最佳Professional-Cloud-Developer資訊和資格考試領先提供商和免費下載的Professional-Cloud-Developer：Google Certified Professional - Cloud Developer

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Google Professional-Cloud-Developer Exam Syllabus Topics:

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

>> Professional-Cloud-Developer資訊 <<

Professional-Cloud-Developer考試指南 & Professional-Cloud-Developer測試題庫

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最新的 Cloud Developer Professional-Cloud-Developer 免費考試真題 (Q305-Q310):

問題 #305
You are designing a deployment technique for your new applications on Google Cloud. As part of your deployment planning, you want to use live traffic to gather performance metrics for both new and existing applications. You need to test against the full production load prior to launch. What should you do?

A. Use blue/green deployment
B. Use canary deployment
C. Use A/B testing with traffic mirroring during deployment
D. Use rolling updates deployment

答案：B

問題 #306
You are creating and running containers across different projects in Google Cloud. The application you are developing needs to access Google Cloud services from within Google Kubernetes Engine (GKE). What should you do?

A. Store the Google service account credentials as a Kubernetes Secret.
B. Use a Google service account to run the Pod with Workload Identity.
C. Assign a Google service account to the GKE nodes.
D. Use a Google service account with GKE role-based access control (RBAC).

答案：B

解題說明：
https://cloud.google.com/kubernetes-engine/docs/concepts/workload-identity

問題 #307
You want to re-architect a monolithic application so that it follows a microservices model. You want to accomplish this efficiently while minimizing the impact of this change to the business.
Which approach should you take?

A. Deploy the application to Compute Engine and turn on autoscaling.
B. Replace the application's features with appropriate microservices in phases.
C. Build a new application with the appropriate microservices separate from the monolith and replace it when
D. Refactor the monolithic application with appropriate microservices in a single effort and deploy it.

答案：D

解題說明：
it is complete.

問題 #308
Your company wants to expand their users outside the United States for their popular application.
The company wants to ensure 99.999% availability of the database for their application and also wants to minimize the read latency for their users across the globe.
Which two actions should they take? (Choose two.)

A. Create a cluster with at least 1 Spanner node.
B. Create a Cloud Dataflow pipeline to replicate data across different databases.
C. Create a multi-regional Cloud Spanner instance with "nam3" configuration.
D. Create a minimum of two Cloud Spanner instances in separate regions with at least one node.
E. Create a cluster with at least 3 Spanner nodes.
F. Create a multi-regional Cloud Spanner instance with "nam-asia-eur1" configuration.

答案：E,F

解題說明：
https://cloud.google.com/spanner/docs/instances
https://cloud.google.com/spanner/docs/latency

問題 #309
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 in parallel, then load into BigQuery.
B. Perform the inserts in parallel by creating multiple threads.
C. Write each row to a Cloud Storage object, then load into BigQuery.
D. Include multiple rows with each request.

答案：B

問題 #310
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