This project born from the need of detect anomalies on multiple and completely different signals, and react to it rapidly. To achieve this, Bluekiri decided to implement its own system to manage multiple signals at the same time in a easy and scalable way.
This project is not focused on Machine Learning models, but in an effective Framework to put those models in production.
This project uses Tornado, RxPy, Apache Spark and WebSockets to aggregate and process streams of signals to detect anomalies and display it live on a dashboard.
You can read the documentation at anomalydetection.readthedocs.io
Please visit the Anomaly Detection Framework Documentation for help with Install, Configuration or read how to Deploy each individual component. You can also find how to extend the Framework via Plugins to adapt to your needs
Anomaly Detection Framework
Copyright (C) 2018 Bluekiri BigData Team <bigdata@bluekiri.com>
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as
published by the Free Software Foundation, either version 3 of the
License, or (at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License
along with this program. If not, see <https://www.gnu.org/licenses/>. David Martín :: Suki_ :: 🤔 |
 Óscar 💻 🤔 |
 Cristòfol Torrens 💻 📖 🤔 |
 juan huguet 💻 🤔 |
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Thanks goes to these wonderful people (emoji key):
This project follows the all-contributors specification. Contributions of any kind welcome!