Update an anomaly detection job Generally available; Added in 5.5.0

POST /_ml/anomaly_detectors/{job_id}/_update

Updates certain properties of an anomaly detection job.

Required authorization

  • Cluster privileges: manage_ml

Path parameters

  • job_id string Required

    Identifier for the job.

application/json

Body Required

  • allow_lazy_open boolean

    Advanced configuration option. Specifies whether this job can open when there is insufficient machine learning node capacity for it to be immediately assigned to a node. If false and a machine learning node with capacity to run the job cannot immediately be found, the open anomaly detection jobs API returns an error. However, this is also subject to the cluster-wide xpack.ml.max_lazy_ml_nodes setting. If this option is set to true, the open anomaly detection jobs API does not return an error and the job waits in the opening state until sufficient machine learning node capacity is available.

  • analysis_limits object
    Hide analysis_limits attribute Show analysis_limits attribute object
    • model_memory_limit string Required

      Limits can be applied for the resources required to hold the mathematical models in memory. These limits are approximate and can be set per job. They do not control the memory used by other processes, for example the Elasticsearch Java processes.

  • background_persist_interval string

    A duration. Units can be nanos, micros, ms (milliseconds), s (seconds), m (minutes), h (hours) and d (days). Also accepts "0" without a unit and "-1" to indicate an unspecified value.

  • custom_settings object

    Advanced configuration option. Contains custom meta data about the job. For example, it can contain custom URL information as shown in Adding custom URLs to machine learning results.

    Hide custom_settings attribute Show custom_settings attribute object
    • * object Additional properties
  • categorization_filters array[string]
  • description string

    A description of the job.

  • model_plot_config object
    Hide model_plot_config attributes Show model_plot_config attributes object
    • annotations_enabled boolean Generally available; Added in 7.9.0

      If true, enables calculation and storage of the model change annotations for each entity that is being analyzed.

    • enabled boolean

      If true, enables calculation and storage of the model bounds for each entity that is being analyzed.

    • terms string

      Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

  • model_prune_window string

    A duration. Units can be nanos, micros, ms (milliseconds), s (seconds), m (minutes), h (hours) and d (days). Also accepts "0" without a unit and "-1" to indicate an unspecified value.

  • daily_model_snapshot_retention_after_days number

    Advanced configuration option, which affects the automatic removal of old model snapshots for this job. It specifies a period of time (in days) after which only the first snapshot per day is retained. This period is relative to the timestamp of the most recent snapshot for this job. Valid values range from 0 to model_snapshot_retention_days. For jobs created before version 7.8.0, the default value matches model_snapshot_retention_days.

  • model_snapshot_retention_days number

    Advanced configuration option, which affects the automatic removal of old model snapshots for this job. It specifies the maximum period of time (in days) that snapshots are retained. This period is relative to the timestamp of the most recent snapshot for this job.

  • renormalization_window_days number

    Advanced configuration option. The period over which adjustments to the score are applied, as new data is seen.

  • results_retention_days number

    Advanced configuration option. The period of time (in days) that results are retained. Age is calculated relative to the timestamp of the latest bucket result. If this property has a non-null value, once per day at 00:30 (server time), results that are the specified number of days older than the latest bucket result are deleted from Elasticsearch. The default value is null, which means all results are retained.

  • groups array[string]

    A list of job groups. A job can belong to no groups or many.

  • detectors array[object]

    An array of detector update objects.

    Hide detectors attributes Show detectors attributes object
    • detector_index number Required

      A unique identifier for the detector. This identifier is based on the order of the detectors in the analysis_config, starting at zero.

    • description string

      A description of the detector.

    • custom_rules array[object]

      An array of custom rule objects, which enable you to customize the way detectors operate. For example, a rule may dictate to the detector conditions under which results should be skipped. Kibana refers to custom rules as job rules.

      Hide custom_rules attributes Show custom_rules attributes object
      • actions array[string]

        The set of actions to be triggered when the rule applies. If more than one action is specified the effects of all actions are combined.

