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

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Google Certified Professional - Cloud Developer Sample Questions (Q26-Q31):

NEW QUESTION # 26
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 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.
B. Trigger a Spinnaker pipeline configured as a canary test of your new code and, if it is successful, deploy the container to production.
C. 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.
D. Trigger a Spinnaker pipeline configured as an A/B test of your new code and, if it is successful, deploy the container to production.

Answer: C

Explanation:
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 # 27
You are planning to deploy your application in a Google Kubernetes Engine (GKE) cluster The application exposes an HTTP-based health check at /healthz. You want to use this health check endpoint to determine whether traffic should be routed to the pod by the load balancer.
Which code snippet should you include in your Pod configuration?

A. Option D
B. Option B
C. Option A
D. Option C

Answer: B

Explanation:
For the GKE ingress controller to use your readinessProbes as health checks, the Pods for an Ingress must exist at the time of Ingress creation. If your replicas are scaled to 0, the default health check will apply.

NEW QUESTION # 28
You have containerized a legacy application that stores its configuration on an NFS share. You need to deploy this application to Google Kubernetes Engine (GKE) and do not want the application serving traffic until after the configuration has been retrieved. What should you do?

A. Add a startup script to the GKE instance group to mount the NFS share at node startup. Copy the configuration files into the container, and start the service using an ENTRYPOINT script.
B. Use the COPY statement in the Dockerfile to load the configuration into the container image. Verify that the configuration is available, and start the service using an ENTRYPOINT script.
C. Create a PersistentVolumeClaim on the GKE cluster. Access the configuration files from the volume, and start the service using an ENTRYPOINT script.
D. Use the gsutil utility to copy files from within the Docker container at startup, and start the service using an ENTRYPOINT script.

Answer: C

NEW QUESTION # 29
You are load testing your server application. During the first 30 seconds, you observe that a previously inactive Cloud Storage bucket is now servicing 2000 write requests per second and 7500 read requests per second.
Your application is now receiving intermittent 5xx and 429 HTTP responses from the Cloud Storage JSON API as the demand escalates. You want to decrease the failed responses from the Cloud Storage API.
What should you do?

A. Limit the upload rate from your application clients so that the dormant bucket's peak request rate is reached more gradually.
B. Use the XML API instead of the JSON API for interfacing with Cloud Storage.
C. Pass the HTTP response codes back to clients that are invoking the uploads from your application.
D. Distribute the uploads across a large number of individual storage buckets.

Answer: D

Explanation:
Reference:
https://cloud.google.com/storage/docs/request-rate

NEW QUESTION # 30
You are tasked with using C++ to build and deploy a microservice for an application hosted on Google Cloud.
The code needs to be containerized and use several custom software libraries that your team has built. You do not want to maintain the underlying infrastructure of the application How should you deploy the microservice?

A. Use Cloud Functions to deploy the microservice.
B. Use Cloud Shell to containerize your microservice. and deploy it on GKE Standard.
C. Use Cloud Shell to containerize your microservice. and deploy it on a Container-Optimized OS Compute Engine instance.
D. Use Cloud Build to create the container, and deploy it on Cloud Run.

Answer: D

NEW QUESTION # 31
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