Free Google Professional-Cloud-Developer Exam Questions

Become Google Certified with updated Professional-Cloud-Developer exam questions and correct answers

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Total 623 Questions | Updated On: Feb 21, 2026

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Question 1

You are developing an application that consists of several microservices running in a Google Kubernetes Engine cluster. One microservice needs to connect to a third-party database running on-premises. You need to store credentials to the database and ensure that these credentials can be rotated while following security best practices. What should you do?

A : ore the credentials in a sidecar container proxy. and use it to connect to the third-party database.

B : nfigure a service mesh to allow or restrict traffic from the Pods in your microservice to the database.

C : ore the credentials in an encrypted volume mount, and associate a Persistent Volume Claim with the client Pod.

D : Store the credentials as a Kubemetes Secret, and use the Cloud Key Management Service plugin to handle encryption and decryption

Answer: A

Question 2

A stateless web application for a marquee is being developed for Google Cloud. It is expected that the incoming user traffic will be unpredictable, with some days having no traffic while other days will have large spikes. The application should be able to automatically scale up and down, while minimizing the cost associated with running the application.

What actions do you need to take?

A : Use Python and Firestore to build the application, then deploy it to a managed instance group with autoscaling on Compute Engine.

B : Create the application with C# and Firestore, and deploy it to App Engine's flexible environment.

C : Build the application using Python and Firestore, then deploy it to Cloud Run.

D : Develop the application with Python and CloudSQL, and deploy it to App Engine's standard environment.

Answer: C

Question 3

Your team is responsible for maintaining an application that aggregates news articles from many different sources. Your monitoring dashboard contains publicly accessible real-time reports and runs on a Compute Engine instance as a web application. External stakeholders and analysts need to access these reports via a secure channel without authentication. How should you configure this secure channel?

A : a public IP address to the instance. Use the service account key of the instance to encrypt the traffic

B : Cloud Scheduler to trigger Cloud Build every hour to create an export from the reports. Store the reports in a public Cloud Storage bucket.

C : an HTTP(S) load balancer in front of the monitoring dashboard. Configure Identity-Aware Proxy to secure the communication channel.

D : Add an HTTP(S) load balancer in front of the monitoring dashboard. Set up a Google-managed SSL certificate on the load balancer for traffic encryption.

Answer: B

Question 4

What is the purpose of selecting the API Key option in the Policies section when creating a proxy in Apigee?

A : To configure the virtual hosts for the proxy

B : To create a proxy with a self-explanatory name

C : To protect the service through the apiKey authentication method

D : To access the Proxy API section

Answer: C

Question 5

Your company is planning to migrate their on-premises Hadoop environment to the cloud. Increasing storage cost and maintenance of data stored in HDFS is a major concern for your company. You also want to make minimal changes to existing data analytics jobs and existing architecture. How should you proceed with the migration?

A : grate your data stored in Hadoop to BigQuery. Change your jobs to source their information from BigQuery instead of the on-premises Hadoop environment.

B : eate Compute Engine instances with HDD instead of SSD to save costs. Then perform a full migration of your existing environment into the new one in Compute Engine instances.

C : eate a Cloud Dataproc cluster on Google Cloud Platform, and then migrate your Hadoop environment to the new Cloud Dataproc cluster. Move your HDFS data into larger HDD disks to save on storage costs.

D : eate a Cloud Dataproc cluster on Google Cloud Platform, and then migrate your Hadoop code objects to the new cluster. Move your data to Cloud Storage and leverage the Cloud Dataproc connector to run jobs on that data.

Answer: D

Page: 1 / 125

Total 623 Questions | Updated On: Feb 21, 2026

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