You are developing an application that reads credit card data from a Pub/Sub subscription. You have written code and completed unit testing. You need to test the Pub/Sub integration before deploying to Google Cloud. What should you do?

You are a lead developer working on a new retail system that runs on Cloud Run and Firestore in Datastore mode. A web UI requirement is for the system to display a list of available products when users access the system and for the user to be able to browse through all products. You have implemented this requirement in the minimum viable product (MVP) phase by returning a list of all available products stored in Firestore.
A few months after go-live, you notice that Cloud Run instances are terminated with HTTP 500:
Container instances are exceeding memory limits errors during busy times. This error coincides with spikes in the number of Datastore entity reads. You need to prevent Cloud Run from crashing and decrease the number of Datastore entity reads. You want to use a solution that optimizes system performance. What should you do?

You are deploying a containerized application to GKE. You have set up a build pipeline by using Cloud Build that builds a Java application and pushes the application container image to Artifact Registry. Your build pipeline executes multiple sequential steps that reference Docker container images with the same layers. You notice that the Cloud Build pipeline runs are taking longer than expected to complete. How should you optimize the Docker image build process?

Your application team is developing an ecommerce application. Your team has developed a new functionality that has a dependency on a third-party service. This third-party service will be deployed in a few days. However, you have been unable to ensure the reliability of this service.
You need to choose a deployment strategy for the ecommerce application that will avoid disruption and can be rolled back quickly if issues are discovered. What should you do?

Your team is using App Engine to write every Cloud Pub/Sub message to both a Cloud Storage object and a BigQuery table. You want to achieve the greatest resource efficiency. Which architecture should you implement?