Free Google Professional-Cloud-Developer Exam Questions

The task at hand is to create a microservice-based application on Google Kubernetes Engine (GKE). The application requires access to various Google Cloud APIs. Two of these services must be able to access these APIs.

What is the recommended approach for implementing authentication of these services in the cluster according to Google's best practices?

The new version of your containerized application has been tested and is ready to deploy to production on Google Kubemetes Engine. You were not able to fully load-test the new version in pre-production environments. and you need to make sure that it does not have performance problems once deployed Your deployment must be automated. What should you do? 

An application is being managed on a Compute Engine instance, alongside multiple backend services that are run on stand-alone Docker containers in Compute Engine instances. These Compute Engine instances supporting the backend services are scaled by managed instance groups across several regions. In order to ensure a loosely coupled calling application, it is necessary to be able to invoke individual service implementations which are selected based on the value of an HTTP header located within the request.

What is the appropriate Google Cloud feature to activate the backend services?

The analytics system is currently facing a permission error while executing queries against a BigQuery dataset. The SQL query is executed in batch by passing the contents of a SQL file to the BigQuery CLI, which in turn redirects the output to another process. To resolve this issue, you need to identify the root cause of the permission error and take necessary steps to fix it.

What actions are recommended in this situation?

What options does the Query builder section provide for filtering logs?