Google Professional-Cloud-Developer Practice Exam Dumps 2025

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Free Professional-Cloud-Developer Exam Dumps

Google Certified Professional - Cloud Developer Questions and Answers

Question 1

You have an application running in a production Google Kubernetes Engine (GKE) cluster. You use Cloud Deploy to automatically deploy your application to your production GKE cluster. As part of your development process: you are planning to make frequent changes to the applications source code and need to select the tools to test the changes before pushing them to your remote source code repository. Your toolset must meet the following requirements:

• Test frequent local changes automatically.

• Local deployment emulates production deployment.

Which tools should you use to test building and running a container on your laptop using minimal resources'?

Options:

Terraform and kubeadm

Docker Compose and dockerd

Minikube and Skaffold

kaniko and Tekton

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Question 2

Your team is developing an ecommerce platform for your company. Users will log in to the website and add items to their shopping cart. Users will be automatically logged out after 30 minutes of inactivity. When users log back in, their shopping cart should be saved. How should you store users’ session and shopping cart information while following Google-recommended best practices?

Options:

Store the session information in Pub/Sub, and store the shopping cart information in Cloud SQL.

Store the shopping cart information in a file on Cloud Storage where the filename is the SESSION ID.

Store the session and shopping cart information in a MySQL database running on multiple Compute Engine instances.

Store the session information in Memorystore for Redis or Memorystore for Memcached, and store the shopping cart information in Firestore.

Question 3

For this question, refer to the HipLocal case study.

How should HipLocal redesign their architecture to ensure that the application scales to support a large increase in users?

Options:

Use Google Kubernetes Engine (GKE) to run the application as a microservice. Run the MySQL database on a dedicated GKE node.

Use multiple Compute Engine instances to run MySQL to store state information. Use a Google Cloud-managed load balancer to distribute the load between instances. Use managed instance groups for scaling.

Use Memorystore to store session information and CloudSQL to store state information. Use a Google Cloud-managed load balancer to distribute the load between instances. Use managed instance groups for scaling.

Use a Cloud Storage bucket to serve the application as a static website, and use another Cloud Storage bucket to store user state information.

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Google Certified Professional - Cloud Developer Questions and Answers

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