To invoke forecasting on multiple time series, you simply just need an ML job that is modeling multiple time series. Let's assume that we have an ML job that has analyzed web requests per country. We may have over 200 unique time series in our weblogs because of the diverse clientele that visit our website. In an ML job, in the logs that were collected by Filebeat, we have elected to configure a multi-metric job of the count of requests for every tnginx.access.geoip.country_iso_code:
When we click the Forecast button in the Single Metric Viewer, the forecast will automatically be run for all detectors and partitions (even if there are hundreds or more). Alternatively, you can use the _forecast API endpoint to invoke the forecast. To do so, in the Dev Tools Console, we could issue this request:
POST _xpack/ml/anomaly_detectors/web_traffic_per_country...
