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Google Professional-Cloud-Developer Exam Syllabus Topics:

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

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Google Certified Professional - Cloud Developer Sample Questions (Q308-Q313):

NEW QUESTION # 308
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 shadow test.
B. Trigger a Spinnaker pipeline configured as an A/B test of your new code and, if it is successful, deploy the container to production.
C. Trigger a Spinnaker pipeline configured as a canary 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 canary test.

Answer: A

Explanation:
https://cloud.google.com/architecture/implementing-deployment-and-testing-strategies-on-gke#perform_a_shadow_test 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 # 309
You are reviewing and updating your Cloud Build steps to adhere to best practices. Currently, your build steps include:
1. Pull the source code from a source repository.
2. Build a container image
3. Upload the built image to Artifact Registry.
You need to add a step to perform a vulnerability scan of the built container image, and you want the results of the scan to be available to your deployment pipeline running in Google Cloud. You want to minimize changes that could disrupt other teams' processes. What should you do?

A. Add Artifact Registry to your Aqua Security instance, and scan the built container images for vulnerabilities.
B. Enable Binary Authorization, and configure it to attest that no vulnerabilities exist in a container image.
C. Enable the Container Scanning API in Artifact Registry, and scan the built container images for vulnerabilities.
D. Upload the built container images to your Docker Hub instance, and scan them for vulnerabilities.

Answer: C

Explanation:
https://cloud.google.com/container-analysis/docs/automated-scanning-
howto#view_the_image_vulnerabilities

NEW QUESTION # 310
You are a developer at a large organization. You are deploying a web application to Google Kubernetes Engine (GKE). The DevOps team has built a CI/CD pipeline that uses Cloud Deploy to deploy the application to Dev, Test, and Prod clusters in GKE. After Cloud Deploy successfully deploys the application to the Dev cluster, you want to automatically promote it to the Test cluster. How should you configure this process following Google-recommended best practices?

A. 1. Create a Cloud Build pipeline that uses the gke-deploy builder.
2. Create a Cloud Build trigger that listens for SUCCEEDED Pub/Sub messages from the cloud- builds topic.
3. Configure this pipeline to run a deployment step to the Test cluster.
B. 1. Create a Cloud Function that calls the Google Cloud Deploy API to promote the application to the Test cluster.
2. Configure this function to be triggered by SUCCEEDED Pub/Sub messages from the clouddeploy-operations topic.
C. 1. Create a Cloud Function that calls the Google Cloud Deploy API to promote the application to the Test cluster.
2. Configure this function to be triggered by SUCCEEDED Pub/Sub messages from the cloud- builds topic.
D. 1. Create a Cloud Build trigger that listens for SUCCEEDED Pub/Sub messages from the clouddeploy-operations topic.
2. Configure Cloud Build to include a step that promotes the application to the Test cluster.

Answer: B

Explanation:
https://cloud.google.com/functions/docs/calling/pubsub

NEW QUESTION # 311
You are planning to migrate a MySQL database to the managed Cloud SQL database for Google Cloud. You have Compute Engine virtual machine instances that will connect with this Cloud SQL instance. You do not want to whitelist IPs for the Compute Engine instances to be able to access Cloud SQL.
What should you do?

A. Enable private IP for the Cloud SQL instance.
B. Whitelist a project to access Cloud SQL, and add Compute Engine instances in the whitelisted project.
C. Create a role in Cloud SQL that allows access to the database from external instances, and assign the Compute Engine instances to that role.
D. Create a CloudSQL instance on one project. Create Compute engine instances in a different project.
Create a VPN between these two projects to allow internal access to CloudSQL.

Answer: C

Explanation:
Reference:
https://cloud.google.com/sql/docs/mysql/connect-external-app

NEW QUESTION # 312
You work for an environmental agency in a large city. You are developing a new monitoring platform that will capture air quality readings from thousands of locations in the city. You want the air quality reading devices to send and receive their data payload to the newly created RESTful backend systems every minute by using a curl command. The backend systems are running in a single cloud region and are using Premium Tier networking. You need to connect the devices to the backend while minimizing the daily average latency, measured by using Time to First Byte (TTFB). How should you build this service?

A. 1. Run the air quality devices' backends on Compute Engine VMs.
2. Create a round robin routing policy on Cloud DNS for these Compute Engine VMs.
3. Configure the air quality devices to connect by using this DNS.
B. 1. Run the air quality devices' backends in a managed instance group.
2. Create an external passthrough Network Load Balancer to connect to the managed instance group.
3. Configure a connection between the air quality devices and the Network Load Balancer.
C. 1 Run the air quality devices' backends in a managed instance group.
2. Create an external Application Load Balancer, and connect it to the managed instance group.
3. Configure a connection between the air quality devices and the Application Load Balancer.
D. 1. Run the air quality devices' backends on Compute Engine VMs.
2. Create a weighted round robin routing policy on Cloud DNS.
3. Configure the air quality devices to connect by using this DNS.

Answer: C

Explanation:
https://web.dev/articles/optimize-ttfb

NEW QUESTION # 313
......

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