English | 简体中文

    Introduction to A-Tune

    A-Tune is an OS tuning engine based on AI. A-Tune uses AI technologies to enable the OS to understand services, simplify IT system optimization, and maximize optimal application performance.

    I. A-Tune Installation

    Supported OS: openEuler 1.0 or later

    Method 1 (applicable to common users): Use the default A-Tune of openEuler.

    yum install -y atune

    Method 2 (applicable to developers): Use the source code of the local repository for installation.

    1. Install dependent system software packages.

    yum install -y golang-bin python3 perf sysstat hwloc-gui

    2. Install Python dependent packages.

    yum install -y python3-dict2xml python3-flask-restful python3-pandas python3-scikit-optimize python3-xgboost


    pip3 install dict2xml Flask-RESTful pandas scikit-optimize xgboost scikit-learn

    3. Download the source code.

    git clone

    4. Compile.

    cd A-Tune
    make models

    5. Install.

    make install

    II. Quick Guide

    1. Manage the atuned service.

    Load and start the atuned service.

    systemctl daemon-reload
    systemctl start atuned
    systemctl start atune-engine

    Check the atuned service status.

    systemctl status atuned

    2. Run the atune-adm command.

    The list command.

    This command is used to list the supported workload types, profiles, and the values of Active.


    atune-adm list


    atune-adm list

    The analysis command.

    This command is used to collect real-time statistics from the system to identify and automatically optimize workload types.


    atune-adm analysis [OPTIONS] [APP_NAME]

    Example 1: Use the default model for classification and identification.

    atune-adm analysis

    Example 2: Use the user-defined training model for recognition.

    atune-adm analysis –model ./model/new-model.m

    Example 3: Specify the current system application as MySQL, which is for reference only.

    atune-adm analysis mysql

    For details about other commands, see the atune-adm help information or A-Tune User Guide.

    III. How to contribute

    We welcome new contributors to participate in the project. And we are happy to provide guidance for new contributors. You need to sign CLA before contribution.

    Mail list

    Any question or discussion please contact A-Tune.

    Routine Meeting

    Holding SIG Meeting at 2:30-4:30 PM on Monday every two weeks. You can apply topic by mail list.


    A-Tune is an OS tuning engine based on AI.



    贡献者 17



    • Go 42.3 %
    • Python 40.1 %
    • Shell 11.3 %
    • TSQL 3.4 %
    • Makefile 1.0 %