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@ -3,7 +3,11 @@
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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 [REST API](REST.md) |
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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) - 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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@ -27,8 +31,6 @@ 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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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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@ -42,7 +44,7 @@ $ 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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# If you don't have nodejs, uncomment next line: |
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# curl -sL https://deb.nodesource.com/setup_9.x | bash - |
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# apt-get install \ |
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$ apt-get install \ |
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python3 \ |
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python3-pip \ |
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gnupg \ |
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@ -50,12 +52,8 @@ $ export HASTIC_PORT=<port_you_want_to_run_server_on>
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make \ |
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g++ \ |
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git |
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$ pip3 install pandas |
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$ pip3 install seglearn |
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$ pip3 install scipy |
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$ pip3 install tsfresh |
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$ pip3 install pandas seglearn scipy 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 |
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