rodrigo-arenas/kafkaml-anomaly-detection

Project for real-time anomaly detection using Kafka and python

43
/ 100
Emerging

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.

real-time monitoring fraud detection system health operational intelligence streaming analytics
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 8 / 25
Maturity 16 / 25
Community 19 / 25

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Stars

60

Forks

18

Language

Python

License

MIT

Last pushed

Dec 04, 2022

Commits (30d)

0

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