You are really looking for architecture diagrams. These are extremely rare in most projects, open source or otherwise.
The reason you don’t see a lot of documentation on algorithms used or architecture is that most of the time the code is not actually novel. It’s like asking a plumber to describe the physical properties of the pipe they used on a job. They’d say “schedule 40” or “copper” and a dimension. They would not describe the manufacturing process or chemical composition of the pipe. The materials are pretty standard and only require special descriptions for when and why they deviate from those standards.
Writing fast unit tests will require some refactoring that could end up being pretty extensive.
For example, you mentioned “cloud storage” - if this is not already behind an
interfaceone ticket could be to define an interface for accessing “cloud storage” and make it so that it can be mocked for most tests and the concrete implementation can be tested directly to confirm the integration works. Try to hone down that interface so that it’s as few methods as possible, only allow the parameters you’re actually using to be exposed and used in the interface. You can add more later if it’s absolutely necessary.Do this for anything that does I/O and/or is CPU intensive.
So, to do tickets, I’d basically say, one per refactoring.
Going forward, writing “unit tests” should not be separate tickets, it should be factored into the estimates for the original stories, and nothing should go out without appropriate tests. The operational burden will decrease over time.
QA should have their own unit for how they want to test the application. Usually this is a suite per section of the app. If your app has an API, that is probably going to have a nice logical breakdown of the different areas that could each have their own ticket for adding QA-level test suites. The tests that developers write should only be additive and reduce the workload of QA. What you want to be sure of is that change sets are getting reviewed and through the entire pipeline without getting logjammed in any stage. Ideally, individual PRs are getting started and deployed in less than a week.
If you’re interested in more techniques, check out the book “Working effectively with legacy code.” It has a lot of patterns for adding tests to existing codebases.