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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
Or
pip3 install dict2xml Flask-RESTful pandas scikit-optimize xgboost
3. Download the source code.
mkdir -p /home/gopath/src
cd /home/gopath/src
git clone https://gitee.com/openeuler/A-Tune.git atune
4. Compile.
cd atune
export GO111MODULE=off
make
5. Install.
make install
II. Quick Guide
1. Manage the atuned service.
Load and start the atuned service.
systemctl daemon-reload
systemctl start atuned
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.
Format:
atune-adm list
Example:
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.
Format:
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.