For example, because of the forced conventions, it's trivial for the Polylith Tool to perform static code analysis on a Polylith codebase. This means that the tool can identify the subset of tests to run, based on the components that have changed since the last run. Which leads to a fast-feedback loop, and encourages both good testing practices and fine-grained component modularity.
Polylith gives you a system-level architectural building block; the component, which encourages a modular design and separation of concerns. However, you're right that it's still possible to create spaghetti code with Polylith. All it would take is poorly designed components, with bad names, multiple reasons to change, and exposing their state everywhere. However, I'd argue that when you give someone a well designed tool (like Polylith), then they're more likely to craft a well designed product with it.
To understand how builds and deployments work with Polylith, I'd recommend reading the "Workflow" section in the Polylith Tool's documentation: https://polylith.gitbook.io/poly/workflow/shell (especially "Build", "Git", "Continuous Integration", and "Testing").
I'm sort of reminded of adopting a formatting and linting stack across a codebase - so long as it mostly makes mostly good choices, the shared conventions are usually a net win overall just because it (a) makes code more accessible across the team (b) gives you a solid default way to resolve a lot of choices.
The whole "can -reliably- figure out which tests need to be re-run" part specifically sounds like it would be a very nice thing to have.
I suspect your biggest challenge in terms of adoption will be the requirement for development group wide buy in to get the full benefits, but that's a problem that's kind of inherent to the goals you're trying to achieve here and so I shall simply wish you good luck with that part.
Including my favourite; a complete untangling of your development and production environments. With Polylith you always develop your system as a monolith (because that's the most effective way to build software), but you're able to deploy it as multiple services (because that's sometimes the most effective way to run software). It turns out that separating deployment complexity from development complexity is a game-changer, and something that I haven't come across from other architectures.
It's true that you don't reap all the benefits of Polylith until your entire codebase uses the same structure, which feels a bit like "all or nothing". However, many of the benefits are unlocked "as you go", so even converting one or two existing microservices to Polylith will feel like a nicer codebase to work with.
> so I shall simply wish you good luck with that part
Thanks!
Having said that, I'm sure it's possible to run the prod version(s) locally and test them, but then don't you lose the benefits of separating deployment complexity from development complexity since you're now running the prod version locally anyways?
Hypothetically, say I'm big corp A with my thousands of developers and hundred of micro services that are just polylith projects. Further, let's say, I have N services that depend on component B. Now, if one team needs to make a breaking change on component B (say you need to change the interface), how would you suggest handling it based on polylith architecture? Would you version each component so that services can pin the component version? Or would you create a new component? Something else? Intuitively, versioning sounds like a mess of thousands of repos. On the other hand, creating a new component would create precedent that might be used to justify an explosion of components that may make your workspace a mess of almost identical components. While refactoring sounds like the way forward here, if you've dug yourself a hole with bad design choices then polylith seems like it would give you more rope to hang yourself with. Otherwise you have to coordinate with all the teams needed to figure out how to modify the N services depending on component B. With typical microservices, my understanding is that this wouldn't happen so long as the service's API remained constant.
You are right that you need to handle breaking changes in some way. Refactor all the code that uses the changed component is probably the best way to go in most cases because it keeps the code as simple as possible. Second best (or best in some situations) is to introduce a new function in the existing component (if it's not a huge change, then a new component can make sense). This can be done in different ways, e.g. by adding one more signature to the function or by putting the new version in a sub namespace, e.g. 'v2' in the interface namespace.
You will face similar coordination problems with microservices too. I worked in a project where we had around 100 microservices. To share code between services we created libraries that was shared across services. Sometimes we found bugs due to some services used an old version of a library. Then we went through all the services to make sure they all used the latest version of all libraries, and that could take two weeks for one person (full time)! You had to go and ask people about breaking changes that was made several weeks ago or try to figure it out yourself.
The alternative is to not share any code and just copy/paste everything (or implement the same shared functionality from scratch every time) but that is probably even worse, because you will not get rid of the coordination needs and if you find a bug in one service, you have to go through all code in all 100 services manually to see if any of the other 99 services contain the same bug, or hope for the best if you don't.