numaproj/numalogic
Collection of operational time series ML models and tools
This project helps operations engineers and ML engineers automatically detect anomalies in real-time operational data streams, like system logs or sensor readings. It takes in continuous time-series data and outputs anomaly scores, helping to flag unusual behavior without constant manual oversight. This is ideal for teams monitoring complex systems or seeking to automate incident detection.
174 stars. No commits in the last 6 months. Available on PyPI.
Use this if you need to continuously monitor high-volume operational time-series data for anomalies, such as system failures or potential fraud, and want to automate model retraining.
Not ideal if your data is not time-series, or if you prefer a fully manual approach to model development and deployment for anomaly detection.
Stars
174
Forks
31
Language
Python
License
Apache-2.0
Category
Last pushed
Oct 15, 2024
Commits (30d)
0
Dependencies
11
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