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Google Professional-Cloud-Developer Exam Syllabus Topics:

Section	Objectives
Topic 1: Build and test applications	- Manage development environments 1. Build application artifacts 2. Implement CI/CD pipelines 3. Perform application testing
Topic 2: Integrate applications with Google Cloud services	- Integrate with data and storage services 1. Implement authentication and authorization 2. Use messaging and event-driven services 3. Integrate with Google Cloud APIs
Topic 3: Deploy applications	- Deploy applications to Google Cloud 1. Deploy applications using Cloud Run 2. Deploy applications to Google Kubernetes Engine 3. Manage application rollout strategies
Topic 4: Manage application performance monitoring	- Monitor and troubleshoot applications 1. Analyze metrics and alerts 2. Optimize application performance 3. Configure logging and tracing
Topic 5: Design scalable, available, and reliable cloud-native applications	- Design highly performant applications and APIs 1. Design secure applications 2. Choose storage options for application data 3. Design resilient and scalable application architectures

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Google Certified Professional - Cloud Developer Sample Questions (Q212-Q217):

NEW QUESTION # 212
Your company's security team uses Identity and Access Management (IAM) to track which users have access to which resources. You need to create a version control system that can integrate with your security team's processes. You want your solution to support fast release cycles and frequent merges to your main branch to minimize merge conflicts. What should you do?

A. Create a GitHub repository, mirror it to a Cloud Source Repositories repository, and use feature- based development.
B. Create a Cloud Source Repositories repository, and use trunk-based development.
C. Create a Cloud Source Repositories repository, and use feature-based development.
D. Create a GitHub repository, mirror it to a Cloud Source Repositories repository, and use trunk- based development.

Answer: B

Explanation:
Where does the GitHub repository requirement come from?
The security team uses IAM for user accesses and we only need to create a version control system that can integrate with their processes. IAM can't control who is pushing stuff in GitHub and with options C or D it will end up in CSR regardless.
Fast release cycles and frequent merges to the main branch to minimize merge conflicts -> trunk- based development.

NEW QUESTION # 213
Your code is running on Cloud Functions in project A. It is supposed to write an object in a Cloud Storage bucket owned by project B. However, the write call is failing with the error "403 Forbidden".
What should you do to correct the problem?

A. Enable the Cloud Storage API in project B.
B. Grant your user account the roles/iam.serviceAccountUser role for the service-PROJECTA@gcf-admin- robot.iam.gserviceaccount.com service account.
C. Grant the service-PROJECTA@gcf-admin-robot.iam.gserviceaccount.com service account the roles/ storage.objectCreator role for the Cloud Storage bucket.
D. Grant your user account the roles/storage.objectCreator role for the Cloud Storage bucket.

Answer: B

NEW QUESTION # 214
You are planning to deploy your application in a Google Kubernetes Engine (GKE) cluster. Your application can scale horizontally, and each instance of your application needs to have a stable network identity and its own persistent disk.
Which GKE object should you use?

A. ReplicaSet
B. Deployment
C. ReplicaController
D. StatefulSet

Answer: D

Explanation:
Explanation/Reference: https://livebook.manning.com/book/kubernetes-in-action/chapter-10/46

NEW QUESTION # 215
You need to deploy resources from your laptop to Google Cloud using Terraform. Resources in your Google Cloud environment must be created using a service account. Your Cloud Identity has the roles/iam.serviceAccountTokenCreator Identity and Access Management (IAM) role and the necessary permissions to deploy the resources using Terraform. You want to set up your development environment to deploy the desired resources following Google-recommended best practices. What should you do?

A. 1. Store the service account's key file in JSON format in Hashicorp Vault.
2. Integrate Terraform with Vault to retrieve the key file dynamically, and authenticate to Vault using a short-lived access token.
B. 1. Run the following command from a command line: gcloud config set
auth/impersonate_service_account service-account-name@project.iam.gserviceacccount.com.
2. Set the GOOGLE_OAUTH_ACCESS_TOKEN environment variable to the value that is returned by the gcloud auth print-access-token command.
C. 1. Run the following command from a command line: gcloud auth application-default login.
2. In the browser window that opens, authenticate using your personal credentials.
D. 1. Download the service account's key file in JSON format, and store it locally on your laptop.
2. Set the GOOGLE_APPLICATION_CREDENTIALS environment variable to the path of your downloaded key file.

Answer: B

Explanation:
https://cloud.google.com/blog/topics/developers-practitioners/using-google-cloud-service- account-impersonation-your-terraform-code

NEW QUESTION # 216
You are deploying a containerized application to GKE. You have set up a build pipeline by using Cloud Build that builds a Java application and pushes the application container image to Artifact Registry. Your build pipeline executes multiple sequential steps that reference Docker container images with the same layers. You notice that the Cloud Build pipeline runs are taking longer than expected to complete. How should you optimize the Docker image build process?

A. Configure Cloud Build to use a private pool in your VPC for pipeline executions.
B. Specify the cached image by adding the --cache-from argument in your build config file with the image as a cache source.
C. Store container artifacts on Cloud Storage. Configure Cloud CDN on the Cloud Storage bucket to enable caching on edge locations.
D. Add the --squash parameter to the Docker build steps to combine newly built layers into a single layer.

Answer: B

Explanation:
Using the --cache-from argument enables Docker layer caching by specifying a previous image as a cache source. This allows Cloud Build to reuse layers from a previously built image, significantly reducing build time, especially when layers have not changed between builds. This approach is effective in optimizing Docker image builds and is a recommended best practice for reducing build times in Cloud Build.
- The --squash parameter is no longer supported in Docker and does not directly improve build speed.
- Using private pools in Cloud Build or Cloud CDN for container artifacts does not directly address build efficiency and caching in Docker builds.

NEW QUESTION # 217
......

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