From 0 to Anomaly Detection in your infrastructure metrics in 15 minutes

From 0 to Anomaly Detection in your infrastructure metrics in 15 minutes

Using the NuPIC framework (https://github.com/numenta/nupic/tree...), we will show the basics of Anomaly Detection using HTM ( Hierarchical Temporal Memory), and perform a demo trying to detect an anomaly in an infrastructure metric (such as a host CPU).

Transcript

  1. 1.

    Alejandro Guirao @lekum From 0 to anomaly detection in your

    infrastructure metrics in 15 minutes github.com/lekum
  2. 2.

    “ The checks are often inflexible Boolean logic or arbitrary

    static in time thresholds. They generally rely on a specific result or range being matched. The checks again don’t consider the dynamism of most complex systems. A match or a breach in a threshold may be important or could have been triggered by an exceptional event—or it could even be a natural consequence of growth. James Turnbull (“The Art of Monitoring”)
  3. 3.

    ◉ Biologically constrained theory of machine intelligence ◉ “On Intelligence”

    (2004, Jeff Hawkins) ◉ Numenta (2005) Time-based learning algorithms that store and recall temporal patterns Hierarchical Temporal Model (HTM)
  4. 4.

    ◉ Encoders ◉ Spatial Poolers -> Sparsely Dense Representation ◉

    Temporal Pooler -> Cortical Learning Algorithm HTM concepts