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# Hastic server
Implementation of basic pattern recognition and unsupervised learning for anomaly detection.
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Implementation of analytic unit for Hastic.
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See also:
* [Hooks](https://github.com/hastic/hastic-server/blob/master/HOOKS.md) - notifications about events
* [REST](REST.md) - developing your plugins
* [HasticPanel][https://github.com/hastic/hastic-grafana-graph-panel] - Hastic plugin for Grafana
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## Build & run
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Server needs Grafana's API key (http://<your_grafana_url>/org/apikeys) to query data from Grafana datasources.
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API key role needs only `Viewer` access.
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### Docker
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Example of running hastic-server in Docker:
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```bash
docker build -t hastic-server .
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docker run -d --name hastic-server -p 80:8000 -e HASTIC_API_KEY=<your_grafana_api_key> hastic-server
```
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### Linux
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#### Environment variables
You can export 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
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#### Dependencies
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You need in your system:
* [nodejs >= 6.0.0](https://nodejs.org/en/download/package-manager/)
* [python3 python3-pip](https://www.python.org/downloads/)
* curl gnupg git make g++
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### Intallation
```bash
pip3 install pandas seglearn scipy tsfresh
git clone https://github.com/hastic/hastic-server.git
cd ./hastic-server/server
npm install
npm run build
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```
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### Run
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```bash
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$ export HASTIC_API_KEY=<your_grafana_api_key>
$ export HASTIC_PORT=<port_you_want_to_run_server_on>
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cd ./hastic-server/server
npm start
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```