{Online Realistic} Google Professional-Cloud-DevOps-Engineer Practice Test Questions

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Google Professional-Cloud-DevOps-Engineer Certification is a highly esteemed certification program for professionals seeking to validate their expertise in cloud-based DevOps engineering. It is designed to test the knowledge and skills required to deploy, manage, and monitor secure, scalable, and highly available cloud-based infrastructure and applications.

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Google Professional-Cloud-DevOps-Engineer Certification is highly valued in the industry and is recognized by leading companies that use Google Cloud Platform (GCP). Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification is an indication of the candidate's ability to design, develop, and manage cloud-based solutions using best practices and industry standards. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification provides an edge to the candidate in the job market and can lead to better career opportunities and higher salaries.

Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q115-Q120):

NEW QUESTION # 115
Your team is designing a new application for deployment both inside and outside Google Cloud Platform (GCP). You need to collect detailed metrics such as system resource utilization. You want to use centralized GCP services while minimizing the amount of work required to set up this collection system. What should you do?

A. Install an Application Performance Monitoring (APM) tool in both locations, and configure an export to a central data storage location for analysis.
B. Import the Stackdriver Profiler package, and configure it to relay function timing data to Stackdriver for further analysis.
C. Instrument the code using a timing library, and publish the metrics via a health check endpoint that is scraped by Stackdriver.
D. Import the Stackdriver Debugger package, and configure the application to emit debug messages with timing information.

Answer: B

NEW QUESTION # 116
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?

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.
B. Configure Config Connector with the GitHub repository. When there is a change in the repository, use Config Connector to apply the change.
C. Configure Config Sync with the GitHub repository. When there is a change in the repository, use Config Sync to apply the change.
D. When there is a change in GitHub, use a webhook to send a request to Cloud Service Mesh, and apply the change.

Answer: C

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.

NEW QUESTION # 117
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?

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.
B. Configure Config Connector with the GitHub repository. When there is a change in the repository, use Config Connector to apply the change.
C. Configure Config Sync with the GitHub repository. When there is a change in the repository, use Config Sync to apply the change.
D. When there is a change in GitHub, use a webhook to send a request to Cloud Service Mesh, and apply the change.

Answer: C

NEW QUESTION # 118
Your team of Infrastructure DevOps Engineers is growing, and you are starting to use Terraform to manage infrastructure. You need a way to implement code versioning and to share code with other team members.
What should you do?

A. Store the Terraform code in a version-control system. Establish procedures for pushing new versions and merging with the master.
B. Store the Terraform code in a shared Google Drive folder so it syncs automatically to every team member's computer. Organize files with a naming convention that identifies each new version.
C. Store the Terraform code in a network shared folder with child folders for each version release. Ensure that everyone works on different files.
D. Store the Terraform code in a Cloud Storage bucket using object versioning. Give access to the bucket to every team member so they can download the files.

Answer: A

Explanation:
Explanation
https://www.terraform.io/docs/cloud/guides/recommended-practices/part3.3.html

NEW QUESTION # 119
You are the Operations Lead for an ongoing incident with one of your services. The service usually runs at around 70% capacity. You notice that one node is returning 5xx errors for all requests. There has also been a noticeable increase in support cases from customers. You need to remove the offending node from the load balancer pool so that you can isolate and investigate the node. You want to follow Google-recommended practices to manage the incident and reduce the impact on users. What should you do?

A. 1. Communicate your intent to the incident team.
2. Perform a load analysis to determine if the remaining nodes can handle the increase in traffic offloaded from the removed node, and scale appropriately.
3. When any new nodes report healthy, drain traffic from the unhealthy node, and remove the unhealthy node from service.
B. 1 . Drain traffic from the unhealthy node and remove the node from service.
2. Monitor traffic to ensure that the error is resolved and that the other nodes in the pool are handling the traffic appropriately.
3. Scale the pool as necessary to handle the new load.
4. Communicate your actions to the incident team.
C. 1 . Drain traffic from the unhealthy node and remove the old node from service.
2. Add a new node to the pool, wait for the new node to report as healthy, and then serve traffic to the new node.
3. Monitor traffic to ensure that the pool is healthy and is handling traffic appropriately.
4. Communicate your actions to the incident team.
D. 1. Communicate your intent to the incident team.
2. Add a new node to the pool, and wait for the new node to report as healthy.
3. When traffic is being served on the new node, drain traffic from the unhealthy node, and remove the old node from service.

Answer: A

Explanation:
Explanation
The correct answer is A. Communicate your intent to the incident team. Perform a load analysis to determine if the remaining nodes can handle the increase in traffic offloaded from the removed node, and scale appropriately. When any new nodes report healthy, drain traffic from the unhealthy node, and remove the unhealthy node from service.
This answer follows the Google-recommended practices for incident management, as described in the Chapter
9 - Incident Response, Google SRE Book1. According to this source, some of the best practices are:
Maintain a clear line of command. Designate clearly defined roles. Keep a working record of debugging and mitigation as you go. Declare incidents early and often.
Communicate your intent before taking any action that might affect the service or the incident response.
This helps to avoid confusion, duplication of work, or unintended consequences.
Perform a load analysis before removing a node from the load balancer pool, as this might affect the capacity and performance of the service. Scale the pool as necessary to handle the expected load.
Drain traffic from the unhealthy node before removing it from service, as this helps to avoid dropping requests or causing errors for users.
Answer A follows these best practices by communicating the intent to the incident team, performing a load analysis and scaling the pool, and draining traffic from the unhealthy node before removing it.
Answer B does not follow the best practice of performing a load analysis before adding or removing nodes, as this might cause overloading or underutilization of resources.
Answer C does not follow the best practice of communicating the intent before taking any action, as this might cause confusion or conflict with other responders.
Answer D does not follow the best practice of draining traffic from the unhealthy node before removing it, as this might cause errors for users.
References:
1: Chapter 9 - Incident Response, Google SRE Book

NEW QUESTION # 120
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