You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
3.2 KiB
3.2 KiB
Hastic server
Implementation of basic pattern recognition for anomaly detection.
Implementation of analytics unit for Hastic.
Please note that we are still in alpha, so features are subject to change
See also:
- Hooks - notifications about events
- REST - for developing your plugins
- HasticPanel - Hastic visualisation plugin for Grafana
Download & Install on Linux
You need only nodejs >= 6.14 on your machine.
wget https://github.com/hastic/hastic-server/releases/download/0.1.2-alpha/hastic-server-0.1.2-alpha.tar.gz
tar -zxvf hastic-server-0.1.2-alpha.tar.gz
cd hastic-server-0.1.2-alpha/server/dist
node server
Build & run from source
Hastic server requires Grafana's API key (http://<your_grafana_url>/org/apikeys) to query data from Grafana datasources.
API key role requires only Viewer
access.
Possible to install on:
Linux
System prerequisites:
- git
- nodejs >= 8.x, but there is special build for nodejs 6.14
- python3 with pip3
Installation
pip3 install -r analytics/requirements.txt
git clone https://github.com/hastic/hastic-server.git
cd ./hastic-server/server
npm install
npm run build
Configuration
You can configure hastic-server using either environment variables or config file.
NOTE: environment variables have higher priority than config file.
Environment variables
You can export the following environment variables for hastic-server to use:
- HASTIC_API_KEY - (required) API-key of your Grafana instance
- HASTIC_PORT - (optional) port you want to run server on, default: 8000
e.g.
export HASTIC_API_KEY=eyJrIjoiVjZqMHY0dHk4UEE3eEN4MzgzRnd2aURlMWlIdXdHNW4iLCJuIjoiaGFzdGljIiwiaWQiOjF9
export HASTIC_PORT=8080
Config file
You can also rename config.example.json
to config.json
and set your values there.
Run
cd ./hastic-server/server
npm start
Docker
Build
git clone https://github.com/hastic/hastic-server.git
cd hastic-server
docker build -t hastic-server .
Run
docker run -d --name hastic-server -p 80:8000 -e HASTIC_API_KEY=<your_grafana_api_key> hastic-server
Known bugs & issues
- Adding labeled segments while learning is in progress is not supported
- Dataset doesn't update after 1st learning
- Currently only influxDB datasource is supported
Changelog
[0.1.2-alpha] - 2018-06-25
Fixed
- Error: type object 'sklearn.tree...' #28
[0.1.1-alpha] - 2018-06-25
Added
- HASTIC_API_KEY to config file #23