- Kibana Guide: other versions:
- What is Kibana?
- What’s new in 7.13
- Kibana concepts
- Quick start
- Set up
- Install Kibana
- Configure Kibana
- Alerting and action settings
- APM settings
- Banners settings
- Development tools settings
- Graph settings
- Fleet settings
- i18n settings
- Logging settings
- Logs settings
- Metrics settings
- Machine learning settings
- Monitoring settings
- Reporting settings
- Secure settings
- Search sessions settings
- Security settings
- Spaces settings
- Task Manager settings
- Telemetry settings
- URL drilldown settings
- Start and stop Kibana
- Access Kibana
- Securing access to Kibana
- Add data
- Upgrade Kibana
- Embed Kibana content in a web page
- Configure monitoring
- Configure security
- Production considerations
- Discover
- Dashboard
- Canvas
- Maps
- Machine learning
- Graph
- Alerting
- Observability
- APM
- Security
- Dev Tools
- Stack Monitoring
- Stack Management
- Fleet
- Reporting
- REST API
- Kibana plugins
- Accessibility
- Release notes
- Developer guide
IMPORTANT: No additional bug fixes or documentation updates
will be released for this version. For the latest information, see the
current release documentation.
Data frame analytics
editData frame analytics
editThis functionality is in technical preview and may be changed or removed in a future release. Elastic will work to fix any issues, but features in technical preview are not subject to the support SLA of official GA features.
The Elastic machine learning data frame analytics feature enables you to analyze your data using classification, outlier detection, and regression algorithms and generate new indices that contain the results alongside your source data.
If you have a license that includes the machine learning features, you can create data frame analytics jobs and view their results on the Data Frame Analytics page in Kibana. For example:
For more information about the data frame analytics feature, see Machine learning data frame analytics.
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