Reference for Kibana extensions

By default, Vega visualizations use the autosize = { type: 'fit', contains: 'padding' } layout. fit uses all available space, ignores width and height values, and respects the padding values. To override this behavior, change the autosize value.

Kibana registers a default Vega color scheme with the id elastic, and sets a default color for each mark type. Override it by providing a different stroke, fill, or color (Vega-Lite) value.

[preview] This 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. Kibana extends the Vega data elements with support for direct Elasticsearch queries specified as a url.

Because of this, Kibana is unable to support dynamically loaded data, which would otherwise work in Vega. All data is fetched before it’s passed to the Vega renderer.

To define an Elasticsearch query in Vega, set the url to an object. Kibana will parse the object looking for special tokens that allow your query to integrate with Kibana. These tokens are:

Putting this together, an example query that counts the number of documents in a specific index:

// An object instead of a string for the URL value
// is treated as a context-aware Elasticsearch query.
url: {
  // Specify the time filter.
  %timefield%: @timestamp
  // Apply dashboard context filters when set
  %context%: true

  // Which indexes to search
  index: kibana_sample_data_logs
  // The body element may contain "aggs" and "query" keys
  body: {
    aggs: {
      time_buckets: {
        date_histogram: {
          // Use date histogram aggregation on @timestamp field
          field: @timestamp 
          // interval value will depend on the time filter
          // Use an integer to set approximate bucket count
          interval: { %autointerval%: true }
          // Make sure we get an entire range, even if it has no data
          extended_bounds: {
            min: { %timefilter%: "min" }
            max: { %timefilter%: "max" }
          }
          // Use this for linear (e.g. line, area) graphs
          // Without it, empty buckets will not show up
          min_doc_count: 0
        }
      }
    }
    // Speed up the response by only including aggregation results
    size: 0
  }
}

The full result includes the following structure:

{
  "aggregations": {
    "time_buckets": {
      "buckets": [{
          "key_as_string": "2015-11-30T22:00:00.000Z",
          "key": 1448920800000,
          "doc_count": 28
        }, {
          "key_as_string": "2015-11-30T23:00:00.000Z",
          "key": 1448924400000, 
          "doc_count": 330
        }, ...

For most visualizations, you only need the list of bucket values. To focus on only the data you need, use format: {property: "aggregations.time_buckets.buckets"}.

Specify a query with individual range and dashboard context. The query is equivalent to "%context%": true, "%timefield%": "@timestamp", except that the time range is shifted back by 10 minutes:

{
  body: {
    query: {
      bool: {
        must: [
          // This string will be replaced
          // with the auto-generated "MUST" clause
          "%dashboard_context-must_clause%"
          {
            range: {
              // apply timefilter (upper right corner)
              // to the @timestamp variable
              @timestamp: {
                // "%timefilter%" will be replaced with
                // the current values of the time filter
                // (from the upper right corner)
                "%timefilter%": true
                // Only work with %timefilter%
                // Shift current timefilter by 10 units back
                shift: 10
                // week, day (default), hour, minute, second
                unit: minute
              }
            }
          }
        ]
        must_not: [
          // This string will be replaced with
          // the auto-generated "MUST-NOT" clause
          "%dashboard_context-must_not_clause%"
        ]
        filter: [
          // This string will be replaced
          // with the auto-generated "FILTER" clause
          "%dashboard_context-filter_clause%"
        ]
      }
    }
  }
}

The "%timefilter%" can also be used to specify a single min or max value. The date_histogram’s extended_bounds can be set with two values - min and max. Instead of hardcoding a value, you may use "min": {"%timefilter%": "min"}, which will be replaced with the beginning of the current time range. The shift and unit values are also supported. The "interval" can also be set dynamically, depending on the currently picked range: "interval": {"%autointerval%": 10} will try to get about 10-15 data points (buckets).

