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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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A3
Discontinued Inspired by recent advances in coverage-guided analysis of neural networks, we propose a novel anomaly detection method. We show that the hidden activation values contain information useful to distinguish between normal and anomalous samples. Our approach combines three neural networks in a purely data-driven end-to-end model. Based on the activation values in the target network, the alarm network decides if the given sample is normal. Thanks to the anomaly network, our method even works in stri
Some good stuff here (tools and libraries). https://github.com/rob-med/awesome-TS-anomaly-detection
p.p.s if curious here is a sort of first stab at what I built using PyOD to try add some anomaly detection to the open source monitoring agent where I work. https://github.com/netdata/netdata/tree/master/collectors/python.d.plugin/anomalies
As the code is available as well, you can directly test the approach and see if it is a viable solution for the telemetry data: https://github.com/Fraunhofer-AISEC/A3/
Also Numenta NAB paper is a good starting point. https://github.com/numenta/NAB