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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.
see [REST API](REST.md)
## 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 installation
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Example of running hastic-server in Docker:
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```
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 installation
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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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See [hooks docs](https://github.com/hastic/hastic-server/blob/master/HOOKS.md) for notifications about events.
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#### Dependencies
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- git
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- python3
- nodejs >= 6.0.0
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Example of running hastic-server on Debian / Ubuntu host:
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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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# If you don't have nodejs, uncomment next line:
# curl -sL https://deb.nodesource.com/setup_9.x | bash -
# apt-get install \
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python3 \
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python3-pip \
gnupg \
curl \
make \
g++ \
git
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$ pip3 install pandas
$ pip3 install seglearn
$ pip3 install scipy
$ pip3 install tsfresh
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# apt-get update && apt-get install -y nodejs
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$ git clone https://github.com/hastic/hastic-server.git
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$ cd hastic-server/server
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$ npm install && npm run build
$ npm start
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```