Slow E350 system with Dockers

  • Hello I am new to openmediavault but I have a litlle experience with debian as a headless homeserver.
    I have OMV4 installed on a passive E350-ITX mainboard with 6gb ram.
    With my previous debian setup I ran Transmission, Emby, sonarr radarr, tvheadend, etc with no isues.
    With the new OMV setup everything runs very SLOW.
    I have tried to install Jellyfin the normal way (command line) but that failed. But I have read here on the forums that the 'new way' of installing applications is via a docker.
    I am new to docker, but I have installed bazarr, jellyfin, ombi, radarr, lidarr, sonarr and deluge.
    When I acces the webui of the applications everything loads slowly.
    I don't know what i am doing wrong.


    The green memory-bar is always at 90% of the 6GB Ram installed.
    I have included messages.txt with a lot of errors the syslog-file was to big to upload here.


    IS there someone that can help me a hand? :)


    Kind regards

  • For the Jellyfin part of the issues installing directly on the OS (no docker):


    I see on your messages.txt a different/incomplete URL for the repo:


    Yellyfin's repo URL:
    https://repo.jellyfin.org/debian[/url] $( lsb_release -c -s ) main
    Your repo URL:
    https://repo.jellyfin.org/debian[/url] $( Release


    Then fails with a clear 404 error:
    Failed to fetch https://repo.jellyfin.org/debian/dists/$(/lsb_stretch/binary-amd64/Packages 404 Not Found

    NOW:
    Mac mini Late 2012 / macOS Catalina / Docker Desktop for Mac
    Intel Core i7-3615QM CPU @ 2.30GHz - 16GB RAM - 4 external disks via USB3.0 - Gigabit Ethernet - 20 docker containers via docker-compose ;)
    PREVIOUS:
    omv 5.2.1-1 (Usul) - Bevy NUC thanks to TechnoDadLife (NUC5CPYB)
    Celeron N3050 @ 1.60GHz - 8GB RAM - 2 external disks via USB3.0 - Gigabit Ethernet - 21 docker containers via docker-compose :)

  • Maybe try the codes on the documentation page again? (https://jellyfin.readthedocs.i…istrator-docs/installing/)


    echo "deb [arch=$( dpkg --print-architecture )] https://repo.jellyfin.org/debian $( lsb_release -c -s ) main" | sudo tee /etc/apt/sources.list.d/jellyfin.list


    Will have to get the wrong one out of /etc/apt/sources.list.d/jellyfin.list


    Watch out for copy/paste from html. Best to get text into an editor first to be sure no formatting from the website gets in the command. Has happened to me (a lot). Just a friendly reminder :)

    NOW:
    Mac mini Late 2012 / macOS Catalina / Docker Desktop for Mac
    Intel Core i7-3615QM CPU @ 2.30GHz - 16GB RAM - 4 external disks via USB3.0 - Gigabit Ethernet - 20 docker containers via docker-compose ;)
    PREVIOUS:
    omv 5.2.1-1 (Usul) - Bevy NUC thanks to TechnoDadLife (NUC5CPYB)
    Celeron N3050 @ 1.60GHz - 8GB RAM - 2 external disks via USB3.0 - Gigabit Ethernet - 21 docker containers via docker-compose :)

  • Thanks for that information!
    Still running a very slow OMV system. If I do a reboot the performance is a lot faster, but after a few hours it is slow again.
    Is it because of the many dockers that my system is running so slowly?

  • You can install glances to take a look at containers and host status in one single screen. Lot of info to diagnose what is happening.

    NOW:
    Mac mini Late 2012 / macOS Catalina / Docker Desktop for Mac
    Intel Core i7-3615QM CPU @ 2.30GHz - 16GB RAM - 4 external disks via USB3.0 - Gigabit Ethernet - 20 docker containers via docker-compose ;)
    PREVIOUS:
    omv 5.2.1-1 (Usul) - Bevy NUC thanks to TechnoDadLife (NUC5CPYB)
    Celeron N3050 @ 1.60GHz - 8GB RAM - 2 external disks via USB3.0 - Gigabit Ethernet - 21 docker containers via docker-compose :)

  • install pip3 using sudo apt install pip3 then pip install glances


    also to activate the docker status view of glances you need to install docker-py for Glances to communicate with docker in the host:
    pip install docker



    Installing Glances using pip3 because the one included in the Debian Stable repositories is an older version which will have no support for docker and showing docker containers status/ram/cpu usage.


