Framework Principles
Use the technologies of the modern enterprise.

6. Distributed

All components should be distributed so that it can scale and be available, all the time, to all users.

Data storage is distributed and replicated for high traffic and availability.
Queues or streams are distributed or sharded for high traffic and availability.
Stream processing should be distributed for computional scale, speed, and availability.

All components should be realtime or reactive platforms.

Data storage should respond to all read and write requests at high speeds.
Queues should respond to all read and write requests at high speeds, without bottlenecks.
Stream processing should handle queue processing and data storage/retrieval at high speeds, without bottlenecks.

All components should be extendable and not closed.

Don't reinvent the wheel if you can help it by using existing components that are extendable.

Cloud native Software, platforms, and infrastructures should be leveraged if and only if they can be extended through APIs, or modules.
Alternatively commercial open source software or platforms should be leveraged for ultimate portability and no vendor lockin.
Pure open source should be used if no commercial or cloud options are available either as a managed service or as a commercially supported offering.

All operations with data and dev should automated.

Development Operations (DevOps) should be implemented for continuous integration and continuous delivery (CICD)
Data Operations (DataOps) should be implemented for automated data pipeline management.
All infrastructure, software configuration, and software maintenance should be automated.

All systems should be monitored with metrics and logging.

All systems should have baseline Service Levels that are monitored as metrics.
All systems should emit logs that are configurable at different levels.
All systems logs should be aggregated and retained in an index for quick correlation and investigation.