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Google Professional-Cloud-DevOps-Engineer Exam Syllabus Topics:

Section	Objectives
Topic 1: Implement site reliability engineering (SRE) practices	- Define and manage SLI, SLO, and SLA 1. Error budgets and monitoring strategies - Incident management and postmortems 1. Alerting and on-call practices
Topic 2: Optimize performance and continuous delivery	- System performance optimization 1. Scaling strategies and load handling - Monitoring and observability 1. Cloud Monitoring and Logging 2. Performance tuning and feedback loops
Topic 3: Implement security and compliance	- Compliance and governance 1. Audit logging and policy enforcement - Secure CI/CD pipelines 1. IAM and least privilege access 2. Secret and credential management
Topic 4: Develop and implement CI/CD pipelines	- Build and manage CI/CD pipelines using Google Cloud tools 1. Cloud Build pipeline design 2. Artifact repository management - Automate build, test, and deployment processes 1. Release management practices 2. Deployment automation strategies

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New Professional-Cloud-DevOps-Engineer Practice Questions & Real Professional-Cloud-DevOps-Engineer Question

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Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q117-Q122):

NEW QUESTION # 117
You are using Terraform to manage infrastructure as code within a Cl/CD pipeline You notice that multiple copies of the entire infrastructure stack exist in your Google Cloud project, and a new copy is created each time a change to the existing infrastructure is made You need to optimize your cloud spend by ensuring that only a single instance of your infrastructure stack exists at a time. You want to follow Google-recommended practices What should you do?

A. Confirm that the pipeline is storing and retrieving the terraform. if state file from Cloud Storage with the Terraform gcs backend
B. Create a new pipeline to delete old infrastructure stacks when they are no longer needed
C. Update the pipeline to remove any existing infrastructure before you apply the latest configuration
D. Verify that the pipeline is storing and retrieving the terrafom.tfstat* file from a source control

Answer: C

NEW QUESTION # 118
You are using Stackdriver to monitor applications hosted on Google Cloud Platform (GCP). You recently deployed a new application, but its logs are not appearing on the Stackdriver dashboard.
You need to troubleshoot the issue. What should you do?

A. Confirm that the Stackdriver agent has been installed in the hosting virtual machine.
B. Confirm that your account has the proper permissions to use the Stackdriver dashboard.
C. Confirm that port 25 has been opened in the firewall to allow messages through to Stackdriver.
D. Confirm that the application is using the required client library and the service account key has proper permissions.

Answer: A

NEW QUESTION # 119
Your team has an application built by using a Dockerfile. The build is executed from Cloud Build, and the resulting artifacts are stored in Artifact Registry. Your team is reporting that builds are slow. You need to increase build speed, while following Google-recommended practices. What should you do?

A. Cache the container layers of the build process to Cloud Storage. Add the most frequently modified files to the later stages of the build process.
B. Use the --cache-from parameter, and point to Artifact Registry. Add the most frequently modified files to the earlier stages of the build process.
C. Use the --cache-from parameter, and point to Artifact Registry. Add the most frequently modified files to the later stages of the build process.
D. Cache the container layers of the build process to Cloud Storage. Add the most frequently modified files to the earlier stages of the build process.

Answer: C

Explanation:
To speed up Docker builds, optimize layer caching. Google Cloud recommends using --cache-from with Artifact Registry, and placing frequently changed files late in the Dockerfile so earlier layers can be reused.
"Put instructions that are less likely to change (like installing packages) early in the Dockerfile, and more frequently changing lines (like copying app code) near the end."
- Dockerfile Best Practices
"Use the --cache-from argument to pull layers from previously built images in Artifact Registry."
- Cloud Build Docker Caching
This dramatically reduces build time by avoiding redundant rebuilds of static layers.

NEW QUESTION # 120
You are building the Cl/CD pipeline for an application deployed to Google Kubernetes Engine (GKE) The application is deployed by using a Kubernetes Deployment, Service, and Ingress The application team asked you to deploy the application by using the blue'green deployment methodology You need to implement the rollback actions What should you do?

A. Delete the new container image, and delete the running Pods
B. Scale the new Kubernetes Deployment to zero
C. Run the kubectl rollout undo command
D. Update the Kubernetes Service to point to the previous Kubernetes Deployment

Answer: D

Explanation:
Explanation
The best option for implementing the rollback actions is to update the Kubernetes Service to point to the previous Kubernetes Deployment. A Kubernetes Service is a resource that defines how to access a set of Pods.
A Kubernetes Deployment is a resource that manages the creation and update of Pods. By using the blue/green deployment methodology, you can create two Deployments, one for the current version (blue) and one for the new version (green), and use a Service to switch traffic between them. If you need to rollback, you can update the Service to point to the previous Deployment (blue) and stop sending traffic to the new Deployment (green).

NEW QUESTION # 121
You are creating a CI/CD pipeline to perform Terraform deployments of Google Cloud resources Your CI/CD tooling is running in Google Kubernetes Engine (GKE) and uses an ephemeral Pod for each pipeline run You must ensure that the pipelines that run in the Pods have the appropriate Identity and Access Management (1AM) permissions to perform the Terraform deployments You want to follow Google-recommended practices for identity management What should you do?
Choose 2 answers

A. Create a new JSON service account key for the Google service account store the key in the secret management store for the CI/CD tool and configure Terraform to use this key for authentication
B. Create a new JSON service account key for the Google service account store the key as a Kubernetes secret, inject the key into the Pods, and set the boogle_application_credentials environment variable
C. Assign the appropriate 1AM permissions to the Google service account associated with the Compute Engine VM instances that run the Pods
D. Create a new Google service account, and assign the appropriate 1AM permissions
E. Create a new Kubernetes service account, and assign the service account to the Pods Use Workload Identity to authenticate as the Google service account

Answer: D,E

Explanation:
The best options for ensuring that the pipelines that run in the Pods have the appropriate IAM permissions to perform the Terraform deployments are to create a new Kubernetes service account and assign the service account to the Pods, and to use Workload Identity to authenticate as the Google service account. A Kubernetes service account is an identity that represents an application or a process running in a Pod. A Google service account is an identity that represents a Google Cloud resource or service. Workload Identity is a feature that allows you to bind Kubernetes service accounts to Google service accounts. By using Workload Identity, you can avoid creating and managing JSON service account keys, which are less secure and require more maintenance. You can also assign the appropriate IAM permissions to the Google service account that corresponds to the Kubernetes service account.

NEW QUESTION # 122
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