Kibana ml API

openapi: 3.0.3
info:
  contact:
    name: Kibana Team
  description: 'The Kibana REST APIs enable you to manage resources such as connectors, data views, and saved objects.

    The API calls are stateless.

    Each request that you make happens in isolation from other calls and must include all of the necessary information for Kibana to fulfill the

    request.

    API requests return JSON output, which is a format that is machine-readable and works well for automation.


    To interact with Kibana APIs, use the following operations:


    - GET: Fetches the information.

    - PATCH: Applies partial modifications to the existing information.

    - POST: Adds new information.

    - PUT: Updates the existing information.

    - DELETE: Removes the information.


    You can prepend any Kibana API endpoint with `kbn:` and run the request in **Dev Tools → Console**.

    For example:


    ```

    GET kbn:/api/data_views

    ```


    For more information about the console, refer to [Run API requests](https://www.elastic.co/docs/explore-analyze/query-filter/tools/console).


    NOTE: Access to internal Kibana API endpoints will be restricted in Kibana version 9.0. Please move any integrations to publicly documented APIs.


    ## Documentation source and versions


    This documentation is derived from the `main` branch of the [kibana](https://github.com/elastic/kibana) repository.

    It is provided under license [Attribution-NonCommercial-NoDerivatives 4.0 International](https://creativecommons.org/licenses/by-nc-nd/4.0/).


    This documentation contains work-in-progress information for future Elastic Stack releases.

    '
  title: Kibana APIs Actions ml API
  version: ''
  x-doc-license:
    name: Attribution-NonCommercial-NoDerivatives 4.0 International
    url: https://creativecommons.org/licenses/by-nc-nd/4.0/
  x-feedbackLink:
    label: Feedback
    url: https://github.com/elastic/docs-content/issues/new?assignees=&labels=feedback%2Ccommunity&projects=&template=api-feedback.yaml&title=%5BFeedback%5D%3A+
servers:
- url: https://{kibana_url}
  variables:
    kibana_url:
      default: localhost:5601
security:
- apiKeyAuth: []
- basicAuth: []
tags:
- description: 'Enables you to synchronize machine learning saved objects.

    '
  name: ml
  x-displayName: Machine learning
paths:
  /api/ml/saved_objects/sync:
    get:
      description: '**Spaces method and path for this operation:**


        <div><span class="operation-verb get">get</span>&nbsp;<span class="operation-path">/s/{space_id}/api/ml/saved_objects/sync</span></div>


        Refer to [Spaces](https://www.elastic.co/docs/deploy-manage/manage-spaces) for more information.


        Synchronizes Kibana saved objects for machine learning jobs and trained models in the default space. You must have `all` privileges for the **Machine Learning** feature in the **Analytics** section of the Kibana feature privileges. This API runs automatically when you start Kibana and periodically thereafter.

        '
      operationId: mlSync
      parameters:
      - $ref: '#/components/parameters/Machine_learning_APIs_simulateParam'
      responses:
        '200':
          content:
            application/json:
              examples:
                syncExample:
                  $ref: '#/components/examples/Machine_learning_APIs_mlSyncExample'
              schema:
                $ref: '#/components/schemas/Machine_learning_APIs_mlSync200Response'
          description: Indicates a successful call
        '401':
          content:
            application/json:
              examples:
                syncExample:
                  $ref: '#/components/examples/Machine_learning_APIs_mlSync401Example'
              schema:
                $ref: '#/components/schemas/Machine_learning_APIs_mlSync4xxResponse'
          description: Authorization information is missing or invalid.
      summary: Sync saved objects in the default space
      tags:
      - ml
      x-metaTags:
      - content: Kibana
        name: product_name
  /api/ml/saved_objects/update_jobs_spaces:
    post:
      description: '**Spaces method and path for this operation:**


        <div><span class="operation-verb post">post</span>&nbsp;<span class="operation-path">/s/{space_id}/api/ml/saved_objects/update_jobs_spaces</span></div>


        Refer to [Spaces](https://www.elastic.co/docs/deploy-manage/manage-spaces) for more information.


