- Machine Learning: other versions:
- What is Elastic Machine Learning?
- Setup and security
- Anomaly detection
- Finding anomalies
- Tutorial: Getting started with anomaly detection
- Advanced concepts
- API quick reference
- How-tos
- Generating alerts for anomaly detection jobs
- Aggregating data for faster performance
- Altering data in your datafeed with runtime fields
- Customizing detectors with custom rules
- Reverting to a model snapshot
- Detecting anomalous locations in geographic data
- Mapping anomalies by location
- Adding custom URLs to machine learning results
- Anomaly detection jobs from visualizations
- Exporting and importing machine learning jobs
- Resources
- Data frame analytics
- Natural language processing
IMPORTANT: No additional bug fixes or documentation updates
will be released for this version. For the latest information, see the
current release documentation.
Appendix I: Uptime anomaly detection configurations
editAppendix I: Uptime anomaly detection configurations
editIf you have appropriate Heartbeat data in Elasticsearch, you can enable this anomaly detection job in the Uptime app in Kibana. For more usage information, refer to Inspect uptime duration anomalies.
Uptime: Heartbeat
editDetect latency issues in heartbeat monitors.
These configurations are available in Kibana only if data exists that matches the recognizer query specified in the manifest file.
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