# Update config of a serving endpoint Launch stage: GA `PUT /api/2.0/serving-endpoints/{name}/config` Updates any combination of the serving endpoint's served entities, the compute configuration of those served entities, and the endpoint's traffic config. An endpoint that already has an update in progress can not be updated until the current update completes or fails. API scopes: model-serving ## Path parameters - `name` (string, required) The name of the serving endpoint to update. This field is required. Example: `feed-ads` Constraints: `[ 1 .. 63 ] characters` ## Request body - `served_entities` (array of object, optional) The list of served entities under the serving endpoint config. - `name` (string, optional) The name of a served entity. It must be unique across an endpoint. A served entity name can consist of alphanumeric characters, dashes, and underscores. If not specified for an external model, this field defaults to external_model.name, with '.' and ':' replaced with '-', and if not specified for other entities, it defaults to entity_name-entity_version. Example: `ads-model-3` - `external_model` (object, optional) The external model to be served. NOTE: Only one of external_model and (entity_name, entity_version, workload_size, workload_type, and scale_to_zero_enabled) can be specified with the latter set being used for custom model serving for a Databricks registered model. For an existing endpoint with external_model, it cannot be updated to an endpoint without external_model. If the endpoint is created without external_model, users cannot update it to add external_model later. The task type of all external models within an endpoint must be the same. - `provider` (string, required) The name of the provider for the external model. Currently, the supported providers are 'ai21labs', 'anthropic', 'amazon-bedrock', 'cohere', 'databricks-model-serving', 'google-cloud-vertex-ai', 'openai', 'palm', and 'custom'. - `name` (string, required) The name of the external model. Example: `gpt-4` - `task` (string, required) The task type of the external model. Example: `llm/v1/chat` - `ai21labs_config` (object, optional) AI21Labs Config. Only required if the provider is 'ai21labs'. - `ai21labs_api_key` (string, optional) The Databricks secret key reference for an AI21 Labs API key. If you prefer to paste your API key directly, see `ai21labs_api_key_plaintext`. You must provide an API key using one of the following fields: `ai21labs_api_key` or `ai21labs_api_key_plaintext`. Example: `{{secrets/my_scope/my_ai21labs_api_key}}` - `ai21labs_api_key_plaintext` (string, optional, Input only) An AI21 Labs API key provided as a plaintext string. If you prefer to reference your key using Databricks Secrets, see `ai21labs_api_key`. You must provide an API key using one of the following fields: `ai21labs_api_key` or `ai21labs_api_key_plaintext`. Example: `Your API Key` - `anthropic_config` (object, optional) Anthropic Config. Only required if the provider is 'anthropic'. - `anthropic_api_key` (string, optional) The Databricks secret key reference for an Anthropic API key. If you prefer to paste your API key directly, see `anthropic_api_key_plaintext`. You must provide an API key using one of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. Example: `{{secrets/my_scope/my_anthropic_api_key}}` - `anthropic_api_key_plaintext` (string, optional, Input only) The Anthropic API key provided as a plaintext string. If you prefer to reference your key using Databricks Secrets, see `anthropic_api_key`. You must provide an API key using one of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. Example: `Your API Key` - `amazon_bedrock_config` (object, optional) Amazon Bedrock Config. Only required if the provider is 'amazon-bedrock'. - `aws_region` (string, required) The AWS region to use. Bedrock has to be enabled there. Example: `myAwsRegion` - `aws_access_key_id` (string, optional) The Databricks secret key reference for an AWS access key ID with permissions to interact with Bedrock services. If you prefer to paste your API key directly, see `aws_access_key_id_plaintext`. You must provide an API key using one of the following fields: `aws_access_key_id` or `aws_access_key_id_plaintext`. Example: `{{secrets/my_scope/my_aws_access_key_id}}` - `aws_secret_access_key` (string, optional) The Databricks secret key reference for an AWS secret access key paired with the access key ID, with permissions to interact with Bedrock services. If you prefer to paste your API key directly, see `aws_secret_access_key_plaintext`. You must provide an API key using one of the following fields: `aws_secret_access_key` or `aws_secret_access_key_plaintext`. Example: `{{secrets/my_scope/my_aws_secret_access_key}}` - `bedrock_provider` (string, required) The underlying provider in Amazon Bedrock. Supported values (case insensitive) include: Anthropic, Cohere, AI21Labs, Amazon. - `aws_access_key_id_plaintext` (string, optional, Input only) An AWS access key ID with permissions to interact with Bedrock