With forewarning about a huge influx of users, you know Lemmy.ml will go down. Even if people go to https://join-lemmy.org/instances and disperse among the great instances there, the servers will go down.

Ruqqus had this issue too. Every time there was a mass exodus from Reddit, Ruqqus would go down, and hardly reap the rewards.

Even if it’s not sustainable, just for one month, I’d like to see Lemmy.ml drastically boost their server power. If we can raise money as a community, what kind of server could we get for 100$? 500$? 1,000$?

  • nutomic@lemmy.mlM
    link
    fedilink
    arrow-up
    27
    ·
    1 year ago

    It should be easy once websocket is removed. Sharded postgres and multiple instances of frontend/backend. Though I don’t have any experience with this myself.

    • Bob/Paul@fosstodon.org
      link
      fedilink
      arrow-up
      12
      ·
      1 year ago

      @nutomic @Lobstronomosity In one of the comments I thought I saw that the biggest CPU load was due to image resizing.

      I think it might be easier to split the image resizer off to its own worker that can run independently on one (or more) external instances. Example: client uses API to get a temporary access token for upload, client uploads to one of many image resizers instead of the main API, image resizer sends output back the main API.

      Then your main instance never sees the original image

    • wiki_me@lemmy.ml
      link
      fedilink
      arrow-up
      11
      ·
      1 year ago

      I think that is unavoidable, Look at the most popular subreddits , they can get something like 80 million upvotes and 66K comments per day, do you think a single server can handle that?

      Splitting communities just so that it will be easier technically is not good UX.

    • ccunix@lemmy.ml
      link
      fedilink
      arrow-up
      8
      ·
      1 year ago

      There is already a docker image so that should not be too hard. I’d be happy to set something up, but (as others have said) the DB will hit a bottleneck relatively quickly.

      I like the idea of splitting off the image processing.