        Update a list of jobs to add and/or remove them from given spaces.'
      operationId: mlUpdateJobsSpaces
      requestBody:
        content:
          application/json:
            examples:
              updateADJobSpacesRequest:
                value:
                  jobIds:
                  - test-job
                  jobType: anomaly-detector
                  spacesToAdd:
                  - default
                  spacesToRemove:
                  - '*'
              updateDFAJobSpacesRequest:
                value:
                  jobIds:
                  - test-job
                  jobType: data-frame-analytics
                  spacesToAdd:
                  - default
                  spacesToRemove:
                  - '*'
      responses:
        '200':
          content:
            application/json:
              examples:
                successADResponse:
                  value:
                    test-job:
                      success: true
                      type: anomaly-detector
                successDFAResponse:
                  value:
                    test-job:
                      success: true
                      type: data-frame-analytics
          description: Indicates a successful call
      summary: Update jobs spaces
      tags:
      - ml
      x-metaTags:
      - content: Kibana
        name: product_name
  /api/ml/saved_objects/update_trained_models_spaces:
    post:
      description: '**Spaces method and path for this operation:**


        <div><span class="operation-verb post">post</span>&nbsp;<span class="operation-path">/s/{space_id}/api/ml/saved_objects/update_trained_models_spaces</span></div>


        Refer to [Spaces](https://www.elastic.co/docs/deploy-manage/manage-spaces) for more information.


