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2.1 KiB
2.1 KiB
Hastic server
Implementation of basic pattern recognition for anomaly detection.
Implementation of analytics unit for Hastic.
See also:
- Hooks - notifications about events
- REST - for developing your plugins
- HasticPanel - Hastic visualisation plugin for Grafana
Build & run
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
Environment variables
It is possible to 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
Dependencies
System prerequisites:
- git
- nodejs >= 6.0.0
- python3 with pip3
Installation
pip3 install pandas seglearn scipy tsfresh
git clone https://github.com/hastic/hastic-server.git
cd ./hastic-server/server
npm install
npm run build
Run
export HASTIC_API_KEY=<your_grafana_api_key>
export HASTIC_PORT=<port_you_want_to_run_server_on>
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