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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.
Supported OS: openEuler 1.0 or later
yum install -y atune
For openEuler 20.09 or later, atune-engine is needed
yum install -y atune-engine
yum install -y golang-bin python3 perf sysstat hwloc-gui
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
git clone https://gitee.com/openeuler/A-Tune.git
cd A-Tune make models make
systemctl daemon-reload systemctl start atuned systemctl start atune-engine
systemctl status atuned
This command is used to list the supported workload types, profiles, and the values of Active.
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.
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.
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.
Any question or discussion please contact A-Tune.
Holding SIG Meeting at 10:00-12:00 AM on Friday every two weeks. You can apply topic by A-Tune mail list.
：Code submit frequency
：React/respond to issue & PR etc.
：Well-balanced team members and collaboration
：Recent popularity of project
：Star counts, download counts etc.