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Google Professional-Cloud-DevOps-Engineer (Google Cloud Certified - Professional Cloud DevOps Engineer) Certification Exam is a highly sought-after certification in the technology industry. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification is aimed at professionals who are involved in the development, deployment, and management of cloud-based applications, services, and infrastructure. Professional-Cloud-DevOps-Engineer exam is designed to test the candidate's knowledge and skills in various areas such as cloud architecture, automation, security, compliance, and monitoring.

Google Professional-Cloud-DevOps-Engineer Certification Exam is a highly respected certification in the field of cloud computing. It is designed to validate the skills and knowledge of professionals who are responsible for building and managing cloud-based solutions using Google Cloud Platform. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification exam requires a deep understanding of DevOps practices, as well as a comprehensive knowledge of Google Cloud Platform tools and services.

Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q44-Q49):

NEW QUESTION # 44
You use Terraform to manage an application deployed to a Google Cloud environment The application runs on instances deployed by a managed instance group The Terraform code is deployed by using aCI/CD pipeline When you change the machine type on the instance template used by the managed instance group, the pipeline fails at the terraform apply stage with the following error message

You need to update the instance template and minimize disruption to the application and the number of pipeline runs What should you do?

A. Add a new instance template update the managed instance group to use the new instance template and delete the old instance template
B. Remove the managed instance group from the Terraform state file update the instance template and reimport the managed instance group.
C. Delete the managed instance group and recreate it after updating the instance template
D. Set the create_bef ore_destroy meta-argument to true in the lifecycle block on the instance template

Answer: D

NEW QUESTION # 45
Your company's security team needs to have read-only access to Data Access audit logs in the _Required bucket You want to provide your security team with the necessary permissions following the principle of least privilege and Google-recommended practices. What should you do?

A. Assign the roles/logging. viewer role to a group with all the security team members
B. Assign the roles/logging.privateLogViewer role to each member of the security team
C. Assign the roles/logging, viewer role to each member of the security team
D. Assign the roles/logging.privateLogviewer role to a group with all the security team members

Answer: D

Explanation:
The best option for providing your security team with the necessary permissions following the principle of least privilege and Google-recommended practices is to assign the roles/logging.privateLogViewer role to a group with all the security team members. The roles/logging.privateLogViewer role is a predefined role that grants read-only access to Data Access audit logs and other private logs in Cloud Logging. A group is a collection of users that can be assigned roles and permissions as a single unit. You can assign the roles/logging.privateLogViewer role to a group with all the security team members by using IAM policies. This way, you can provide your security team with the minimum level of access they need to view Data Access audit logs in the _Required bucket.

NEW QUESTION # 46
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. 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.
B. 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.
C. Publish various metrics from the application directly to the Slackdriver Monitoring API, and then observe these custom 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: B

NEW QUESTION # 47
You need to define Service Level Objectives (SLOs) for a high-traffic multi-region web application.
Customers expect the application to always be available and have fast response times. Customers are currently happy with the application performance and availability. Based on current measurement, you observe that the
90th percentile of latency is 120ms and the 95th percentile of latency is 275ms over a 28-day window. What latency SLO would you recommend to the team to publish?

A. 90th percentile - 120ms95th percentile - 275ms
B. 90th percentile - 100ms95th percentile - 250ms
C. 90th percentile - 250ms95th percentile - 400ms
D. 90th percentile - 150ms95th percentile - 300ms

Answer: D

Explanation:
https://sre.google/sre-book/service-level-objectives/

NEW QUESTION # 48
You are designing a new multi-tenant Google Kubernetes Engine (GKE) cluster for a customer. Your customer is concerned with the risks associated with long-lived credentials use. The customer requires that each GKE workload has the minimum Identity and Access Management (IAM) permissions set following the principle of least privilege (PoLP). You need to design an IAM impersonation solution while following Google-recommended practices. What should you do?

A. Create a Google service account.
Create a Kubernetes service account in a Workload Identity-enabled cluster.
Link the Google service account with the Kubernetes service account by using the roles/iam.
workloadIdentityUser role and iam.gke.io/gcp-service-account annotation.
Map the Kubernetes service account to the workload.
Repeat for each workload.
B. Create a Google service account.
Create a service account key for the Google service account.
Create a Kubernetes secret with a service account key.
Ensure that workload mounts the secret and set the GOOGLE_APPLICATION_CREDENTIALS environment variable to point at the mount path.
Repeat for each workload.
C. Create a Google service account.
Create a node pool, and set the Google service account as the default identity.
Ensure that workloads can only run on the designated node pool by using node selectors, taints, and tolerations.
Repeat for each workload.
D. Create a Google service account.
Create a node pool without taints, and set the Google service account as the default identity.
Grant IAM permissions to the Google service account.

Answer: A

Explanation:
Google Workload Identity is the recommended method to allow GKE workloads to securely access Google Cloud APIs using short-lived credentials without managing keys.
"Workload Identity is the recommended way to access Google Cloud services from GKE. It replaces the older method of using service account keys."
- Workload Identity Overview
"You can configure a Kubernetes service account to impersonate a Google Cloud service account by granting the roles/iam.workloadIdentityUser role and using the iam.gke.io/gcp-service-account annotation."
- Configure Workload Identity
This satisfies the customer's requirement for PoLP and avoids long-lived keys.

NEW QUESTION # 49
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