configure Config Sync with the GitHub repository. When there is a change in the repository, use Config Sync to apply the change.

Configure Config Connector with the GitHub repository. When there is a change in the repository, use Config Connector to apply the change.

Discussion

Answer:

Explanation:

Comprehensive and Detailed Explanation From General GKE and GitOps Knowledge:

The requirements are:

Enforce constraint templates (implying a policy agent like OPA Gatekeeper) on GKE.

Store policy parameters in a GitHub repository.

Automatically apply changes from the GitHub repository to the clusters.

This is a classic GitOps scenario.

A. Set up a GitHub action to trigger Cloud Build when there is a parameter change. In Cloud Build, run a gcloud CLI command to apply the change.This is a plausible CI/CD approach. GitHub Actions can trigger Cloud Build, which can then use kubectl or gcloud to apply configurations. However, this is a push-based imperative approach. GitOps tools offer a more declarative, pull-based model specifically designed for syncing Kubernetes configurations.

B. When there is a change in GitHub, use a webhook to send a request to Cloud Service Mesh, and apply the change.Cloud Service Mesh (based on Istio) is primarily for managing traffic, security, and observability for microservices. It's not designed for applying general Kubernetes policy configurations like Gatekeeper constraints from a Git repository.

C. Configure Config Sync with the GitHub repository. When there is a change in the repository, use Config Sync to apply the change.Config Sync is a Google Cloud product specifically designed for GitOps with GKE (and other Kubernetes clusters). It synchronizes configurations (including CustomResourceDefinitions for constraint templates and the constraints themselves) from a Git repository (like GitHub) to your clusters. It continuously monitors the repository and automatically applies any committed changes to the clusters, ensuring they remain in the desired state. This perfectly matches the requirements.

D. Configure Config Connector with the GitHub repository. When there is a change in the repository, use Config Connector to apply the change.Config Connector allows you to manage Google Cloud resources (like Pub/Sub topics, Spanner instances, etc.) using Kubernetes-style declarative configurations and kubectl. While it uses Kubernetes tooling, its primary purpose is managing Google Cloud resources, not syncing general Kubernetes configurations like Gatekeeper constraints from Git. Config Sync is the tool for syncing arbitrary Kubernetes manifests from Git to a cluster.

Config Sync is the Google Cloud tool built for the exact purpose described: maintaining consistency between Kubernetes cluster configurations and a Git repository using a GitOps model.

Reference (Based on Google Cloud GKE and Config Sync documentation):

Config Sync Overview: https://cloud.google.com/anthos-config-management/docs/config-sync-overview or https://cloud.google.com/kubernetes-engine/docs/add-on/config-sync/overview (if referring to it as a GKE add-on). "Config Sync is a GitOps tool that helps you keep your Google Kubernetes Engine (GKE) Enterprise edition clusters synchronized with configs stored in a Git repository."

It supports syncing various Kubernetes objects, including CustomResources, which are used by OPA Gatekeeper for defining constraints and constraint templates.

It automatically pulls changes from the Git repository and applies them, which meets the "automatically applied when changes occur" requirement.

Question 13

You have a CI/CD pipeline that uses Cloud Build to build new Docker images and push them to Docker Hub. You use Git for code versioning. After making a change in the Cloud Build YAML configuration, you notice that no new artifacts are being built by the pipeline. You need to resolve the issue following Site Reliability Engineering practices. What should you do?

Options:

Disable the CI pipeline and revert to manually building and pushing the artifacts.

Change the CI pipeline to push the artifacts to Container Registry instead of Docker Hub.

Upload the configuration YAML file to Cloud Storage and use Error Reporting to identify and fix the issue.

Run a Git compare between the previous and current Cloud Build Configuration files to find and fix the bug.

Discussion

Question 14

You are creating Cloud Logging sinks to export log entries from Cloud Logging to BigQuery for future analysis Your organization has a Google Cloud folder named Dev that contains development projects and a folder named Prod that contains production projects Log entries for development projects must be exported to dev_dataset. and log entries for production projects must be exported to prod_datasetYou need to minimize the number of log sinks created and you want to ensure that the log sinks apply to future projects What should you do?

Options:

Create a single aggregated log sink at the organization level.

Create a log sink in each project

Create two aggregated log sinks at the organization level, and filter by project ID

Create an aggregated Iog sink in the Dev and Prod folders

Discussion

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Question 15

Your application’s performance in Google Cloud has degraded since the last release. You suspect that downstream dependencies might be causing some requests to take longer to complete. You need to investigate the issue with your application to determine the cause. What should you do?

Options:

Configure Cloud Trace in your application.

Configure Error Reporting in your application.

Configure Cloud Profiler in your application.

Configure Google Cloud Managed Service for Prometheus in your application.