services provided as a plaintext string. If you prefer to reference your key using Databricks Secrets, see `aws_access_key_id`. You must provide an API key using one of the following fields: `aws_access_key_id` or `aws_access_key_id_plaintext`. Example: `Your AWS Access Key ID` - `aws_secret_access_key_plaintext` (string, optional, Input only) An AWS secret access key paired with the access key ID, with permissions to interact with Bedrock services provided as a plaintext string. If you prefer to reference your key using Databricks Secrets, see `aws_secret_access_key`. You must provide an API key using one of the following fields: `aws_secret_access_key` or `aws_secret_access_key_plaintext`. Example: `Your AWS Secret Access Key` - `instance_profile_arn` (string, optional) ARN of the instance profile that the external model will use to access AWS resources. You must authenticate using an instance profile or access keys. If you prefer to authenticate using access keys, see `aws_access_key_id`, `aws_access_key_id_plaintext`, `aws_secret_access_key` and `aws_secret_access_key_plaintext`. Example: `arn:aws:iam::123456789012:instance-profile/my-instance-profile` - `uc_service_credential_name` (string, optional, Public Preview) The name of the Unity Catalog service credential that the external model uses to access AWS resources. Example: `my-uc-service-credential` - `cohere_config` (object, optional) Cohere Config. Only required if the provider is 'cohere'. - `cohere_api_key` (string, optional) The Databricks secret key reference for a Cohere API key. If you prefer to paste your API key directly, see `cohere_api_key_plaintext`. You must provide an API key using one of the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. Example: `{{secrets/my_scope/my_cohere_api_key}}` - `cohere_api_key_plaintext` (string, optional, Input only) The Cohere API key provided as a plaintext string. If you prefer to reference your key using Databricks Secrets, see `cohere_api_key`. You must provide an API key using one of the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. Example: `Your API Key` - `cohere_api_base` (string, optional) This is an optional field to provide a customized base URL for the Cohere API. If left unspecified, the standard Cohere base URL is used. Example: `https://api.cohere.ai/v1` - `google_cloud_vertex_ai_config` (object, optional) Google Cloud Vertex AI Config. Only required if the provider is 'google-cloud-vertex-ai'. - `private_key` (string, optional) The Databricks secret key reference for a private key for the service account which has access to the Google Cloud Vertex AI Service. See [Best practices for managing service account keys]. If you prefer to paste your API key directly, see `private_key_plaintext`. You must provide an API key using one of the following fields: `private_key` or `private_key_plaintext` [Best practices for managing service account keys]: https://cloud.google.com/iam/docs/best-practices-for-managing-service-account-keys Example: `{{secrets/my_scope/my_google_cloud_vertex_ai_api_key}}` - `project_id` (string, required) This is the Google Cloud project id that the service account is associated with. Example: `your-project-id` - `region` (string, required) This is the region for the Google Cloud Vertex AI Service. See [supported regions] for more details. Some models are only available in specific regions. [supported regions]: https://cloud.google.com/vertex-ai/docs/general/locations Example: `us-central1` - `private_key_plaintext` (string, optional, Input only) The private key for the service account which has access to the Google Cloud Vertex AI Service provided as a plaintext secret. See [Best practices for managing service account keys]. If you prefer to reference your key using Databricks Secrets, see `private_key`. You must provide an API key using one of the following fields: `private_key` or `private_key_plaintext`. [Best practices for managing service account keys]: https://cloud.google.com/iam/docs/best-practices-for-managing-service-account-keys Example: `Your API Key` - `databricks_model_serving_config` (object, optional) Databricks Model Serving Config. Only required if the provider is 'databricks-model-serving'. - `databricks_api_token` (string, optional) The Databricks secret key reference for a Databricks API token that corresponds to a user or service principal with Can Query access to the model serving endpoint pointed to by this external model. If you prefer to paste your API key directly, see `databricks_api_token_plaintext`. You must provide an API key using one of the following fields: `databricks_api_token` or `databricks_api_token_plaintext`. Example: `{{secrets/my_scope/my_databricks_api_token}}` - `databricks_workspace_url` (string, required) The URL of the Databricks workspace containing the model serving endpoint pointed to by this external model. Example: `https://my-databricks-workspace.com` - `databricks_api_token_plaintext` (string, optional, Input only) The Databricks API token that corresponds to a