[preview] This 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. Access the Elastic Map Service files via the same mechanism:

url: {
  // "type" defaults to "elasticsearch" otherwise
  type: emsfile
  // Name of the file, exactly as in the Region map visualization
  name: World Countries
}
// The result is a geojson file, get its features to use
// this data source with the "shape" marks
// https://vega.github.io/vega/docs/marks/shape/
format: {property: "features"}

To enable Maps, the graph must specify type=map in the host configuration:

{
  "config": {
    "kibana": {
      "type": "map",

      // Initial map position
      "latitude": 40.7,   // default 0
      "longitude": -74,   // default 0
      "zoom": 7,          // default 2

      // defaults to "default". Use false to disable base layer.
      "mapStyle": false,

      // default 0
      "minZoom": 5,

      // defaults to the maximum for the given style,
      // or 25 when base is disabled
      "maxZoom": 13,

      // defaults to true, shows +/- buttons to zoom in/out
      "zoomControl": false,

      // Defaults to 'false', disables mouse wheel zoom. If set to
      // 'true', map may zoom unexpectedly while scrolling dashboard
      "scrollWheelZoom": false,

      // When false, repaints on each move frame.
      // Makes the graph slower when moving the map
      "delayRepaint": true, // default true
    }
  },
  /* the rest of Vega JSON */
}

The visualization automatically injects a "projection", which you can use to calculate the position of all geo-aware marks. Additionally, you can use latitude, longitude, and zoom signals. These signals can be used in the graph, or can be updated to modify the position of the map.

Kibana has installed the Vega tooltip plugin, so tooltips can be defined in the ways documented there. Beyond that, Kibana also supports a configuration option for changing the tooltip position and padding:

{
  config: {
    kibana: {
      tooltips: {
        position: 'top',
        padding: 15
      }
    }
  }
}

Vega can load data from any URL, but this is disabled by default in Kibana. To change this, set vis_type_vega.enableExternalUrls: true in kibana.yml, then restart Kibana.

[preview] This 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. Use browser debugging tools (for example, F12 or Ctrl+Shift+J in Chrome) to inspect the VEGA_DEBUG variable:

[preview] This 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. If you are using an Elasticsearch query, make sure your resulting data is what you expected. The easiest way to view it is by using the "networking" tab in the browser debugging tools (for example, F12). Modify the graph slightly so that it makes a search request, and view the response from the server. Another approach is to use Dev Tools. Place the index name into the first line: GET <INDEX_NAME>/_search, then add your query as the following lines (just the value of the "query" field).

Because of the dynamic nature of the data in Elasticsearch, it is hard to help you with Vega specs unless you can share a dataset. To do this, use the browser developer tools and type:

JSON.stringify(VEGA_DEBUG.vegalite_spec, null, 2)

Copy the response to gist.github.com, possibly with a .json extension, use the [raw] button, and share that when asking for help.

Kibana has extended the Vega expression language with these functions:

/**
  * @param {object} query Elastic Query DSL snippet, as used in the query DSL editor
  * @param {string} [index] as defined in Kibana, or default if missing
  */
kibanaAddFilter(query, index)

/**
  * @param {object} query Elastic Query DSL snippet, as used in the query DSL editor
  * @param {string} [index] as defined in Kibana, or default if missing
  */
kibanaRemoveFilter(query, index)

kibanaRemoveAllFilters()

/**
  * Update dashboard time filter to the new values
  * @param {number|string|Date} start
  * @param {number|string|Date} end
  */
kibanaSetTimeFilter(start, end)

{
  config: {
    kibana: {
      // Placement of the Vega-defined signal bindings.
      // Can be `left`, `right`, `top`, or `bottom` (default).
      controlsLocation: top
      // Can be `vertical` or `horizontal` (default).
      controlsDirection: vertical
      // If true, hides most of Vega and Vega-Lite warnings
      hideWarnings: true
      // Vega renderer to use: `svg` or `canvas` (default)
      renderer: canvas
    }
  }
}