        Update a list of trained models to add and/or remove them from given spaces.'
      operationId: mlUpdateTrainedModelsSpaces
      requestBody:
        content:
          application/json:
            examples:
              updateTrainedModelsSpacesRequest:
                value:
                  modelIds:
                  - test-model
                  spacesToAdd:
                  - default
                  spacesToRemove:
                  - '*'
      responses:
        '200':
          content:
            application/json:
              examples:
                successTMResponse:
                  value:
                    test-model:
                      success: true
                      type: trained-model"
          description: Indicates a successful call
      summary: Update trained models spaces
      tags:
      - ml
      x-metaTags:
      - content: Kibana
        name: product_name
components:
  schemas:
    Machine_learning_APIs_mlSyncResponseSuccess:
      description: The success or failure of the synchronization.
      type: boolean
    Machine_learning_APIs_mlSync200Response:
      properties:
        datafeedsAdded:
          additionalProperties:
            $ref: '#/components/schemas/Machine_learning_APIs_mlSyncResponseDatafeeds'
          description: If a saved object for an anomaly detection job is missing a datafeed identifier, it is added when you run the sync machine learning saved objects API.
          type: object
        datafeedsRemoved:
          additionalProperties:
            $ref: '#/components/schemas/Machine_learning_APIs_mlSyncResponseDatafeeds'
          description: If a saved object for an anomaly detection job references a datafeed that no longer exists, it is deleted when you run the sync machine learning saved objects API.
          type: object
        savedObjectsCreated:
          $ref: '#/components/schemas/Machine_learning_APIs_mlSyncResponseSavedObjectsCreated'
        savedObjectsDeleted:
          $ref: '#/components/schemas/Machine_learning_APIs_mlSyncResponseSavedObjectsDeleted'
      title: Successful sync API response
      type: object
    Machine_learning_APIs_mlSync4xxResponse:
      properties:
        error:
          example: Unauthorized
          type: string
        message:
          type: string
        statusCode:
          example: 401
          type: integer
      title: Unsuccessful sync API response
      type: object
    Machine_learning_APIs_mlSyncResponseTrainedModels:
      description: The sync machine learning saved objects API response contains this object when there are trained models affected by the synchronization. There is an object for each relevant trained model, which contains the synchronization status.
      properties:
        success:
          $ref: '#/components/schemas/Machine_learning_APIs_mlSyncResponseSuccess'
      title: Sync API response for trained models
      type: object
    Machine_learning_APIs_mlSyncResponseDataFrameAnalytics:
      description: The sync machine learning saved objects API response contains this object when there are data frame analytics jobs affected by the synchronization. There is an object for each relevant job, which contains the synchronization status.
      properties:
        success:
          $ref: '#/components/schemas/Machine_learning_APIs_mlSyncResponseSuccess'
      title: Sync API response for data frame analytics jobs
      type: object
    Machine_learning_APIs_mlSyncResponseDatafeeds:
      description: The sync machine learning saved objects API response contains this object when there are datafeeds affected by the synchronization. There is an object for each relevant datafeed, which contains the synchronization status.
      properties:
        success:
          $ref: '#/components/schemas/Machine_learning_APIs_mlSyncResponseSuccess'
      title: Sync API response for datafeeds
      type: object
    Machine_learning_APIs_mlSyncResponseSavedObjectsCreated:
      description: If saved objects are missing for machine learning jobs or trained models, they are created when you run the sync machine learning saved objects API.
      properties:
        anomaly-detector:
          additionalProperties:
            $ref: '#/components/schemas/Machine_learning_APIs_mlSyncResponseAnomalyDetectors'
          description: If saved objects are missing for anomaly detection jobs, they are created.
          type: object
        data-frame-analytics:
          additionalProperties:
            $ref: '#/components/schemas/Machine_learning_APIs_mlSyncResponseDataFrameAnalytics'
          description: If saved objects are missing for data frame analytics jobs, they are created.
          type: object
        trained-model:
          additionalProperties:
            $ref: '#/components/schemas/Machine_learning_APIs_mlSyncResponseTrainedModels'
          description: If saved objects are missing for trained models, they are created.
          type: object
      title: Sync API response for created saved objects
      type: object
    Machine_learning_APIs_mlSyncResponseAnomalyDetectors:
      description: The sync machine learning saved objects API response contains this object when there are anomaly detection jobs affected by the synchronization. There is an object for each relevant job, which contains the synchronization status.
      properties:
        success:
          $ref: '#/components/schemas/Machine_learning_APIs_mlSyncResponseSuccess'
      title: Sync API response for anomaly detection jobs
      type: object
    Machine_learning_APIs_mlSyncResponseSavedObjectsDeleted:
      description: If saved objects exist for machine learning jobs or trained models that no longer exist, they are deleted when you run the sync machine learning saved objects API.
      properties:
        anomaly-detector:
          additionalProperties:
            $ref: '#/components/schemas/Machine_learning_APIs_mlSyncResponseAnomalyDetectors'
          description: If there are saved objects exist for nonexistent anomaly detection jobs, they are deleted.
          type: object
        data-frame-analytics:
          additionalProperties:
            $ref: '#/components/schemas/Machine_learning_APIs_mlSyncResponseDataFrameAnalytics'
          description: If there are saved objects exist for nonexistent data frame analytics jobs, they are deleted.
          type: object
        trained-model:
          additionalProperties:
            $ref: '#/components/schemas/Machine_learning_APIs_mlSyncResponseTrainedModels'
          description: If there are saved objects exist for nonexistent trained models, they are deleted.
          type: object
      title: Sync API response for deleted saved objects
      type: object
  examples:
    Machine_learning_APIs_mlSyncExample:
      summary: Two anomaly detection jobs required synchronization in this example.
      value:
        datafeedsAdded: {}
        datafeedsRemoved: {}
        savedObjectsCreated:
          anomaly-detector:
            myjob1:
              success: true
            myjob2:
              success: true
        savedObjectsDeleted: {}
    Machine_learning_APIs_mlSync401Example:
      summary: Two anomaly detection jobs required synchronization in this example.
      value:
        error: Unauthorized
        message: "[security_exception\n\tRoot causes:\n\t\tsecurity_exception: unable to authenticate user [ml_viewer] for REST request [/_security/_authenticate]]: unable to authenticate user [ml_viewer] for REST request [/_security/_authenticate]"
        statusCode: 401
  parameters:
    Machine_learning_APIs_simulateParam:
      description: When true, simulates the synchronization by returning only the list of actions that would be performed.
      example: 'true'
      in: query
      name: simulate
      required: false
      schema:
        type: boolean
  securitySchemes:
    apiKeyAuth:
      description: 'These APIs use key-based authentication. You must create an API key and use the encoded value in the request header. For example: `Authorization: ApiKey base64AccessApiKey`

        '
      in: header
      name: Authorization
      type: apiKey
    basicAuth:
      scheme: basic
      type: http
x-topics:
- title: Kibana spaces
  content: "Spaces enable you to organize your dashboards and other saved objects into meaningful categories.\nYou can use the default space or create your own spaces.\n\nTo run APIs in non-default spaces, you must add `s/{space_id}/` to the path.\nFor example:\n\n```bash\ncurl -X GET \"http://${KIBANA_URL}/s/marketing/api/data_views\" \\\n  -H \"Authorization: ApiKey ${API_KEY}\"\n```\n\nIf you use the Kibana console to send API requests, it automatically adds the appropriate space identifier.\n\nTo learn more, check out [Spaces](https://www.elastic.co/docs/deploy-manage/manage-spaces).\n"