While on-premise, an enterprise had multiple teams, each with its own analytics data store. Attempts to converge the storage for centralized, company-wide analysis failed because of speed and scaling issues. What would be the preferred destination architecture on Google Cloud?

A financial services company is running an experimental application workload that has a very large number of mathematical calculations involving floating-point numbers. The current application that is running on compute engine is not providing enough speed and throughput. What are the options to increase the processing performance?

Your team has developed a machine learning model for your customer. The test results indicate very strong predictive capability. The model is then deployed in production. Evaluation of the predictions in production show that they are off by a pronounced margin. What is the issue and how can you solve for it?

You are a program manager for a team of developers who are building an event-driven application to allow users to follow one another's activities in the app. Each time a user adds himself as a follower of another user, a write occurs in the real-time database.
The developers will develop a lightweight piece of code that can respond to database writes and generate a notification to let the appropriate users know that they have gained new followers. The code should integrate with other cloud services such as Pub/Sub, Firebase, and Cloud APIs to streamline the orchestration process. The application requires a platform that automatically manages underlying infrastructure and scales to zero when there is no activity.
Which primary compute resource should your developers select, given these requirements?

A partner of yours used to have their own private data center. Your company was already on Google Cloud and now they have also moved to Google Cloud. You are investigating whether there are ways to collaborate better or shared services. What would be one good option to consider?