• @DocBarkowitz@lemm.ee
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    31 year ago

    I’m mobile for the holiday right now, I’m not 100% sure on utilization. But it’s running on a 2 core 4 GB Ubuntu machine along with Caddy and Redis. I also have a Lemmy instance on that same machine so Lemmy, Lemmy-UI, Postgres, and pictr all fit on that machine and work for my daily use.

    I can get exact utilization later tonight.

    • @DocBarkowitz@lemm.ee
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      21 year ago
      docker stats --no-stream
      CONTAINER ID   NAME               CPU %     MEM USAGE / LIMIT    MEM %     NET I/O           BLOCK I/O         PIDS
      dd2a774ad1a6   lemmy_lemmy-ui_1   0.00%     42.5MiB / 3.82GiB    1.09%     418kB / 7.24MB    2.65MB / 0B       15
      718629b5514f   lemmy_lemmy_1      0.03%     6.82MiB / 3.82GiB    0.17%     1.52MB / 1.48MB   864kB / 0B        5
      0c944dccc1e1   lemmy_postfix_1    0.00%     4.762MiB / 3.82GiB   0.12%     3.74kB / 0B       0B / 762kB        7
      7f939790561c   lemmy_postgres_1   0.00%     46.45MiB / 3.82GiB   1.19%     1.09MB / 1.44MB   24.6kB / 2.16MB   9
      14c7db5ae7ec   lemmy_pictrs_1     0.08%     23.36MiB / 690MiB    3.39%     3.81kB / 0B       0B / 0B           13
      3695b8a0b67a   caddy              0.00%     9.984MiB / 3.82GiB   0.26%     0B / 0B           34.1MB / 12.3kB   9
      12c8bd7c1cdf   redis              0.21%     3.555MiB / 3.82GiB   0.09%     101kB / 78.8kB    7.06MB / 0B       5
      f03c3298de46   searxng            0.01%     349.9MiB / 3.82GiB   8.94%     9.21MB / 3.82MB   61.4MB / 61.4kB   25
      

      I guess it is the largest consumer of memory. Unfortunately I rebooted yesterday, while setting up lemmy I noticed there was a decent amount of OS security updates. Otherwise I probably would have had stats from like 6 months of uptime. I’ll keep an eye on it and see if it balloons.

      • @somedaysoon@lemmy.world
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        1 year ago

        Thanks for reporting back on it.

        Yeah, even that, I just don’t understand why a search engine, sitting idle, consumes that much memory. The largest consumers of memory for me are: Omada Controller, Airsonic-Advanced, HomeAssistant, Lidarr, Sonarr, Paperless… all things that process a lot of data, or are written in Java, so it’s to be expected they use more resources.

        I would see it grow to 600MB+ and occasionally crash, so I just decided to use public instances.