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Google Professional-Cloud-DevOps-Engineer Exam is designed to test the candidate's knowledge and skills related to DevOps engineering practices and Google Cloud technologies. Professional-Cloud-DevOps-Engineer exam comprises of two sections – the first section includes multiple-choice questions, while the second section includes practical scenarios that test the candidate's ability to apply their knowledge and skills to real-world situations.

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The Google Professional-Cloud-DevOps-Engineer exam covers a wide range of topics including continuous integration and delivery, infrastructure as code, monitoring and logging, automation, and security. It is a comprehensive exam that tests the candidate's ability to design and implement efficient cloud-based systems using Google Cloud technologies. Professional-Cloud-DevOps-Engineer Exam is intended for individuals who have a strong understanding of the DevOps principles and practices and are looking to enhance their skills in cloud-based systems management.

Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q127-Q132):

NEW QUESTION # 127
You support a service with a well-defined Service Level Objective (SLO). Over the previous 6 months, your service has consistently met its SLO and customer satisfaction has been consistently high. Most of your service's operations tasks are automated and few repetitive tasks occur frequently. You want to optimize the balance between reliability and deployment velocity while following site reliability engineering best practices.
What should you do? (Choose two.)

A. Make the service's SLO more strict.
B. Change the implementation of your Service Level Indicators (SLIs) to increase coverage.
C. Shift engineering time to other services that need more reliability.
D. Get the product team to prioritize reliability work over new features.
E. Increase the service's deployment velocity and/or risk.

Answer: C,E

Explanation:
Explanation
(https://sre.google/workbook/implementing-slos/#slo-decision-matrix)

NEW QUESTION # 128
You need to create a Cloud Monitoring SLO for a service that will be published soon. You want to verify that requests to the service will be addressed in fewer than 300 ms at least 90% Of the time per calendar month. You need to identify the metric and evaluation method to use. What should you do?

A. Select an availability metric for a request-based method of evaluation.
B. Select a latency metric for a request-based method of evaluation.
C. Select an availability metric for a window-based method Of evaluation.
D. Select a latency metric for a window-based method of evaluation.

Answer: B

NEW QUESTION # 129
Your team is designing a new application for deployment into Google Kubernetes Engine (GKE). You need to set up monitoring to collect and aggregate various application-level metrics in a centralized location. You want to use Google Cloud Platform services while minimizing the amount of work required to set up monitoring.
What should you do?

A. Publish various metrics from the application directly to the Stackdriver Monitoring API, and then observe these custom metrics in Stackdriver.
B. Emit all metrics in the form of application-specific log messages, pass these messages from the containers to the Stackdriver logging collector, and then observe metrics in Stackdriver.
C. Install the OpenTelemetry client libraries in the application, configure Stackdriver as the export destination for the metrics, and then observe the application's metrics in Stackdriver.
D. Install the Cloud Pub/Sub client libraries, push various metrics from the application to various topics, and then observe the aggregated metrics in Stackdriver.

Answer: C

NEW QUESTION # 130
You are designing a system with three different environments: development, quality assurance (QA), and production.
Each environment will be deployed with Terraform and has a Google Kubemetes Engine (GKE) cluster created so that application teams can deploy their applications. Anthos Config Management will be used and templated to deploy infrastructure level resources in each GKE cluster. All users (for example, infrastructure operators and application owners) will use GitOps. How should you structure your source control repositories for both Infrastructure as Code (laC) and application code?

A. Cloud Infrastructure (Terraform) repository is shared: different branches are different environmentsGKE Infrastructure (Anthos Config Management Kustomize manifests) repository is shared: differentoverlay directories are different environmentsApplication (app source code) repository is shared: different directories are different features
B. Cloud Infrastructure (Terraform) repository is shared: different directories are different environmentsGKE Infrastructure (Anthos Config Management Kustomize manifests) repositories are separated:different branches are different environmentsApplication (app source code) repositories are separated: different branches are different features
C. Cloud Infrastructure (Terraform) repositories are separated: different branches are different environmentsGKE Infrastructure (Anthos Config Management Kustomize manifests) repositories are separated:different overlay directories are different environmentsApplication (app source code) repositories are separated: different branches are different features
D. Cloud Infrastructure (Terraform) repository is shared: different directories are different environmentsGKE Infrastructure (Anthos Config Management Kustomize manifests) repository is shared: differentoverlay directories are different environmentsApplication (app source code) repositories are separated: different branches are different features

Answer: B

Explanation:
The correct answer is B. Cloud Infrastructure (Terraform) repository is shared: different directories are different environments. GKE Infrastructure (Anthos Config Management Kustomize manifests) repositories are separated: different branches are different environments. Application (app source code) repositories are separated: different branches are different features.
This answer follows the best practices for using Terraform and Anthos Config Management with GitOps, as described in the following sources:
For Terraform, it is recommended to use a single repository for all environments, and use directories to separate them. This way, you can reuse the same Terraform modules and configurations across environments, and avoid code duplication and drift.You can also use Terraform workspaces to isolate the state files for each environment12.
For Anthos Config Management, it is recommended to use separate repositories for each environment, and use branches to separate the clusters within each environment. This way, you can enforce different policies and configurations for each environment, and use pull requests to promote changes across environments.You can also use Kustomize to create overlays for each cluster that apply specific patches or customizations34.
For application code, it is recommended to use separate repositories for each application, and use branches to separate the features or bug fixes for each application. This way, you can isolate the development and testing of each application, and use pull requests to merge changes into the main branch.You can also use tags or labels to trigger deployments to different environments5.
References:
1:Best practices for using Terraform | Google Cloud
2: Terraform Recommended Practices - Part 1 | Terraform - HashiCorp Learn
3:Deploy Anthos on GKE with Terraform part 1: GitOps with Config Sync | Google Cloud Blog
4: Using Kustomize with Anthos Config Management | Anthos Config Management Documentation | Google Cloud
5: Deploy Anthos on GKE with Terraform part 3: Continuous Delivery with Cloud Build | Google Cloud Blog GitOps-style continuous delivery with Cloud Build | Cloud Build Documentation | Google Cloud

NEW QUESTION # 131
You need to run a business-critical workload on a fixed set of Compute Engine instances for several months.
The workload is stable with the exact amount of resources allocated to it. You want to lower the costs for this workload without any performance implications. What should you do?

A. Convert the instances to preemptible virtual machines.
B. Migrate the instances to a Managed Instance Group.
C. Create an Unmanaged Instance Group for the instances used to run the workload.
D. Purchase Committed Use Discounts.

Answer: D

NEW QUESTION # 132
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