rodrigo-arenas/kafkaml-anomaly-detection
Project for real-time anomaly detection using Kafka and python
This project helps operations engineers, security analysts, or financial fraud teams monitor incoming streams of data, like transaction logs or system metrics, in real-time to spot unusual patterns. It takes your continuous data stream, identifies deviations from normal behavior using a trained model, and outputs detected anomalies to a separate stream, optionally sending alerts to Slack. This is for anyone needing to quickly identify rare, critical events in live data.
No commits in the last 6 months.
Use this if you need an immediate alert when something out of the ordinary happens in your ongoing data streams, like detecting fraudulent transactions or system failures.
Not ideal if you need to analyze historical data or perform complex, retrospective batch analysis rather than real-time monitoring.
Stars
60
Forks
18
Language
Python
License
MIT
Category
Last pushed
Dec 04, 2022
Commits (30d)
0
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