        Values are skip_result or skip_model_update.

      • conditions array[object]

        An array of numeric conditions when the rule applies. A rule must either have a non-empty scope or at least one condition. Multiple conditions are combined together with a logical AND.

        Hide conditions attributes Show conditions attributes object
        • applies_to string Required

          Values are actual, typical, diff_from_typical, or time.

        • operator string Required

          Values are gt, gte, lt, or lte.

        • value number Required

          The value that is compared against the applies_to field using the operator.

      • scope object

        A scope of series where the rule applies. A rule must either have a non-empty scope or at least one condition. By default, the scope includes all series. Scoping is allowed for any of the fields that are also specified in by_field_name, over_field_name, or partition_field_name.

        Hide scope attribute Show scope attribute object
        • * object Additional properties
          Hide * attributes Show * attributes object
          • filter_id string Required
          • filter_type string

            Values are include or exclude.

  • per_partition_categorization object
    Hide per_partition_categorization attributes Show per_partition_categorization attributes object
    • enabled boolean

      To enable this setting, you must also set the partition_field_name property to the same value in every detector that uses the keyword mlcategory. Otherwise, job creation fails.

    • stop_on_warn boolean

      This setting can be set to true only if per-partition categorization is enabled. If true, both categorization and subsequent anomaly detection stops for partitions where the categorization status changes to warn. This setting makes it viable to have a job where it is expected that categorization works well for some partitions but not others; you do not pay the cost of bad categorization forever in the partitions where it works badly.

Responses

  • 200 application/json
    Hide response attributes Show response attributes object
    • allow_lazy_open boolean Required
    • analysis_config object Required
      Hide analysis_config attributes Show analysis_config attributes object
      • bucket_span string Required

        A duration. Units can be nanos, micros, ms (milliseconds), s (seconds), m (minutes), h (hours) and d (days). Also accepts "0" without a unit and "-1" to indicate an unspecified value.

      • categorization_analyzer string | object

        One of:
      • categorization_field_name string

        Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

      • categorization_filters array[string]

        If categorization_field_name is specified, you can also define optional filters. This property expects an array of regular expressions. The expressions are used to filter out matching sequences from the categorization field values.

      • detectors array[object] Required

        An array of detector configuration objects. Detector configuration objects specify which data fields a job analyzes. They also specify which analytical functions are used. You can specify multiple detectors for a job.

        Hide detectors attributes Show detectors attributes object
        • by_field_name string

          Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

        • custom_rules array[object]

          An array of custom rule objects, which enable you to customize the way detectors operate. For example, a rule may dictate to the detector conditions under which results should be skipped. Kibana refers to custom rules as job rules.

          Hide custom_rules attributes Show custom_rules attributes object
          • actions array[string]

            The set of actions to be triggered when the rule applies. If more than one action is specified the effects of all actions are combined.

            Values are skip_result or skip_model_update.

          • conditions array[object]

            An array of numeric conditions when the rule applies. A rule must either have a non-empty scope or at least one condition. Multiple conditions are combined together with a logical AND.

          • scope object

            A scope of series where the rule applies. A rule must either have a non-empty scope or at least one condition. By default, the scope includes all series. Scoping is allowed for any of the fields that are also specified in by_field_name, over_field_name, or partition_field_name.

        • detector_description string

          A description of the detector.

        • detector_index number

          A unique identifier for the detector. This identifier is based on the order of the detectors in the analysis_config, starting at zero.

        • exclude_frequent string

          Values are all, none, by, or over.

        • field_name string

          Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

        • function string Required

          The analysis function that is used. For example, count, rare, mean, min, max, and sum.

        • over_field_name string

          Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

        • partition_field_name string

          Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

        • use_null boolean

          Defines whether a new series is used as the null series when there is no value for the by or partition fields.

      • influencers array[string] Required

        A comma separated list of influencer field names. Typically these can be the by, over, or partition fields that are used in the detector configuration. You might also want to use a field name that is not specifically named in a detector, but is available as part of the input data. When you use multiple detectors, the use of influencers is recommended as it aggregates results for each influencer entity.

