Use data sources to detect changes that could be anomalies through habit learning!
Progression
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First step to the module Anomaly detection, the Data source learning feature allows you to:
- Know all data sources
- Identify event flow cycles
- Identify flow anomalies
- Notify / alert the user of an anomaly
Examples:
- Source 1 publishes 10 times more events than usual: this is a burst of activity
- Source 2 no longer publishes events: the state of my application is no longer 100% reliable
- Source 2 no longer publishes events: I apply the associated instruction
For more information on Data source learning and many other features of our Open Source hypervision solution, visit the Canopsis documentation (in French, please use your browser translator to read in other languages). Any unanswered questions? You can also discuss with our team directly via the contact form of our website.
Audience
- Supervision pilots
- Administrators
- Application managers
Added value
- Relevance
- Decision support
- Continuous improvement
- Valuation
