Adding Custom URLs To Machine Learning Resultsedit

When you create an advanced job or edit any job in Kibana, you can optionally attach one or more custom URLs. You can also specify these custom settings when you create or update jobs by using the machine learning APIs.

The custom URLs provide links from the anomalies table in the Anomaly Explorer or Single Metric Viewer window in Kibana to custom dashboards or external websites. For example, you can define a custom URL that provides a way for users to drill down to the source data from the results set.

For each custom URL, you must supply the URL and a label, which is the link text that appears in the anomalies table.

Links in the Anomaly Explorer anoamilies table

String Substitution in Custom URLsedit

You can use dollar sign ($) delimited tokens in a custom URL. These tokens are substituted for the values of the corresponding fields in the anomaly records. For example, for a configured URL of http://my.datastore.com/dashboards?user=$user_name$, the value of the user_name field in the anomaly record is substituted into the $user_name$ token when you click the link in the anomalies table.

Not all fields in your source data exist in the anomaly results. If a field is specified in the detector as the field_name, by_field_name, over_field_name, or partition_field_name, for example, it can be used in a custom URL. A field that is only used in the categorization_field_name property, however, does not exist in the anomaly results.

The following keywords can also be used as tokens for string substitution in a custom URL: $earliest$; $latest$; $mlcategoryregex$; $mlcategoryterms$.

The $earliest$ and $latest$ tokens pass the beginning and end of the time span of the selected anomaly to the target page. The tokens are substituted with date-time strings in ISO-8601 format. If you selected an interval of 1 hour for the anomalies table, these tokens use one hour on either side of the anomaly time as the earliest and latest times. The same is also true if the interval is set to Auto and a one hour interval was chosen.

The $mlcategoryregex$ and $mlcategoryterms$ tokens pertain to jobs where you are categorizing field values. For more information about this type of analysis, see Categorizing log messages.

The $mlcategoryregex$ token passes the regular expression value of the category of the selected anomaly, as identified by the value of the mlcategory field of the anomaly record.

The $mlcategoryterms$ token likewise passes the terms value of the category of the selected anomaly. Each categorization term is prefixed by a plus (+) character, so that when the token is passed to a Kibana dashboard, the resulting dashboard query seeks a match for all of the terms of the category.

For example, the following API updates a log_categories job to add a custom URL that uses $earliest$, $latest$, and $mlcategoryterms$ tokens:

POST _xpack/ml/anomaly_detectors/log_categories/_update
{
  "custom_settings": {
        "custom_urls": [
          {
            "url_name": "test-link1",
            "url_value": "http://localhost:5601/app/kibana#/discover?_g=(refreshInterval:(display:Off,pause:!f,value:0),time:(from:'$earliest$',mode:quick,to:'$latest$'))&_a=(columns:!(_source),index:AV3OWB68ue3Ht69t29aw,interval:auto,query:(query_string:(analyze_wildcard:!t,query:'$mlcategoryterms$')),sort:!(time,desc))"
          }
        ]
      }
}

When you click this custom URL in the anomalies table in Kibana, it opens up the Discover page and displays source data for the period when the anomaly occurred. Since this job was categorizing log messages, some $mlcategoryterms$ token values that were passed to the target page for an example anomaly are as follows:

A query for category terms on the Discover page in Kibana
  • The custom URL links in the anomaly tables use pop-ups. You must configure your web browser so that it does not block pop-up windows or create an exception for your Kibana URL.
  • When creating a link to a Kibana dashboard, the URLs for dashboards can be very long. Be careful of typos, end of line characters, and URL encoding. Also ensure you use the appropriate index ID for the target Kibana index pattern.
  • If you use an influencer name for string substitution, keep in mind that it might not always be available in the analysis results and the URL is invalid in those cases. There is not always a statistically significant influencer for each anomaly.
  • The dates substituted for $earliest$ and $latest$ tokens are in ISO-8601 format and the target system must understand this format.
  • If the job performs an analysis against nested JSON fields, the tokens for string substitution can refer to these fields using dot notation. For example, $cpu.total$.
  • Elasticsearch source data mappings might make it difficult for the query string to work. Test the custom URL before saving the job configuration to check that it works as expected, particularly when using string substitution.