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[Hastic server](https://hastic.io) [](https://travis-ci.org/hastic/hastic-server)
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[Website](https://hastic.io) |
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[Twitter](https://twitter.com/hasticio)
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Implementation of basic pattern recognition for anomaly detection.
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Implementation of analytic unit for Hastic.
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See also:
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* [Hooks](https://github.com/hastic/hastic-server/blob/master/HOOKS.md) - notifications about events
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* [REST](REST.md) - for developing your plugins
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* [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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You can install it on:
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* [Linux](#linux)
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* [Docker](#docker)
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### Linux
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#### Environment variables
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You can export following environment variables for hastic-server to use:
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- HASTIC_API_KEY - (required) API-key of your Grafana instance
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- 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:
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* [nodejs >= 6.0.0](https://nodejs.org/en/download/package-manager/)
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* [python3](https://www.python.org/downloads/) with pip3
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* curl gnupg git make g++
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#### Intallation
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```bash
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pip3 install pandas seglearn scipy tsfresh
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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
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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>
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export HASTIC_PORT=<port_you_want_to_run_server_on>
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cd ./hastic-server/server
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npm start
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```
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### Docker
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Example of running hastic-server in Docker:
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#### Build
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```bash
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git clone https://github.com/hastic/hastic-server.git
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cd hastic-server
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docker build -t hastic-server .
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```
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#### Run
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```bash
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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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```
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### Known bugs & issues
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- If you add labeled segments while learning - it fails
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- Dataset doesn't get updated after 1st learning
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- Currently only influxDB datasource is supported
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