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Google Professional-Cloud-Developer Exam Syllabus Topics:

Section	Objectives
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
Integrate applications with Google Cloud services	- Integrate with data and storage services 1. Integrate with Google Cloud APIs 2. Use messaging and event-driven services 3. Implement authentication and authorization
Deploy applications	- Deploy applications to Google Cloud 1. Deploy applications to Google Kubernetes Engine 2. Deploy applications using Cloud Run 3. Manage application rollout strategies
Build and test applications	- Manage development environments 1. Build application artifacts 2. Perform application testing 3. Implement CI/CD pipelines
Manage application performance monitoring	- Monitor and troubleshoot applications 1. Configure logging and tracing 2. Analyze metrics and alerts 3. Optimize application performance

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Google Certified Professional - Cloud Developer Sample Questions (Q317-Q322):

NEW QUESTION # 317
You are developing an application that reads credit card data from a Pub/Sub subscription. You have written code and completed unit testing. You need to test the Pub/Sub integration before deploying to Google Cloud.
What should you do?

A. Create a service to publish messages to your application. Collect the messages from Pub/Sub in production, and replay them through the publishing service.
B. Create a service to publish messages, and deploy the Pub/Sub emulator. Generate random content in the publishing service, and publish to the emulator.
C. Create a service to publish messages, and deploy the Pub/Sub emulator. Collect the messages from Pub/Sub in production, and publish them to the emulator.
D. Create a service to publish messages, and deploy the Pub/Sub emulator. Publish a standard set of testing messages from the publishing service to the emulator.

Answer: D

NEW QUESTION # 318
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. Perform the inserts in parallel by creating multiple threads.
B. Write each row to a Cloud Storage object in parallel, then load into BigQuery.
C. Write each row to a Cloud Storage object, then load into BigQuery.
D. Include multiple rows with each request.

Answer: A

NEW QUESTION # 319
You have recently instrumented a new application with OpenTelemetry, and you want to check the latency of your application requests in Trace. You want to ensure that a specific request is always traced. What should you do?

A. Wait 10 minutes, then verify that Trace captures those types of requests automatically.
B. Use the Trace API to apply custom attributes to the trace.
C. Write a custom script that sends this type of request repeatedly from your dev project.
D. Add the X-Cloud-Trace-Context header to the request with the appropriate parameters.

Answer: D

Explanation:
https://cloud.google.com/trace/docs/setup#force-trace
Cloud Trace doesn't sample every request. To force a specific request to be traced, add an X-Cloud-Trace-Context header to the request.

NEW QUESTION # 320
Your team develops services that run on Google Kubernetes Engine. Your team's code is stored in Cloud Source Repositories. You need to quickly identify bugs in the code before it is deployed to production. You want to invest in automation to improve developer feedback and make the process as efficient as possible. What should you do?

A. Use Cloud Build to automate building container images from code based on Git tags.
B. Use Spinnaker to automate deploying container images to the production environment.
C. Use Spinnaker to automate building container images from code based on Git tags.
D. Use Cloud Build to automate building container images from code based on forked versions.

Answer: C

NEW QUESTION # 321
You have a container deployed on Google Kubernetes Engine. The container can sometimes be slow to launch, so you have implemented a liveness probe. You notice that the liveness probe occasionally fails on launch. What should you do?

A. Increase the CPU limit for the container.
B. Add a readiness probe.
C. Add a startup probe.
D. Increase the initial delay for the liveness probe.

Answer: D

Explanation:
Explanation
https://kubernetes.io/docs/tasks/configure-pod-container/configure-liveness-readiness-startup-probes/#configure-

NEW QUESTION # 322
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