    Glances also comes as a docker image: https://hub.docker.com/r/nicolargo/glances/

    NOW:
    Mac mini Late 2012 / macOS Catalina / Docker Desktop for Mac
    Intel Core i7-3615QM CPU @ 2.30GHz - 16GB RAM - 4 external disks via USB3.0 - Gigabit Ethernet - 20 docker containers via docker-compose ;)
    PREVIOUS:
    omv 5.2.1-1 (Usul) - Bevy NUC thanks to TechnoDadLife (NUC5CPYB)
    Celeron N3050 @ 1.60GHz - 8GB RAM - 2 external disks via USB3.0 - Gigabit Ethernet - 21 docker containers via docker-compose :)

    2 Mal editiert, zuletzt von djismgaming ()

  • Check your SWAP usage. You may be swapping a lot to disk because of ram constraints.


    Glances will let you know what very easily. It shows an alert log of things like swap usage, memory usage, cpu-io wait (storage bandwidth constraints) and more in plain english

    NOW:
    Mac mini Late 2012 / macOS Catalina / Docker Desktop for Mac
    Intel Core i7-3615QM CPU @ 2.30GHz - 16GB RAM - 4 external disks via USB3.0 - Gigabit Ethernet - 20 docker containers via docker-compose ;)
    PREVIOUS:
    omv 5.2.1-1 (Usul) - Bevy NUC thanks to TechnoDadLife (NUC5CPYB)
    Celeron N3050 @ 1.60GHz - 8GB RAM - 2 external disks via USB3.0 - Gigabit Ethernet - 21 docker containers via docker-compose :)

  • Example of screen on iOS with Termius SSH client.

    Bilder

    NOW:
    Mac mini Late 2012 / macOS Catalina / Docker Desktop for Mac
    Intel Core i7-3615QM CPU @ 2.30GHz - 16GB RAM - 4 external disks via USB3.0 - Gigabit Ethernet - 20 docker containers via docker-compose ;)
    PREVIOUS:
    omv 5.2.1-1 (Usul) - Bevy NUC thanks to TechnoDadLife (NUC5CPYB)
    Celeron N3050 @ 1.60GHz - 8GB RAM - 2 external disks via USB3.0 - Gigabit Ethernet - 21 docker containers via docker-compose :)

  • As you can see on this screenshot, my sonarr container is eating RAM as an unchained child :D


    3.28 GB to be exact!


    (screenshot using Guacamole for better display)

    Bilder

    NOW:
    Mac mini Late 2012 / macOS Catalina / Docker Desktop for Mac
    Intel Core i7-3615QM CPU @ 2.30GHz - 16GB RAM - 4 external disks via USB3.0 - Gigabit Ethernet - 20 docker containers via docker-compose ;)
    PREVIOUS:
    omv 5.2.1-1 (Usul) - Bevy NUC thanks to TechnoDadLife (NUC5CPYB)
    Celeron N3050 @ 1.60GHz - 8GB RAM - 2 external disks via USB3.0 - Gigabit Ethernet - 21 docker containers via docker-compose :)

  • Exactly. Swapping a lot. You see the red bars and the log indicate this diagnosis. Critical CPU-iowait which means the CPU is waiting for the writing/reading to finish to do more job.


    I think as per your needs, that idea of the new board should be a better bet. As you can see you have 5+GB in use on RAM and same amount in the SWAP.


    If you are going to stay on this one or upgrade it to 8GB, some memory management will be needed.

    NOW:
    Mac mini Late 2012 / macOS Catalina / Docker Desktop for Mac
    Intel Core i7-3615QM CPU @ 2.30GHz - 16GB RAM - 4 external disks via USB3.0 - Gigabit Ethernet - 20 docker containers via docker-compose ;)
    PREVIOUS:
    omv 5.2.1-1 (Usul) - Bevy NUC thanks to TechnoDadLife (NUC5CPYB)
    Celeron N3050 @ 1.60GHz - 8GB RAM - 2 external disks via USB3.0 - Gigabit Ethernet - 21 docker containers via docker-compose :)

  • thank you, It was not easy to get the docker running but here it is! IS there a kind of settings menu in the webgui for glances?


    The settings of glances are set on a configuration file or on the command itself but there are also interactive settings. See here:


    https://glances.readthedocs.io…html#interactive-commands

    NOW:
    Mac mini Late 2012 / macOS Catalina / Docker Desktop for Mac
    Intel Core i7-3615QM CPU @ 2.30GHz - 16GB RAM - 4 external disks via USB3.0 - Gigabit Ethernet - 20 docker containers via docker-compose ;)
    PREVIOUS:
    omv 5.2.1-1 (Usul) - Bevy NUC thanks to TechnoDadLife (NUC5CPYB)
    Celeron N3050 @ 1.60GHz - 8GB RAM - 2 external disks via USB3.0 - Gigabit Ethernet - 21 docker containers via docker-compose :)

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