> ## Documentation Index > Fetch the complete documentation index at: https://docs.domino.ai/llms.txt > Use this file to discover all available pages before exploring further. # Update run > Update run metadata. ## OpenAPI ````yaml /api-specs/cloud/public-api.json post /api/2.0/mlflow/runs/update openapi: 3.0.3 info: title: Domino Public API description: Reference for Domino's public REST API endpoints. version: 6.4.0 x-catalog-key: nucleus servers: - url: https://mycluster.domino.tech description: >- Replace 'mycluster.domino.tech' with your Domino cluster hostname. For Domino Cloud customers, that is `your-subdomain`.domino.tech (e.g., acme.domino.tech). For self-hosted deployments, it is the hostname you reach the Domino UI at. security: [] tags: - name: Projects - name: Project templates - name: Workspaces - name: Jobs - name: HPC Jobs - name: Environments - name: Hardware Tiers - name: Datasets - name: Data Sources - name: GenAI - name: AI Systems - name: MLflow experiments and runs - name: MLflow models - name: MLflow artifacts - name: MLflow traces - name: Apps - name: App versions - name: App instances - name: Model APIs - name: Registered models - name: Model deployment - name: Extensions - name: Cost and billing - name: Users and organizations - name: Service accounts - name: Personal Access Tokens - name: Personal Access Tokens (admin) - name: Audit Trail - name: Custom metrics - name: PPM - name: Model Monitoring models - name: Model Monitoring drift and quality - name: Model Monitoring settings - name: Model Monitoring authentication - name: Governance bundles - name: Governance policies - name: Governance evidence and results - name: Governance operations - name: NetApp Volumes - name: NetApp Volumes snapshots - name: NetApp Volumes filesystems - name: NetApp Volumes transfers - name: Tags - name: Properties externalDocs: description: OpenAPI url: https://swagger.io/resources/open-api/ paths: /api/2.0/mlflow/runs/update: post: tags: - MLflow experiments and runs description: Update run metadata. operationId: runs.Update requestBody: content: application/json: schema: $ref: '#/components/schemas/mlflow-proxy_UpdateRunRequest' responses: '200': description: Run updated successfully content: application/json: schema: $ref: '#/components/schemas/mlflow-proxy_UpdateRunResponse' default: $ref: '#/components/responses/mlflow-proxy_MLflowNativeError' components: schemas: mlflow-proxy_UpdateRunRequest: properties: end_time: description: Unix timestamp in milliseconds of when the run ended. oneOf: - format: int64 type: integer - type: string run_id: description: ID of the run to update. Must be provided. type: string run_name: description: Updated name of the run. type: string status: description: Updated status of the run. enum: - RUNNING - SCHEDULED - FINISHED - FAILED - KILLED type: string required: - run_id type: object mlflow-proxy_UpdateRunResponse: properties: run_info: $ref: '#/components/schemas/mlflow-proxy_RunInfo' required: - run_info type: object mlflow-proxy_RunInfo: properties: artifact_uri: description: >- URI of the directory where artifacts should be uploaded. This can be a local path (starting with "/"), or a distributed file system (DFS) path, like ``s3://bucket/directory`` or ``dbfs:/my/directory``. If not set, the local ``./mlruns`` directory is chosen. type: string end_time: description: Unix timestamp of when the run ended in milliseconds. type: integer format: int64 experiment_id: description: The experiment ID. type: string lifecycle_stage: description: >- Current life cycle stage of the experiment : OneOf("active", "deleted") type: string run_id: description: Unique identifier for the run. type: string run_name: description: Name for the run. type: string start_time: description: Unix timestamp of when the run started in milliseconds. type: integer format: int64 status: description: Current status of the run. enum: - RUNNING - SCHEDULED - FINISHED - FAILED - KILLED type: string user_id: description: >- User who initiated the run. This field is deprecated as of MLflow 1.0, and will be removed in a future MLflow release. Use 'mlflow.user' tag instead. type: string required: - artifact_uri - experiment_id - run_name - user_id - lifecycle_stage - run_id - start_time - status type: object mlflow-proxy_ErrorResponse: properties: error_code: $ref: '#/components/schemas/mlflow-proxy_ErrorCode' message: description: Error message type: string required: - error_code - message type: object mlflow-proxy_ErrorCode: description: Error code enum: - INTERNAL_ERROR - INVALID_STATE - DATA_LOSS - NOT_IMPLEMENTED - TEMPORARILY_UNAVAILABLE - DEADLINE_EXCEEDED - CANCELLED - RESOURCE_EXHAUSTED - REQUEST_LIMIT_EXCEEDED - ABORTED - RESOURCE_CONFLICT - ALREADY_EXISTS - NOT_FOUND - ENDPOINT_NOT_FOUND - RESOURCE_DOES_NOT_EXIST - PERMISSION_DENIED - CUSTOMER_UNAUTHORIZED - UNAUTHENTICATED - BAD_REQUEST - RESOURCE_ALREADY_EXISTS - INVALID_PARAMETER_VALUE type: string responses: mlflow-proxy_MLflowNativeError: description: The client issued a bad request to the server content: application/json: schema: $ref: '#/components/schemas/mlflow-proxy_ErrorResponse' ```` ## Related topics - [Update experiment](/api-reference/mlflow-experiments-and-runs/post-api20mlflowexperimentsupdate.md) - [Update the ConfigMap](/cloud/admin/security-and-compliance/custom-certificates/update-configmap.md) - [Update model version](/api-reference/mlflow-models/patch-api20mlflowmodel-versionsupdate.md) - [Update registered model](/api-reference/mlflow-models/patch-api20mlflowregistered-modelsupdate.md)