user or service principal with Can Query access to the model serving endpoint pointed to by this external model provided as a plaintext string. If you prefer to reference your key using Databricks Secrets, see `databricks_api_token`. You must provide an API key using one of the following fields: `databricks_api_token` or `databricks_api_token_plaintext`. Example: `Your Databricks API Token` - `openai_config` (object, optional) OpenAI Config. Only required if the provider is 'openai'. - `openai_api_key` (string, optional) The Databricks secret key reference for an OpenAI API key using the OpenAI or Azure service. If you prefer to paste your API key directly, see `openai_api_key_plaintext`. You must provide an API key using one of the following fields: `openai_api_key` or `openai_api_key_plaintext`. Example: `{{secrets/my_scope/my_openai_api_key}}` - `openai_api_type` (string, optional) This is an optional field to specify the type of OpenAI API to use. For Azure OpenAI, this field is required, and adjust this parameter to represent the preferred security access validation protocol. For access token validation, use azure. For authentication using Azure Active Directory (Azure AD) use, azuread. Example: `azure` - `openai_api_base` (string, optional) This is a field to provide a customized base URl for the OpenAI API. For Azure OpenAI, this field is required, and is the base URL for the Azure OpenAI API service provided by Azure. For other OpenAI API types, this field is optional, and if left unspecified, the standard OpenAI base URL is used. Example: `https://api.openai.com/v1` - `openai_api_version` (string, optional) This is an optional field to specify the OpenAI API version. For Azure OpenAI, this field is required, and is the version of the Azure OpenAI service to utilize, specified by a date. Example: `2023-11-01` - `openai_deployment_name` (string, optional) This field is only required for Azure OpenAI and is the name of the deployment resource for the Azure OpenAI service. Example: `my_deployment_resource` - `openai_organization` (string, optional) This is an optional field to specify the organization in OpenAI or Azure OpenAI. Example: `Databricks` - `microsoft_entra_tenant_id` (string, optional) This field is only required for Azure AD OpenAI and is the Microsoft Entra Tenant ID. Example: `12345678-abcd-1234-5678-12345678abcd` - `microsoft_entra_client_id` (string, optional) This field is only required for Azure AD OpenAI and is the Microsoft Entra Client ID. Example: `12345678-abcd-1234-5678-12345678abcd` - `microsoft_entra_client_secret` (string, optional) The Databricks secret key reference for a client secret used for Microsoft Entra ID authentication. If you prefer to paste your client secret directly, see `microsoft_entra_client_secret_plaintext`. You must provide an API key using one of the following fields: `microsoft_entra_client_secret` or `microsoft_entra_client_secret_plaintext`. Example: `{{secrets/my_scope/my_microsoft_entra_client_secret}}` - `openai_api_key_plaintext` (string, optional, Input only) The OpenAI API key using the OpenAI or Azure service provided as a plaintext string. If you prefer to reference your key using Databricks Secrets, see `openai_api_key`. You must provide an API key using one of the following fields: `openai_api_key` or `openai_api_key_plaintext`. Example: `Your API Key` - `microsoft_entra_client_secret_plaintext` (string, optional, Input only) The client secret used for Microsoft Entra ID authentication provided as a plaintext string. If you prefer to reference your key using Databricks Secrets, see `microsoft_entra_client_secret`. You must provide an API key using one of the following fields: `microsoft_entra_client_secret` or `microsoft_entra_client_secret_plaintext`. Example: `Your Microsoft Entra Client Secret` - `palm_config` (object, optional) PaLM Config. Only required if the provider is 'palm'. - `palm_api_key` (string, optional) The Databricks secret key reference for a PaLM API key. If you prefer to paste your API key directly, see `palm_api_key_plaintext`. You must provide an API key using one of the following fields: `palm_api_key` or `palm_api_key_plaintext`. Example: `{{secrets/my_scope/my_palm_api_key}}` - `palm_api_key_plaintext` (string, optional, Input only) The PaLM API key provided as a plaintext string. If you prefer to reference your key using Databricks Secrets, see `palm_api_key`. You must provide an API key using one of the following fields: `palm_api_key` or `palm_api_key_plaintext`. Example: `Your API Key` - `custom_provider_config` (object, optional) Custom Provider Config. Only required if the provider is 'custom'. - `custom_provider_url` (string, required) This is a field to provide the URL of the custom provider API. Example: `https://custom-provider.com` - `bearer_token_auth` (object, optional) This is a field to provide bearer token authentication for the custom provider API. You can only specify one authentication method. - `token` (string, optional) The Databricks secret key