Comment by yowlingcat

Comment by yowlingcat 3 days ago

I see a lot of value in spinning up microservices where the database is global across all services (and not inside the service) but I struggle more to see the value of separate core transactional databases for separate services unless/until the point where two separate parts of the organizations are almost two separate companies that cannot operate as a single org/single company. You lose data integrity, joining ability, one coherent state of the world, etc.

The main time I can see this making sense is when the data access patterns are so different in scale and frequency that they're optimizing for different things that cause resource contention, but even then, my question would become do you really need a separate instance of the same kind of DB inside the service, or do you need another global replica/a new instance of a new but different kind of DB (for example Clickhouse if you've been running Postgres and now need efficient OLAP on large columnar data).

Once you get to this scale, I can see the idea of cell-based architecture [1] making sense -- but even at this point, you're really looking at a multi-dimensionally sharded global persistence store where each cell is functionally isolated for a single slice of routing space. This makes me question the value of microservices with state bound to the service writ large and I can't really think of a good use case for it.

[1] https://docs.aws.amazon.com/wellarchitected/latest/reducing-...

mjr00 3 days ago

> I see a lot of value in spinning up microservices where the database is global across all services (and not inside the service)

This issue with this is schema evolution. As a very simple example, let's say you have a User table, and many microservices accessing this table. Now you want to add an "IsDeleted" column to implement soft deletion; how do you do that? First you need to add the actual column to the database, then you need to go update every single service which queries that table and ensure that it's filtering out IsDeleted=True, deploy all those services, and only then can you actually start using the column. If you must update services in lockstep like this, you've built a distributed monolith, which is all of the complexity of microservices with none of the benefits.

A proper service-oriented way to deal with this is have a single service with control of the User table and expose a `GetUsers` API. This way, only one database and its associated service needs to be updated to support IsDeleted. Because of API stability guarantees--another important guarantee of good SoA--other services will continue to only get non-deleted users when using this API, without any updates on their end.

> You lose data integrity, joining ability, one coherent state of the world, etc.

You do lose this! And it's one of the tradeoffs, and why understanding your domain is so important for doing SoA well. For subsets of the domain where data integrity is important, it should all be in one database, and controlled by one service. For most domains, though, a lot of features don't have strict integrity requirements. As a concrete though slightly simplified example, I work with IoT time-series data, and one feature of our platform is using some ML algorithms to predict future values based on historical trends. The prediction calculation and storage of its results is done in a separate service, with the results being linked back via a "foreign key" to the device ID in the primary database. Now, if that device is deleted from the primary database, what happens? You have a bunch of orphaned rows in the prediction service's database. But how big of a deal is this actually? We never "walk back" from any individual prediction record to the device via the ID in the row; queries are always some variant of "give me the predictions for device ID 123". So the only real consequence is a bit of database bloat, which can be resolved via regularly scheduled orphan checking processes if it's a concern.

It's definitely a mindshift if you're used to a "everything in one RDBMS linked by foreign keys" strategy, but I've seen this successfully deployed at many companies (AWS, among others).

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yowlingcat 14 hours ago

I get your point around the soft deletion example but that sounds more like poor module separation + relational query abstraction/re-use rather than a shared database issue. Whether it's through a service, a module or a library, leaky abstraction boundaries will always cause issues. I see your point about separately versioning separate services which I think can make certain kinds of migrations more tractable -- but it comes at the expense of making it heavier and prolonging the duration of supporting two systems.
The difference I generally see with shared-state microservices is that now you introduce a network call (although you have a singular master for your OLTP state), and with isolated state microservices, now you are running into multiple store synchronization issues and conflict resolution. Those tradeoffs are very painful to make and borderline questionable to me without a really good reason to sacrifice them (reasons I rarely see but can't in good faith say never happen).
Pertaining to your IoT example -- that's definitely a spot where I see a reason to move out of the cozy RDBMS, which is an access pattern that is predominated by reads and writes of temporal data in a homogenous row layout and seemingly little to no updates -- a great use case for a columnar store such as Clickhouse. I've resisted moving onto it at $MYCORP because of the aforementioned paranoia about losing RDBMS niceties (and our data isn't really large enough for vertical scaling to not just work) but I could see that being different if our data got a lot larger a lot more quickly.
Maybe putting it together, there are maybe only several reasons I've seen where microservices are genuinely the right tool for a specific job (and which create value even with shared state/distributed monolith):
1) [Shared state] Polyglot implementation -- this is the most obvious one that's given leverage for me at other orgs; being able to have what's functionally a distributed monolith allows you to use multiple ecosystems at little to no ongoing cost of maintenance. This need doesn't happen for me that often given I often work in the Python ecosystem (so being able to drop down into cython, numba, etc is always an option for speed and the ecosystem is massive on its own), but at previous orgs, spinning up a service to make use of the Java ecosystem was a huge win for the org over being stuck in the original ecosystem. Aside from that, being able to deploy frontend and backend separately is probably the simplest and most useful variant of this that I've used just about everywhere (given I've mostly worked at shops that ship SPAs).
2) [Shared state] SDLC velocity -- as a monolith grows it just gets plain heavy to check out a large repository, set up the environment run tests, and have that occur over and over again in CI. Being able to know that a build recipe and test suite for just a subset of the codebase needs to occur can really create order of magnitude speed ups in wall to wall CI time which in my experience tends to be the speed limit for how quickly teams can ship code.
3) [Multi-store] Specialized access patterns at scale -- there really are certain workloads that don't play that well with RDBMS in a performant and simple way unless you take on significant ongoing maintenance burden -- two I can think of off the top of my head are large OLAP workloads and search/vector database workloads; no real way of getting around needing to use something like ElasticSearch when Postgres FTS won't cut it, and maybe no way around using something like Clickhouse for big temporal queries when it would be 10x more expensive and brittle to use postgres for it; even so, these still feel more like "multiple singleton stores" rather than "one store per service"
4) [Multi-store] Independent services aligned with separate lines of revenue -- this is probably the best case I can think of for microservices from a first principles level. Does the service stand on its own as a separate product and line of revenue from the rest of the codebase, and is it actually sold by and operated by the business that independently? If so, it really is and should be its own "company" inside a company and it makes sense for it to have the autonomy and independence to consume its upstream dependencies (and expose dependencies to its downstream) however it sees fit. When I was at AWS, this was a blaringly obvious justification, and one that made a lot of intuitive sense to me given that so much of the good stuff that Amazon builds to use internally is also built to be sold externally.
5 [Multi-store] Mechanism to enforce hygiene and accountability around organizational divisions of labor - to me, this feels like the most questionable and yet most common variant that I often see. Microservices are still sexy and have the allure of creating high visibility career advancing project track records for ambitious engineers, even if at the detriment to the good of the company they work for. Microservices can be used as a bureaucratic mechanism to enforce accountability and ownership of one part of the codebase to a specific team to prevent the illegibility of tragedy of the commons -- but ultimately, I've often found that the forces and challenges that lead to those original tragedy of the commons are not actually solved any better in the move to microservices and if anything the cost of solving it is actually increased.

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