- 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
- Detecting anomalous categories of data
- 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
Export and import machine learning jobs
editExport and import machine learning jobs
editIn Kibana, you can export and import your machine learning job and datafeed configuration details in Stack Management > Machine Learning Jobs. For example, you can export jobs from your test environment and import them into your production environment.
The exported file contains configuration details; it does not contain the machine learning models. For anomaly detection, you must import and run the job to build a model that is accurate for the new environment. For data frame analytics, trained models are portable and can be transferred between clusters as described in Exporting and importing models.
There are some additional actions that you must take before you can successfully import and run your jobs:
- The Kibana data views that are used by anomaly detection datafeeds and data frame analytics source indices must exist; otherwise, the import fails.
- If your anomaly detection jobs use custom rules with filter lists, the filter lists must exist; otherwise, the import fails. To create filter lists, use Kibana or the create filters API.
- If your anomaly detection jobs were associated with calendars, you must create the calendar in the new environment and add your imported jobs to the calendar. Use Kibana or the create calendars, add events to calendar, and add jobs to calendar APIs.
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