this post was submitted on 05 Jun 2023
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Lemmy
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Based on looking at the code and the relatively small size of the data, I think there may be fundamental scaling issues with the site architecture. Software development may be far more critical than hardware at this point.
What are you seeing in the code that makes it hard do scale horizontally? I've never looked at Lemmy before, but I've done the steps of (monolithic app) -> docker -> make app stateless -> Kubernetes before and as a user, I don't necessarily see the complexity (not saying it's not there, but wondering what specifically in the site architecture prevents this transition)
Right now it looks to me like Lemmy is built all around live real-time data queries of the SQL database. This may work when there are 100 postings a day and an active posting gets 80 comments... but it likely doesn't scale very well. You tend to have to evolve to a queue system where things like comments and votes are merged into the main database in more of a batch process (Reddit does this, you will see on their status page that comments and votes have different uptime tracking than the main website).
On the output side, it seems ideal to have all data live and up to the very instant, but it can fall over under load surges (which may be a popular topic, not just an influx from the decline of Twitter or Reddit). To scale, you tend to have to make some compromises and reuse output. Some kind of intermediate layer such as every 10 seconds only regenerate the output page if there has been a new write (vote or comment change).
It's the lack of complexity that's kind of the problem. Doing direct SQL queries gets you the latest data, but it becomes a big bottleneck. Again, what might have seemed to work fine when there were only 5000 postings and 100,000 total comments in the database can start to seriously fall over when you have reached the point of accumulating 1000 times that.
Do you know of any resources about this, and/or how to implement it?