How would you design a solution for running a large-scale, multi-region, and secure IoT platform on Google Cloud, considering the requirement for real-time data processing, low latency, and the ability to handle millions of connected devices and terabytes of data?

Files must be uploaded from your on-premises environment to Cloud Storage. You want the files encrypted on Cloud Storage with encryption keys supplied by the customer. What are your options?

You want to optimize the performance of an accurate, real-time, weather-charting application. The data comes from 50,000 sensors sending 10 readings a second, in the format of a timestamp and sensor reading.

Where should you store the data?

A development manager is building a new application. He asks you to review his requirements and identify what cloud technologies he can use to meet them. The application must:

1. Be based on open-source technology for cloud portability

2. Dynamically scale compute capacity based on demand

3. Support continuous software delivery

4. Run multiple segregated copies of the same application stack

5. Deploy application bundles using dynamic templates

6. Route network traffic to specific services based on URL

Which combination of technologies will meet all of his requirements?

The company runs its application over multiple regions; they have static images and relational database. The database has over 10 TB of data, so they use a single repository storage for all regions and for each type of data. Which two products should you recommend?