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| Vendor: | |
|---|---|
| Exam Code: | Professional-Cloud-Developer |
| Exam Name: | Professional Cloud Developer |
| Exam Questions: | 265 |
| Last Updated: | May 25, 2026 |
| Related Certifications: | Google Cloud Certified |
| Exam Tags: |
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You recently deployed your application in Google Kubernetes Engine, and now need to release a new version of your application. You need the ability to instantly roll back to the previous version in case there are issues with the new version. Which deployment model should you use?
Your website is deployed on Compute Engine. Your marketing team wants to test conversion rates between 3
different website designs.
Which approach should you use?
Your application is composed of a set of loosely coupled services orchestrated by code executed on Compute Engine. You want your application to easily bring up new Compute Engine instances that find and use a specific version of a service. How should this be configured?
Your team has created an application that is hosted on a Google Kubernetes Engine (GKE) cluster You need to connect the application to a legacy REST service that is deployed in two GKE clusters in two different regions. You want to connect your application to the legacy service in a way that is resilient and requires the fewest number of steps You also want to be able to run probe-based health checks on the legacy service on a separate port How should you set up the connection?
A) Using Traffic Director with a sidecar proxy can provide resilience for your application by allowing for failover to the secondary region in the event of an outage. The sidecar proxy can route traffic to the legacy service in either of the two GKE clusters, ensuring high availability. C. Configuring the legacy service's firewall to allow health checks originating from the proxy allows the proxy to periodically check the health of the legacy service and ensure that it is functioning properly. This helps to ensure that traffic is only routed to healthy instances of the legacy service, further improving the resilience of the setup.
You have an HTTP Cloud Function that is called via POST. Each submission's request body has a flat, unnested JSON structure containing numeric and text dat
a. After the Cloud Function completes, the collected data should be immediately available for ongoing and complex analytics by many users in parallel. How should you persist the submissions?
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