reference for a token. If you prefer to paste your token directly, see `token_plaintext`. Example: `{{secrets/my_scope/my_openai_api_key}}` - `token_plaintext` (string, optional, Input only) The token provided as a plaintext string. If you prefer to reference your token using Databricks Secrets, see `token`. Example: `Your API Key` - `api_key_auth` (object, optional) This is a field to provide API key authentication for the custom provider API. You can only specify one authentication method. - `key` (string, required) The name of the API key parameter used for authentication. Example: `api-key` - `value` (string, optional) The Databricks secret key reference for an API Key. If you prefer to paste your token directly, see `value_plaintext`. Example: `{{secrets/my_scope/my_api_key}}` - `value_plaintext` (string, optional, Input only) The API Key provided as a plaintext string. If you prefer to reference your token using Databricks Secrets, see `value`. Example: `Your API Key` - `entity_name` (string, optional) The name of the entity to be served. The entity may be a model in the Databricks Model Registry, a model in the Unity Catalog (UC), or a function of type FEATURE_SPEC in the UC. If it is a UC object, the full name of the object should be given in the form of **catalog_name.schema_name.model_name**. Example: `ads-model` - `entity_version` (string, optional) Example: `3` - `min_provisioned_throughput` (int32, optional) The minimum tokens per second that the endpoint can scale down to. Example: `970` - `max_provisioned_throughput` (int32, optional) The maximum tokens per second that the endpoint can scale up to. Example: `1960` - `min_provisioned_concurrency` (int32, optional) The minimum provisioned concurrency that the endpoint can scale down to. Do not use if workload_size is specified. Example: `8` - `max_provisioned_concurrency` (int32, optional) The maximum provisioned concurrency that the endpoint can scale up to. Do not use if workload_size is specified. Example: `32` - `workload_size` (string, optional) The workload size of the served entity. The workload size corresponds to a range of provisioned concurrency that the compute autoscales between. A single unit of provisioned concurrency can process one request at a time. Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). Additional custom workload sizes can also be used when available in the workspace. If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each workload size is 0. Do not use if min_provisioned_concurrency and max_provisioned_concurrency are specified. - `provisioned_model_units` (int64, optional, Public Preview) The number of model units provisioned. Example: `100` - `burst_scaling_enabled` (boolean, optional, Public Preview, Input only) Whether burst scaling is enabled. When enabled (default), the endpoint can automatically scale up beyond provisioned capacity to handle traffic spikes. When disabled, the endpoint maintains fixed capacity at provisioned_model_units. Example: `true` - `scale_to_zero_enabled` (boolean, optional) Whether the compute resources for the served entity should scale down to zero. Example: `false` - `model_name` (string, required) - `model_version` (string, required) - `environment_vars` (object, optional) An object containing a set of optional, user-specified environment variable key-value pairs used for serving this entity. Note: this is an experimental feature and subject to change. Example entity environment variables that refer to Databricks secrets: `{"OPENAI_API_KEY": "{{secrets/my_scope/my_key}}", "DATABRICKS_TOKEN": "{{secrets/my_scope2/my_key2}}"}` - `instance_profile_arn` (string, optional, Public Preview) ARN of the instance profile that the served entity uses to access AWS resources. - `foundation_model` (object, optional, Public Preview) - `name` (string, optional, Public Preview) - `display_name` (string, optional, Public Preview) - `docs` (string, optional, Public Preview) - `description` (string, optional, Public Preview) - `state` (object, optional) - `deployment` (string, optional) Possible values: - `DEPLOYMENT_UNKNOWN` - `DEPLOYMENT_CREATING` - `DEPLOYMENT_RECOVERING` - `DEPLOYMENT_READY` - `DEPLOYMENT_FAILED` - `DEPLOYMENT_ABORTED` - `DEPLOYMENT_STOPPED` - `deployment_state_message` (string, optional) - `creator` (string, optional) - `creation_timestamp` (int64, optional) - `served_models` (array of object, optional) (Deprecated, use served_entities instead) The list of served models under the serving endpoint config. - `name` (string, optional) The name of a served entity. It must be unique across an endpoint. A served entity name can consist of alphanumeric characters, dashes, and underscores. If not specified for an external model, this field defaults to external_model.name, with '.' and ':' replaced with '-', and if not specified for other entities, it defaults to entity_name-entity_version. Example: `ads-model-3` - `external_model` (object, optional) The external model to be served. NOTE: Only one of external_model and (entity_name, entity_version, workload_size, workload_type, and scale_to_zero_enabled) can be specified with the latter set being used for custom model serving for a Databricks registered model. For an existing endpoint with external_model, it cannot be updated to an endpoint without external_model. If the endpoint is created without external_model, users cannot update it to add external_model later. The task type of all external models within an endpoint must be the same. - `provider` (string, required) The name of the provider for the external model. Currently, the supported providers are 'ai21labs', 'anthropic', 'amazon-bedrock', 'cohere', 'databricks-model-serving', 'google-cloud-vertex-ai', 'openai', 'palm', and 'custom'. - `name` (string, required) The name of the external model. Example: `gpt-4` - `task` (string, required) The task type of the external model. Example: `llm/v1/chat` - `ai21labs_config` (object, optional) AI21Labs Config. Only required if the provider is 'ai21labs'. - `ai21labs_api_key` (string, optional) The Databricks secret key reference for an AI21 Labs API key. If you prefer to paste your API key directly, see `ai21labs_api_key_plaintext`. You must provide an API key using one of the following fields: `ai21labs_api_key` or `ai21labs_api_key_plaintext`. Example: `{{secrets/my_scope/my_ai21labs_api_key}}` - `ai21labs_api_key_plaintext` (string, optional, Input only) An AI21 Labs API key provided as a plaintext string. If you prefer to reference your key using Databricks Secrets, see `ai21labs_api_key`. You must provide an API key using one of the following fields: `ai21labs_api_key` or `ai21labs_api_key_plaintext`. Example: `Your API Key` - `anthropic_config` (object, optional) Anthropic Config. Only required if the provider is 'anthropic'. - `anthropic_api_key` (string, optional) The Databricks secret key reference for an Anthropic API key. If you prefer to paste your API key directly, see `anthropic_api_key_plaintext`. You must provide an API key using one of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. Example: `{{secrets/my_scope/my_anthropic_api_key}}` - `anthropic_api_key_plaintext` (string, optional, Input only) The Anthropic API key provided as a plaintext string. If you prefer to reference your key using Databricks Secrets, see `anthropic_api_key`. You must provide an API key using one of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. Example: `Your API Key` - `amazon_bedrock_config` (object, optional) Amazon Bedrock Config. Only required if the provider is 'amazon-bedrock'. - `aws_region` (string, required) The AWS region to use. Bedrock has to be enabled there. Example: `myAwsRegion` - `aws_access_key_id` (string, optional) The Databricks secret key reference for an AWS access key ID with permissions to interact with Bedrock services. If you prefer to paste your API key directly, see `aws_access_key_id_plaintext`. You must provide an API key using one of the following fields: `aws_access_key_id` or `aws_access_key_id_plaintext`. Example: `{{secrets/my_scope/my_aws_access_key_id}}` - `aws_secret_access_key` (string, optional) The Databricks secret key reference for an AWS secret access key paired with the access key ID, with permissions to interact with Bedrock services. If you prefer to paste your API key directly, see `aws_secret_access_key_plaintext`. You must provide an API key using one of the following fields: `aws_secret_access_key` or `aws_secret_access_key_plaintext`. Example: `{{secrets/my_scope/my_aws_secret_access_key}}` - `bedrock_provider` (string, required) The underlying provider in Amazon Bedrock. Supported values (case insensitive) include: Anthropic, Cohere, AI21Labs, Amazon. - `aws_access_key_id_plaintext` (string, optional, Input only) An AWS access key ID with permissions to interact with Bedrock services provided as a plaintext string. If you prefer to reference your key using Databricks Secrets, see `aws_access_key_id`. You must provide an API key using one of the following fields: `aws_access_key_id` or `aws_access_key_id_plaintext`. Example: `Your AWS Access Key ID` - `aws_secret_access_key_plaintext` (string, optional, Input only) An AWS secret access key paired with the access key ID, with permissions to interact with Bedrock services provided as a plaintext string. If you prefer to reference your key using Databricks Secrets, see `aws_secret_access_key`. You must provide an API key using one of the following fields: `aws_secret_access_key` or `aws_secret_access_key_plaintext`. Example: `Your AWS Secret Access Key` - `instance_profile_arn` (string, optional) ARN of the instance profile that the external model will use to access AWS resources. You must authenticate using an instance profile or access keys. If you prefer to authenticate using access keys, see `aws_access_key_id`, `aws_access_key_id_plaintext`, `aws_secret_access_key` and `aws_secret_access_key_plaintext`. Example: `arn:aws:iam::123456789012:instance-profile/my-instance-profile` - `uc_service_credential_name` (string, optional, Public