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Updating a deployment

Updating a deployment

After you create an online or a batch deployment, you can still update your deployment details and update the assets that are associated with your deployment.

For more information, see:

Updating deployment details

You can update general deployment details, such as deployment name, description, metadata, and tags by using one of these methods:

Updating deployment details from the UI

  1. From the Deployments tab of your deployment space, click the action menu for the deployment and choose Edit settings.

  2. Update the details and then click Save.

    Tip: You can also update a deployment from the information sheet for the deployment.

Updating deployment details by using the Patch API command

Use the Watson Machine Learning API Patch command to update deployment details.

curl -X PATCH '<deployment endpoint url>/ml/v4/deployments/<deployment id>?space_id=<space id>&version=<YYYY-MM-DD>' \n--data-raw '[
    {
        "op": "<operation type>",
        "path": "<path>",
        "value": "<new value>"
    },
    {
        "op": "<operation type>",
        "path": "<path>",
        "value": "<new value>"
    }
]'

For example, to update a description for deployment:

curl -X PATCH '<deployment endpoint url>/ml/v4/deployments/<deployment_id>?space_id=<space_id>&version=<YYYY-MM-DD>' \n--data-raw '[
    {
        "op": "replace",
        "path": "/description",
        "value": "<new_description>"
    },
]'

Notes:

  • For <operation type>, use "add", "remove", or "replace".

Updating assets associated with a deployment

After you create an online or batch deployment, you can update the deployed asset from the same endpoint. For example, if you have a better performing model, you can replace the deployed model with the improved version. When the update is complete, the new model is available from the REST API endpoint.

Before you update an asset, make sure that these conditions are true:

Updating an asset from the deployment space UI

  1. From the Deployments tab of your deployment space, click the action menu for the deployment and choose Edit.
  2. Click Replace asset. From the Select an asset dialog box, select the asset that you want to replace the current asset with and click Select asset.
  3. Click Save.
Important: Make sure that the new asset is compatible with the deployment.

Replacing a deployed asset

Updating an asset by using the Patch API command

Use the Watson Machine Learning API Patch command to update any supported asset.

Use this method to patch a model for an online deployment.

curl -X PATCH '<deployment endpoint url>/ml/v4/models/<model_id>?space_id=<space_id>&project_id=<project_id>&version=<YYYY-MM-DD>' \n--data-raw '[
    {
        "op": "<operation type>",
        "path": "<path>",
        "value": "<new value>"
    },
    {
        "op": "<operation type>",
        "path": "<path>",
        "value": "<new value>"
    }
]'

For example, patch a model with ID 6f01d512-fe0f-41cd-9a52-1e200c525c84 in space ID f2ddb8ce-7b10-4846-9ab0-62454a449802:

curl -X PATCH '<deployment endpoint url>/ml/v4/models/6f01d512-fe0f-41cd-9a52-1e200c525c84?space_id=f2ddb8ce-7b10-4846-9ab0-62454a449802&project_id=<project_id>&version=<YYYY-MM-DD>' \n--data-raw '[

   {
      "op":"replace",
      "path":"/asset",
      "value":{
         "id":"6f01d512-fe0f-41cd-9a52-1e200c525c84",
         "rev":"1"
      }
   }
]'

A successful output response looks like this:

{
  "entity": {
    "asset": {
      "href": "/v4/models/6f01d512-fe0f-41cd-9a52-1e200c525c84?space_id=f2ddb8ce-7b10-4846-9ab0-62454a449802",
      "id": "6f01d512-fe0f-41cd-9a52-1e200c525c84"
    },
    "custom": {
    },
    "description": "Test V4 deployments",
    "name": "test_v4_dep_online_space_hardware_spec",
    "online": {
    },
    "space": {
      "href": "/v4/spaces/f2ddb8ce-7b10-4846-9ab0-62454a449802",
      "id": "f2ddb8ce-7b10-4846-9ab0-62454a449802"
    },
    "space_id": "f2ddb8ce-7b10-4846-9ab0-62454a449802",
    "status": {
      "online_url": {
        "url": "https://example.com/v4/deployments/349dc1f7-9452-491b-8aa4-0777f784bd83/predictions"
      },
      "state": "updating"
    }
  },
  "metadata": {
    "created_at": "2020-06-08T16:51:08.315Z",
    "description": "Test V4 deployments",
    "guid": "349dc1f7-9452-491b-8aa4-0777f784bd83",
    "href": "/v4/deployments/349dc1f7-9452-491b-8aa4-0777f784bd83",
    "id": "349dc1f7-9452-491b-8aa4-0777f784bd83",
    "modified_at": "2020-06-08T16:55:28.348Z",
    "name": "test_v4_dep_online_space_hardware_spec",
    "parent": {
      "href": ""
    },
    "space_id": "f2ddb8ce-7b10-4846-9ab0-62454a449802"
  }
}

Notes:

  • For <operation type>, use "add", "remove", or "replace".

  • The initial state for the PATCH API output is "updating". Keep polling the status until it changes to "ready", then retrieve the deployment meta.

  • Only the ASSET attribute can be specified for the asset patch. Changing any other attribute results in an error.

  • The schema of the current model and the model being patched is compared to the deployed asset. A warning message is returned in the output of the Patch request API if the two don't match. For example, if a mismatch is detected, you can find this information in the output response.

    "status": {
          "message": {
            "text": "The input schema of the asset being patched does not match with the currently deployed asset. Please ensure that the score payloads are up to date as per the asset being patched."
          },
    
  • For more information, see Updating software specifications by using the API.

Parent topic: Managing predictive deployments

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