this post was submitted on 15 Jun 2023
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My first experience with Lemmy was thinking that the UI was beautiful, and lemmy.ml (the first instance I looked at) was asking people not to join because they already had 1500 users and were struggling to scale.

1500 users just doesn't seem like much, it seems like the type of load you could handle with a Raspberry Pi in a dusty corner.

Are the Lemmy servers struggling to scale because of the federation process / protocols?

Maybe I underestimate how much compute goes into hosting user generated content? Users generate very little text, but uploading pictures takes more space. Users are generating millions of bytes of content and it's overloading computers that can handle billions of bytes with ease, what happened? Am I missing something here?

Or maybe the code is just inefficient?

Which brings me to the title's question: Does Lemmy benefit from using Rust? None of the problems I can imagine are related to code execution speed.

If the federation process and protocols are inefficient, then everything is being built on sand. Popular protocols are hard to change. How often does the HTTP protocol change? Never. The language used for the code doesn't matter in this case.

If the code is just inefficient, well, inefficient Rust is probably slower than efficient Python or JavaScript. Could the complexity of Rust have pushed the devs towards a simpler but less efficient solution that ends up being slower than garbage collected languages? I'm sure this has happened before, but I don't know anything about the Lemmy code.

Or, again, maybe I'm just underestimating the amount of compute required to support 1500 users sharing a little bit of text and a few images?

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[–] [email protected] 86 points 1 year ago (18 children)

The numbers are a little higher than you mention (currently ~3.2k active users). The server isn't very powerful either, it's now running on a dedicated server with 6 cores/12 threads and 32 gb ram. Other public instances are using larger servers, such as lemmy.world running on a AMD EPYC 7502P 32 Cores “Rome” CPU and 128GB RAM or sh.itjust.works running on 24 cores and 64GB of RAM. Without running one of these larger instances, I cannot tell what the bottleneck is.

The issues I've heard with federation are currently how ActivityPub is implemented, and possibly the fact all upvotes are federated individually. This means every upvote causes a federation queue to be built, and with a ton of users this would pile up fast. Multiply this by all the instances an instance is connected to and you have an exponential increase in requests. ActivityPub is the same protocol used by other federated servers, including Mastodon which had growing pains but appears to be running large instances smoothly now.

Other than that, websockets seem to be a big issue, but is being resolved in 0.18. It also appears every connected user gets all the information being federated, which is the cause for the spam of posts being prepended to the top of the feed. I wouldn't be surprised if people are already botting content scrapers/posters as well, which might cause a flood of new content which has to get federated which causes queues to back up; this is mostly speculation though.

As it goes with development, generally you focus on feature sets first. Optimization comes once you reach a point a code-freeze makes sense, then you can work on speeding things up without new features breaking stuff. This might be an issue for new users temporarily, but this project wasn't expecting a sudden increase in demand. This is a great way to show where inefficiencies are and improve performance is though. I have no doubt these will be resolved in a timely manner.

My personal node seems to use minimal resources, not having even registered compared to my other services. Looking at the process manager the postgres/lemmy backend/frontend use ~250MB of RAM.

For now, staying off lemmy.ml and moving communities to other instances is probably best. The use case of large instances anywhere near the scale of reddit wasn't the goal of the project until reddit users sought alternatives. We can't expect to show up here and demand it work how we want without a little patience and contributing.

[–] [email protected] 5 points 1 year ago (1 children)

What specs are you running your instance on?

[–] [email protected] 14 points 1 year ago (1 children)

An old Chromebox G1 (i7-4600U and 8GB of ram) with a 128GB internal NGFF and external 1TB NVMe. It's by no means powerful or expensive hardware. I'm also only receiving federated posts for my subscribed communities, and sending out these comments I write so it's a lot lower workload than the larger instances.

[–] [email protected] 6 points 1 year ago (1 children)

Hosting a personal instance is the direction I want to go. That'll be a winter project, though. It's fishing/swimming/rowing/woodworking season now :)

Are there any general tips or hidden dangers you can share? Or is it as straightforward as just putting my nose into documentation and playing around a bit?

[–] [email protected] 5 points 1 year ago

Right now there appears to be no more danger than hosting anything else. I run my services behind a reverse proxy to insulate my home LAN from the wider internet, but hooking anything up to the internet comes with potential dangers.

I personally wrote a helm chart for kubernetes to host the service, and a few more can be found here. I have some work to do yet on the helm chart but it closely mirrors the docker-compose file provided by the developers. Deployment of an instance should be a lot easier soon, with all the increased interest and contributions.

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