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Google Professional-Cloud-Developer Exam Syllabus Topics:

Section	Objectives
Topic 1: Designing cloud-native applications	- Scalability and resiliency patterns - Microservices design principles - Application architecture design
Topic 2: Ensuring application performance and reliability	- Monitoring and logging (Cloud Monitoring, Cloud Logging) - Fault tolerance and incident response - Performance optimization
Topic 3: Deploying applications	- Release management strategies - Containerization and deployment (Cloud Run, GKE) - CI/CD pipelines
Topic 4: Integrating Google Cloud services	- API integration and service-to-service communication - Using managed services (Pub/Sub, Firestore, Cloud SQL)
Topic 5: Building and testing applications	- Unit and integration testing strategies - Application development on Google Cloud - Debugging and troubleshooting applications

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Google Certified Professional - Cloud Developer Sample Questions (Q15-Q20):

NEW QUESTION # 15
Your application in production has recently been experiencing reliability issues, and you are unsure how the application will behave in the event of an unexpected failure. You want to assess the application's resilience. What should you do?

A. Write end-to-end tests to determine how different microservices interact. Validate that all tests pass.
B. Perform load testing of the application, and use JMeter for the critical endpoints of the application.Ensure that the application performs as expected under a heavy load.
C. Test individual units of code for a critical portion of the application's code. Ensure that unit tests are part of the Cloud Build pipeline.
D. Perform chaos engineering by intentionally introducing failures into the system. Observe how the application behaves, and ensure that it is able to recover from a failure.

Answer: D

Explanation:
Chaos engineering is the practice of intentionally introducing failures into a system to test its resilience and observe how it behaves under unexpected conditions. This approach allows you to uncover potential weaknesses and ensure that the application can recover from failures. By testing with chaos engineering, you gain insights into how the system behaves in production-like failure scenarios, which is essential for assessing and improving resilience.
Other options, like end-to-end testing, unit testing, and load testing, are useful for verifying functionality and performance but do not directly assess how the application behaves during unexpected failures.

NEW QUESTION # 16
You are designing an application that consists of several microservices. Each microservice has its own RESTful API and will be deployed as a separate Kubernetes Service. You want to ensure that the consumers of these APIs aren't impacted when there is a change to your API, and also ensure that third-party systems aren't interrupted when new versions of the API are released. How should you configure the connection to the application following Google-recommended best practices?

A. Use an Ingress that uses the API's URL to route requests to the appropriate backend.
B. Use multiple clusters, and use DNS entries to route requests to separate versioned backends.
C. Leverage a Service Discovery system, and connect to the backend specified by the request.
D. Combine multiple versions in the same service, and then specify the API version in the POST request.

Answer: A

NEW QUESTION # 17
Your company's development teams want to use Cloud Build in their projects to build and push Docker images to Container Registry. The operations team requires all Docker images to be published to a centralized, securely managed Docker registry that the operations team manages.
What should you do?

A. Use Container Registry to create a registry in each development team's project. Configure the Cloud Build build to push the Docker image to the project's registry. Grant the operations team access to each development team's registry.
B. Create a separate project for the operations team that has Container Registry configured. Create a Service Account for each development team and assign the appropriate permissions to allow it access to the operations team's registry. Store the service account key file in the source code repository and use it to authenticate against the operations team's registry.
C. Create a separate project for the operations team that has Container Registry configured. Assign appropriate permissions to the Cloud Build service account in each developer team's project to allow access to the operation team's registry.
D. Create a separate project for the operations team that has the open source Docker Registry deployed on a Compute Engine virtual machine instance. Create a username and password for each development team.
Store the username and password in the source code repository and use it to authenticate against the operations team's Docker registry.

Answer: A

Explanation:
Reference: https://cloud.google.com/container-registry/

NEW QUESTION # 18
Your application requires service accounts to be authenticated to GCP products via credentials stored on its host Compute Engine virtual machine instances. You want to distribute these credentials to the host instances as securely as possible.
What should you do?

A. Generate a P12 file from the GCP Console after the instance is deployed, and copy the credentials to the host instance before starting the application.
B. Use the instance's service account Application Default Credentials to authenticate to the required resources.
C. Commit the credential JSON file into your application's source repository, and have your CI/CD process package it with the software that is deployed to the instance.
D. Use HTTP signed URLs to securely provide access to the required resources.

Answer: B

Explanation:
Explanation/Reference: https://cloud.google.com/compute/docs/api/how-tos/authorization

NEW QUESTION # 19
Your teammate has asked you to review the code below. Its purpose is to efficiently add a large number of small rows to a BigQuery table.

Which improvement should you suggest your teammate make?

A. Write each row to a Cloud Storage object, then load into BigQuery.
B. Include multiple rows with each request.
C. Perform the inserts in parallel by creating multiple threads.
D. Write each row to a Cloud Storage object in parallel, then load into BigQuery.

Answer: C

NEW QUESTION # 20
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