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Google Professional-Cloud-Developer Exam Syllabus Topics:

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

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Google Certified Professional - Cloud Developer Sample Questions (Q95-Q100):

NEW QUESTION # 95
You plan to make a simple HTML application available on the internet. This site keeps information about FAQs for your application. The application is static and contains images, HTML, CSS, and Javascript. You want to make this application available on the internet with as few steps as possible.
What should you do?

A. Containerize your application first. Deploy this container to Google Kubernetes Engine (GKE) and assign an external IP address to the GKE pod hosting the application.
B. Upload your application to an App Engine environment.
C. Create a Compute Engine instance with Apache web server installed. Configure Apache web server to host the application.
D. Upload your application to Cloud Storage.

Answer: D

Explanation:
Explanation/Reference: https://cloud.google.com/storage/docs/hosting-static-website

NEW QUESTION # 96
Your application is deployed in a Google Kubernetes Engine (GKE) cluster. When a new version of your application is released, your CI/CD tool updates the spec.template.spec.containers[0].image value to reference the Docker image of your new application version. When the Deployment object applies the change, you want to deploy at least 1 replica of the new version and maintain the previous replicas until the new replica is healthy.
Which change should you make to the GKE Deployment object shown below?

A. Set the Deployment strategy to Recreate with maxSurge set to 1, maxUnavailable set to 0.
B. Set the Deployment strategy to RollingUpdate with maxSurge set to 1, maxUnavailable set to 0.
C. Set the Deployment strategy to Recreate with maxSurge set to 0, maxUnavailable set to 1.
D. Set the Deployment strategy to RollingUpdate with maxSurge set to 0, maxUnavailable set to 1.

Answer: A

NEW QUESTION # 97
You have an application running on Cloud Run that receives a large volume of traffic. You need to deploy a new version of the application. You want your deployment process to minimize the risk of downtime while following Google-recommended practices. What should you do?

A. Use Cloud Run emulator to test changes locally before deploying the new version of the application to the production Cloud Run service.
B. Use Cloud Build to create a pipeline, and configure a test stage before the deployment stage.
When all tests pass, deploy the application to Cloud Run, and direct 100% of users to this new version of the application. Roll back if any issues are detected.
C. Use traffic splitting to have a small percentage of users test out new features on the new revision of the application on the production Cloud Run service. If performance meets expectations, gradually increase the percentage of users until it reaches 100%.
D. Use Cloud Load Balancing to route a percentage of production traffic to a separate Cloud Run service running the new version of the application. If performance meets expectations, gradually increase the percentage of users until the new Cloud Run service reaches 100%.

Answer: C

Explanation:
Traffic splitting in Cloud Run allows you to route a specific percentage of users to a new revision of your service, making it possible to test the new version with real traffic while minimizing the risk of downtime. This gradual rollout approach helps you monitor performance and user experience, and if issues arise, you can easily adjust the traffic split or revert to the previous version. This aligns with Google-recommended practices for safe, low-risk deployments in Cloud Run.
Options like testing locally with a Cloud Run emulator or deploying after passing tests in a pipeline are useful for initial testing but do not provide the gradual, controlled release approach that traffic splitting offers. Using Cloud Load Balancing is not necessary here, as Cloud Run has built-in traffic splitting capabilities designed for this purpose.

NEW QUESTION # 98
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. Build a new application with the appropriate microservices separate from the monolith and replace it when
C. Refactor the monolithic application with appropriate microservices in a single effort and deploy it.
D. Replace the application's features with appropriate microservices in phases.

Answer: C

Explanation:
it is complete.

NEW QUESTION # 99
You are building a CI/CD pipeline that consists of a version control system, Cloud Build, and Container Registry. Each time a new tag is pushed to the repository, a Cloud Build job is triggered, which runs unit tests on the new code builds a new Docker container image, and pushes it into Container Registry. The last step of your pipeline should deploy the new container to your production Google Kubernetes Engine (GKE) cluster.
You need to select a tool and deployment strategy that meets the following requirements:
* Zero downtime is incurred
* Testing is fully automated
* Allows for testing before being rolled out to users
* Can quickly rollback if needed
What should you do?

A. Trigger a Spinnaker pipeline configured as a canary test of your new code and, if it is successful, deploy the container to production.
B. Trigger another Cloud Build job that uses the Kubernetes CLI tools to deploy your new container to your GKE cluster, where you can perform a canary test.
C. Trigger a Spinnaker pipeline configured as an A/B test of your new code and, if it is successful, deploy the container to production.
D. Trigger another Cloud Build job that uses the Kubernetes CLI tools to deploy your new container to your GKE cluster, where you can perform a shadow test.

Answer: D

Explanation:
https://cloud.google.com/architecture/implementing-deployment-and-testing-strategies-on-gke#perform_a_shado With a shadow test, you test the new version of your application by mirroring user traffic from the current application version without impacting the user requests.

NEW QUESTION # 100
......

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