Hastic server

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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

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
• Docker

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

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