      • model_prune_window string

        A duration. Units can be nanos, micros, ms (milliseconds), s (seconds), m (minutes), h (hours) and d (days). Also accepts "0" without a unit and "-1" to indicate an unspecified value.

      • latency string

        A duration. Units can be nanos, micros, ms (milliseconds), s (seconds), m (minutes), h (hours) and d (days). Also accepts "0" without a unit and "-1" to indicate an unspecified value.

      • multivariate_by_fields boolean

        This functionality is reserved for internal use. It is not supported for use in customer environments and is not subject to the support SLA of official GA features. If set to true, the analysis will automatically find correlations between metrics for a given by field value and report anomalies when those correlations cease to hold.

      • per_partition_categorization object
        Hide per_partition_categorization attributes Show per_partition_categorization attributes object
        • enabled boolean

          To enable this setting, you must also set the partition_field_name property to the same value in every detector that uses the keyword mlcategory. Otherwise, job creation fails.

        • stop_on_warn boolean

          This setting can be set to true only if per-partition categorization is enabled. If true, both categorization and subsequent anomaly detection stops for partitions where the categorization status changes to warn. This setting makes it viable to have a job where it is expected that categorization works well for some partitions but not others; you do not pay the cost of bad categorization forever in the partitions where it works badly.

      • summary_count_field_name string

        Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

    • analysis_limits object Required
      Hide analysis_limits attributes Show analysis_limits attributes object
      • categorization_examples_limit number

        The maximum number of examples stored per category in memory and in the results data store. If you increase this value, more examples are available, however it requires that you have more storage available. If you set this value to 0, no examples are stored. NOTE: The categorization_examples_limit applies only to analysis that uses categorization.

      • model_memory_limit number | string

    • background_persist_interval string

      A duration. Units can be nanos, micros, ms (milliseconds), s (seconds), m (minutes), h (hours) and d (days). Also accepts "0" without a unit and "-1" to indicate an unspecified value.

    • create_time number

      Time unit for milliseconds

    • finished_time number

      Time unit for milliseconds

    • custom_settings object
      Hide custom_settings attribute Show custom_settings attribute object
      • * string Additional properties
    • daily_model_snapshot_retention_after_days number Required
    • data_description object Required
      Hide data_description attributes Show data_description attributes object
      • format string

        Only JSON format is supported at this time.

      • time_field string

        Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

      • time_format string

        The time format, which can be epoch, epoch_ms, or a custom pattern. The value epoch refers to UNIX or Epoch time (the number of seconds since 1 Jan 1970). The value epoch_ms indicates that time is measured in milliseconds since the epoch. The epoch and epoch_ms time formats accept either integer or real values. Custom patterns must conform to the Java DateTimeFormatter class. When you use date-time formatting patterns, it is recommended that you provide the full date, time and time zone. For example: yyyy-MM-dd'T'HH:mm:ssX. If the pattern that you specify is not sufficient to produce a complete timestamp, job creation fails.

      • field_delimiter string
    • datafeed_config object
      Hide datafeed_config attributes Show datafeed_config attributes object
      • aggregations object
      • authorization object
        Hide authorization attributes Show authorization attributes object
        • api_key object
          Hide api_key attributes Show api_key attributes object
          • id string Required

            The identifier for the API key.

          • name string Required

            The name of the API key.

        • roles array[string]

          If a user ID was used for the most recent update to the datafeed, its roles at the time of the update are listed in the response.

        • service_account string

          If a service account was used for the most recent update to the datafeed, the account name is listed in the response.

      • chunking_config object
        Hide chunking_config attributes Show chunking_config attributes object
        • mode string Required

          Values are auto, manual, or off.

        • time_span string

          A duration. Units can be nanos, micros, ms (milliseconds), s (seconds), m (minutes), h (hours) and d (days). Also accepts "0" without a unit and "-1" to indicate an unspecified value.

