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rozetko
b9917d34f9
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7 years ago | |
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server | 7 years ago | |
src | 7 years ago | |
.gitignore | 7 years ago | |
Dockerfile | 7 years ago | |
LICENSE | 7 years ago | |
README.md | 7 years ago | |
REST.md | 7 years ago |
README.md
Hastic server
Implementation of basic pattern recognition and unsupervised learning for anomaly detection.
Implementation of analytic unit for Hastic. see REST API
Build & run
First of all, you should generate API key in your Grafana instance.
Without API key hastic-server will not be able to use your datasources.
Docker
Example of running hastic-server in Docker:
docker build -t hastic-server .
docker run -d --name hastic-server -p 80:8000 -e HASTIC_API_KEY=<your_grafana_api_key> hastic-server
Linux
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
Dependencies
- python3 with:
- pip
- pandas
- seglearn
- scipy
- tsfresh
- nodejs >= 9
Example of running hastic-server on Debian / Ubuntu host:
$ export HASTIC_API_KEY=<your_grafana_api_key>
$ export HASTIC_PORT=<port_you_want_to_run_server_on>
# apt-get install python3 \
python3-pip \
gnupg \
curl \
make \
g++ \
git
$ pip3 install pandas
$ pip3 install seglearn
$ pip3 install scipy
$ pip3 install tsfresh
$ curl -sL https://deb.nodesource.com/setup_9.x | bash -
# apt-get update && apt-get install -y nodejs
$ cd server
$ npm install && npm run build
$ npm start