I know that Lemmy is open source and it can only get better from here on out, but I do wonder if any experts can weigh in whether the foundation is well written? Or are we building on top of 4 years worth of tech debt?
I know that Lemmy is open source and it can only get better from here on out, but I do wonder if any experts can weigh in whether the foundation is well written? Or are we building on top of 4 years worth of tech debt?
I disagree that it being a monolith is immediately a problem, but also
This is just not true. With microservices, it is easy to scale out individual services to multiple instances as demand requires them. Hosting a fleet of entire Lemmy instances is far more expensive than just small slices of it that may require the additional processing power.
What microservices would you split Lemmy into? The database, image hosting and the UI are already separate.
Well, I’m going to start by repeating that I don’t necessarily agree that it being monolithic is necessarily a problem right now.
The immediate thought in my mind would be all of the federation logic. That’s where all of the instances seem to be lagging behind, and it seems the common fix is “just increase the workers to one billion”. Apparently that does something meaningful, but the developer in me wants to know how a few cores can put so many workers to use.
Spinning federation off into a microservice means you could deploy it on something like Cloud Run or AWS ECS, and have it autoscale as the workload demands it. Seems like a pretty prime candidate to me.
To me this sounds like a code / DB problem more so than a monolith vs microservice issue. You can totally run only the worker part of a monolith inside AWS ECS and have it autoscale, this is not specific to microservices.
I’d split it out into a few systems
The ultimate goal, and I don’t know how possible it is with rust, would be to have a way to run those as individual services or as one part of a larger monolith. Smaller instances would be able to run it as one binary, while larger instances like Lemmy.world or Lemmy.ml can run each part independently. That would allow easier scaling on large instances while (hopefully) leaving it just as simple to deploy on a small scale too.
There’s no reason to split it into 100 different services, but 4-5 mid sized ones might help.
Lemmy’s backend is native code, not run in a virtual machine or interpreted from text like most backends (Java and PHP are still so, so popular, as is Python). You’re not going to pay much extra for an extra megabyte or 10 of RAM being used per instance for the extra code sitting idle. It certainly shouldn’t use much processing power when not in use.
I’d be less concerned with memory (of which Lemmy seems to use very little), and much more concerned with CPU core count. I touched on it in my other comment, but I don’t understand how a few cores is supposed to handle the ridiculous number of federation workers people are setting their instances to.
Does code that exists but isn’t being executed often actually impact CPU usage that much?
Linux kernel has like 30 million lines of code and you probably compile a fifth of it into your actual kernel binary by default. That’s still several million lines, but it doesn’t use much CPU at all. Rather, eliminating all the excess code keeps your size down so you can load it from disk in 0.0001 seconds instead of 0.0002.
Now if code that doesn’t need to run often, runs more often because we scaled the monolith horizontally - that IS a problem, but it’s not a problem inherent to the monolith design pattern, but rather a specific instance of bad design.
Again, my knowledge of the Lemmy codebase is very small, and we could possibly host the monolith in microservices style. The point I am making is this (when it comes to scaling monolith vs microservices):
If the federation logic were split out, we could configure it to run on super tiny docker instances on Google Cloud or AWS. Any time we needed it to, it would autoscale to handle the traffic. The configuration for these dockers could be super minimal memory, no storage, and multiple weak CPU cores. This would be super affordable while still being able to handle as much traffic from federation as we ask it to. One of the cool things with Google Cloud Run is that it handles load balancing between docker containers for you (just point the federation traffic at the necessary URL)
IF Lemmy has things like background services, scheduled tasks, etc, this would significantly muddy the water (we would need each service to be able to handle being run on a multitude of instances, or we would need to be able to disable each one instance by instance). And if we just scaled by spinning up more instances of Lemmy, we would also need to ensure that only federation traffic is heading to the weaker instances that we spun up for such purpose, or we would need to ensure that each spun up instance has enough resources to handle federation traffic along with the main application.
I feel like I need to state once more: I don’t necessarily think Lemmy needs to move to microservices. Only that scaling monolith vs microservices is not necessarily the same.
I suppose that’s completely fair - async workers tend to fare well as standalone services and are often split off even in monoliths. But I guess what I’m saying is that splitting it might not actually win you THAT much compared to just scaling the whole thing. Not until we’re talking like 100 runners to 1 API instance or something. It gives you a bit of additional flexibility, but won’t necessarily be a huge difference in total resource cost, is what I’m saying. But it is still a good idea because it results in cleaner code and, as outlined before, tinier docker images.
Also the thing about Google Cloud Run is that it’s probably not a good idea for many instance owners. Autoscaling can lead to unexpected costs if set up by an amateur. But that’s an unrelated can of worms.
Agreed (along with all things cloud!). That said, Cloud Run does a good job of letting you define how many connections each container can handle, and a max number of containers (and min) to scale to.
You can easily scale a monolith. You typically horizontally replicate any web server (monolith or not) to handle whatever traffic you’re getting. It shouldn’t really matter what type of traffic it is. Plenty of the world’s biggest websites run monoliths in production. You know how people used to say “rails doesn’t scale”? Well they were wrong because Rails monoliths are behind some huge companies like GitHub and Shopify.
The lemmy backend is also quite lightweight and parallel so it’s cheap and effective to replicate.
In my professional experience microservices are usually a dumpster fire from both the dev perspective and an ops perspective (I’m a Site Reliability Engineer).
This isn’t really contradictory to what I said. I only wished to express that the two don’t scale exactly the same (in terms of execution)