      • datafeed_id string Required
      • frequency string

        A duration. Units can be nanos, micros, ms (milliseconds), s (seconds), m (minutes), h (hours) and d (days). Also accepts "0" without a unit and "-1" to indicate an unspecified value.

      • indices array[string] Required
      • indexes array[string]
      • job_id string Required
      • max_empty_searches number
      • query_delay string

        A duration. Units can be nanos, micros, ms (milliseconds), s (seconds), m (minutes), h (hours) and d (days). Also accepts "0" without a unit and "-1" to indicate an unspecified value.

      • script_fields object
        Hide script_fields attribute Show script_fields attribute object
        • * object Additional properties
          Hide * attributes Show * attributes object
          • script object Required
            Hide script attributes Show script attributes object
            • id string
            • params object

              Specifies any named parameters that are passed into the script as variables. Use parameters instead of hard-coded values to decrease compile time.

              Hide params attribute Show params attribute object
              • * object Additional properties
            • lang string

              Any of:

              Values are painless, expression, mustache, or java.

            • options object
              Hide options attribute Show options attribute object
              • * string Additional properties
          • ignore_failure boolean
      • scroll_size number
      • delayed_data_check_config object Required
        Hide delayed_data_check_config attributes Show delayed_data_check_config attributes object
        • check_window string

          A duration. Units can be nanos, micros, ms (milliseconds), s (seconds), m (minutes), h (hours) and d (days). Also accepts "0" without a unit and "-1" to indicate an unspecified value.

        • enabled boolean Required

          Specifies whether the datafeed periodically checks for delayed data.

      • runtime_mappings object
        Hide runtime_mappings attribute Show runtime_mappings attribute object
        • * object Additional properties
          Hide * attributes Show * attributes object
          • fields object

            For type composite

            Hide fields attribute Show fields attribute object
            • * object Additional properties
              Hide * attribute Show * attribute object
              • type string Required

                Values are boolean, composite, date, double, geo_point, geo_shape, ip, keyword, long, or lookup.

          • fetch_fields array[object]

            For type lookup

            Hide fetch_fields attributes Show fetch_fields attributes object
            • field string Required

              Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

            • format string
          • format string

            A custom format for date type runtime fields.

          • input_field string

            Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

          • target_field string

            Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

          • target_index string
          • script object
            Hide script attributes Show script attributes object
            • id string
            • params object

              Specifies any named parameters that are passed into the script as variables. Use parameters instead of hard-coded values to decrease compile time.

              Hide params attribute Show params attribute object
              • * object Additional properties
            • lang string

              Any of:

              Values are painless, expression, mustache, or java.

            • options object
              Hide options attribute Show options attribute object
              • * string Additional properties
          • type string Required

            Values are boolean, composite, date, double, geo_point, geo_shape, ip, keyword, long, or lookup.

      • indices_options object

        Controls how to deal with unavailable concrete indices (closed or missing), how wildcard expressions are expanded to actual indices (all, closed or open indices) and how to deal with wildcard expressions that resolve to no indices.

        Hide indices_options attributes Show indices_options attributes object
        • allow_no_indices boolean

          If false, the request returns an error if any wildcard expression, index alias, or _all value targets only missing or closed indices. This behavior applies even if the request targets other open indices. For example, a request targeting foo*,bar* returns an error if an index starts with foo but no index starts with bar.

        • expand_wildcards string | array[string]
        • ignore_unavailable boolean

          If true, missing or closed indices are not included in the response.

        • ignore_throttled boolean

          If true, concrete, expanded or aliased indices are ignored when frozen.

      • query object Required

        The Elasticsearch query domain-specific language (DSL). This value corresponds to the query object in an Elasticsearch search POST body. All the options that are supported by Elasticsearch can be used, as this object is passed verbatim to Elasticsearch. By default, this property has the following value: {"match_all": {"boost": 1}}.

        Query DSL
    • description string
    • groups array[string]
    • job_id string Required
    • job_type string Required
    • job_version string Required
    • model_plot_config object
      Hide model_plot_config attributes Show model_plot_config attributes object
      • annotations_enabled boolean Generally available; Added in 7.9.0

        If true, enables calculation and storage of the model change annotations for each entity that is being analyzed.

