support@Free-Braindumps.com
Register Login
Cisco
CompTIA
ISC
EC-Council
EXIN
Fortinet
ITIL
Juniper
Microsoft
VMware
Avaya
SAP
Google
NVIDIA
Salesforce
Amazon
Palo Alto Networks
ISC2
CrowdStrike
Anthropic
All Vendors
  1. Home
  2. Exams
  3. Google
  4. Professional Cloud Developer

Free Professional Cloud Developer Exam Braindumps
Professional Cloud Developer Questions 116–120 (page: 25)

Updated On: 10-Feb-2026
Page 25 of 52
PDF with 379 Questions

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?

  1. Use the gsutil utility to copy files from within the Docker container at startup, and start the service using an ENTRYPOINT script.
  2. Create a PersistentVolumeClaim on the GKE cluster. Access the configuration files from the volume, and start the service using an ENTRYPOINT script.
  3. 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.
  4. 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.

Answer(s): D


Reference:

https://cloud.google.com/compute/docs/instances/startup-scripts/linux



Your team is developing a new application using a PostgreSQL database and Cloud Run. You are responsible for ensuring that all traffic is kept private on Google Cloud. You want to use managed services and follow Google-recommended best practices. What should you do?


  1. 1. Enable Cloud SQL and Cloud Run in the same project.
    2. Configure a private IP address for Cloud SQL. Enable private services access.
    3. Create a Serverless VPC Access connector.
    4. Configure Cloud Run to use the connector to connect to Cloud SQL.

  2. 1. Install PostgreSQL on a Compute Engine virtual machine (VM), and enable Cloud Run in the same project.
    2. Configure a private IP address for the VM. Enable private services access.
    3. Create a Serverless VPC Access connector.
    4. Configure Cloud Run to use the connector to connect to the VM hosting PostgreSQL.

  3. 1. Use Cloud SQL and Cloud Run in different projects.
    2. Configure a private IP address for Cloud SQL. Enable private services access.
    3. Create a Serverless VPC Access connector.
    4. Set up a VPN connection between the two projects. Configure Cloud Run to use the connector to connect to Cloud SQL.

  4. 1. Install PostgreSQL on a Compute Engine VM, and enable Cloud Run in different projects.
    2. Configure a private IP address for the VM. Enable private services access.
    3. Create a Serverless VPC Access connector.
    4. Set up a VPN connection between the two projects. Configure Cloud Run to use the connector to access the VM hosting PostgreSQL

Answer(s): B



You are developing an application that will allow clients to download a file from your website for a specific period of time. How should you design the application to complete this task while following Google-recommended best practices?

  1. Configure the application to send the file to the client as an email attachment.
  2. Generate and assign a Cloud Storage-signed URL for the file. Make the URL available for the client to download.
  3. Create a temporary Cloud Storage bucket with time expiration specified, and give download permissions to the bucket. Copy the file, and send it to the client.
  4. Generate the HTTP cookies with time expiration specified. If the time is valid, copy the file from the Cloud Storage bucket, and make the file available for the client to download.

Answer(s): B



Your development team has been asked to refactor an existing monolithic application into a set of composable microservices. Which design aspects should you implement for the new application? (Choose two.)

  1. Develop the microservice code in the same programming language used by the microservice caller.
  2. Create an API contract agreement between the microservice implementation and microservice caller.
  3. Require asynchronous communications between all microservice implementations and microservice callers.
  4. Ensure that sufficient instances of the microservice are running to accommodate the performance requirements.
  5. Implement a versioning scheme to permit future changes that could be incompatible with the current interface.

Answer(s): B



You deployed a new application to Google Kubernetes Engine and are experiencing some performance degradation. Your logs are being written to Cloud Logging, and you are using a Prometheus sidecar model for capturing metrics. You need to correlate the metrics and data from the logs to troubleshoot the performance issue and send real-time alerts while minimizing costs. What should you do?

  1. Create custom metrics from the Cloud Logging logs, and use Prometheus to import the results using the Cloud Monitoring REST API.
  2. Export the Cloud Logging logs and the Prometheus metrics to Cloud Bigtable. Run a query to join the results, and analyze in Google Data Studio.
  3. Export the Cloud Logging logs and stream the Prometheus metrics to BigQuery. Run a recurring query to join the results, and send notifications using Cloud Tasks.
  4. Export the Prometheus metrics and use Cloud Monitoring to view them as external metrics. Configure Cloud Monitoring to create log-based metrics from the logs, and correlate them with the Prometheus data.

Answer(s): D


Reference:

https://cloud.google.com/blog/products/operations/troubleshoot-gke-faster-with-monitoring-data-in-your-logs



  PDF
Viewing page 25 of 52
Viewing questions 121 - 125 out of 379 questions


Post your Comments and Discuss Google Professional Cloud Developer exam prep with other Community members:

AI Tutor AI Tutor 👋 I’m here to help!