      • enabled boolean

        If true, enables calculation and storage of the model bounds for each entity that is being analyzed.

      • terms string

        Path to field or array of paths. Some API's support wildcards in the path to select multiple fields.

    • model_snapshot_id string
    • model_snapshot_retention_days number Required
    • renormalization_window_days number
    • results_index_name string Required
    • results_retention_days number
POST /_ml/anomaly_detectors/{job_id}/_update
POST _ml/anomaly_detectors/low_request_rate/_update
{
  "description":"An updated job",
  "detectors": {
    "detector_index": 0,
    "description": "An updated detector description"
  },
  "groups": ["kibana_sample_data","kibana_sample_web_logs"],
  "model_plot_config": {
    "enabled": true
  },
  "renormalization_window_days": 30,
  "background_persist_interval": "2h",
  "model_snapshot_retention_days": 7,
  "results_retention_days": 60
}
resp = client.ml.update_job(
    job_id="low_request_rate",
    description="An updated job",
    detectors={
        "detector_index": 0,
        "description": "An updated detector description"
    },
    groups=[
        "kibana_sample_data",
        "kibana_sample_web_logs"
    ],
    model_plot_config={
        "enabled": True
    },
    renormalization_window_days=30,
    background_persist_interval="2h",
    model_snapshot_retention_days=7,
    results_retention_days=60,
)
const response = await client.ml.updateJob({
  job_id: "low_request_rate",
  description: "An updated job",
  detectors: {
    detector_index: 0,
    description: "An updated detector description",
  },
  groups: ["kibana_sample_data", "kibana_sample_web_logs"],
  model_plot_config: {
    enabled: true,
  },
  renormalization_window_days: 30,
  background_persist_interval: "2h",
  model_snapshot_retention_days: 7,
  results_retention_days: 60,
});
response = client.ml.update_job(
  job_id: "low_request_rate",
  body: {
    "description": "An updated job",
    "detectors": {
      "detector_index": 0,
      "description": "An updated detector description"
    },
    "groups": [
      "kibana_sample_data",
      "kibana_sample_web_logs"
    ],
    "model_plot_config": {
      "enabled": true
    },
    "renormalization_window_days": 30,
    "background_persist_interval": "2h",
    "model_snapshot_retention_days": 7,
    "results_retention_days": 60
  }
)
$resp = $client->ml()->updateJob([
    "job_id" => "low_request_rate",
    "body" => [
        "description" => "An updated job",
        "detectors" => [
            "detector_index" => 0,
            "description" => "An updated detector description",
        ],
        "groups" => array(
            "kibana_sample_data",
            "kibana_sample_web_logs",
        ),
        "model_plot_config" => [
            "enabled" => true,
        ],
        "renormalization_window_days" => 30,
        "background_persist_interval" => "2h",
        "model_snapshot_retention_days" => 7,
        "results_retention_days" => 60,
    ],
]);
curl -X POST -H "Authorization: ApiKey $ELASTIC_API_KEY" -H "Content-Type: application/json" -d '{"description":"An updated job","detectors":{"detector_index":0,"description":"An updated detector description"},"groups":["kibana_sample_data","kibana_sample_web_logs"],"model_plot_config":{"enabled":true},"renormalization_window_days":30,"background_persist_interval":"2h","model_snapshot_retention_days":7,"results_retention_days":60}' "$ELASTICSEARCH_URL/_ml/anomaly_detectors/low_request_rate/_update"
Request example
An example body for a `POST _ml/anomaly_detectors/low_request_rate/_update` request.
{
  "description":"An updated job",
  "detectors": {
    "detector_index": 0,
    "description": "An updated detector description"
  },
  "groups": ["kibana_sample_data","kibana_sample_web_logs"],
  "model_plot_config": {
    "enabled": true
  },
  "renormalization_window_days": 30,
  "background_persist_interval": "2h",
  "model_snapshot_retention_days": 7,
  "results_retention_days": 60
}