Preview) The name of the Unity Catalog service credential that the external model uses to access AWS resources. Example: `my-uc-service-credential` - `cohere_config` (object, optional) Cohere Config. Only required if the provider is 'cohere'. - `cohere_api_key` (string, optional) The Databricks secret key reference for a Cohere API key. If you prefer to paste your API key directly, see `cohere_api_key_plaintext`. You must provide an API key using one of the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. Example: `{{secrets/my_scope/my_cohere_api_key}}` - `cohere_api_key_plaintext` (string, optional, Input only) The Cohere API key provided as a plaintext string. If you prefer to reference your key using Databricks Secrets, see `cohere_api_key`. You must provide an API key using one of the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. Example: `Your API Key` - `cohere_api_base` (string, optional) This is an optional field to provide a customized base URL for the Cohere API. If left unspecified, the standard Cohere base URL is used. Example: `https://api.cohere.ai/v1` - `google_cloud_vertex_ai_config` (object, optional) Google Cloud Vertex AI Config. Only required if the provider is 'google-cloud-vertex-ai'. - `private_key` (string, optional) The Databricks secret key reference for a private key for the service account which has access to the Google Cloud Vertex AI Service. See [Best practices for managing service account keys]. If you prefer to paste your API key directly, see `private_key_plaintext`. You must provide an API key using one of the following fields: `private_key` or `private_key_plaintext` [Best practices for managing service account keys]: https://cloud.google.com/iam/docs/best-practices-for-managing-service-account-keys Example: `{{secrets/my_scope/my_google_cloud_vertex_ai_api_key}}` - `project_id` (string, required) This is the Google Cloud project id that the service account is associated with. Example: `your-project-id` - `region` (string, required) This is the region for the Google Cloud Vertex AI Service. See [supported regions] for more details. Some models are only available in specific regions. [supported regions]: https://cloud.google.com/vertex-ai/docs/general/locations Example: `us-central1` - `private_key_plaintext` (string, optional, Input only) The private key for the service account which has access to the Google Cloud Vertex AI Service provided as a plaintext secret. See [Best practices for managing service account keys]. If you prefer to reference your key using Databricks Secrets, see `private_key`. You must provide an API key using one of the following fields: `private_key` or `private_key_plaintext`. [Best practices for managing service account keys]: https://cloud.google.com/iam/docs/best-practices-for-managing-service-account-keys Example: `Your API Key` - `databricks_model_serving_config` (object, optional) Databricks Model Serving Config. Only required if the provider is 'databricks-model-serving'. - `databricks_api_token` (string, optional) The Databricks secret key reference for a Databricks API token that corresponds to a user or service principal with Can Query access to the model serving endpoint pointed to by this external model. If you prefer to paste your API key directly, see `databricks_api_token_plaintext`. You must provide an API key using one of the following fields: `databricks_api_token` or `databricks_api_token_plaintext`. Example: `{{secrets/my_scope/my_databricks_api_token}}` - `databricks_workspace_url` (string, required) The URL of the Databricks workspace containing the model serving endpoint pointed to by this external model. Example: `https://my-databricks-workspace.com` - `databricks_api_token_plaintext` (string, optional, Input only) The Databricks API token that corresponds to a user or service principal with Can Query access to the model serving endpoint pointed to by this external model provided as a plaintext string. If you prefer to reference your key using Databricks Secrets, see `databricks_api_token`. You must provide an API key using one of the following fields: `databricks_api_token` or `databricks_api_token_plaintext`. Example: `Your Databricks API Token` - `openai_config` (object, optional) OpenAI Config. Only required if the provider is 'openai'. - `openai_api_key` (string, optional) The Databricks secret key reference for an OpenAI API key using the OpenAI or Azure service. If you prefer to paste your API key directly, see `openai_api_key_plaintext`. You must provide an API key using one of the following fields: `openai_api_key` or `openai_api_key_plaintext`. Example: `{{secrets/my_scope/my_openai_api_key}}` - `openai_api_type` (string, optional) This is an optional field to specify the type of OpenAI API to use. For Azure OpenAI, this field is required, and adjust this parameter to represent the preferred security access validation protocol. For access token validation, use azure. For authentication using Azure Active Directory (Azure AD) use, azuread. Example: `azure` - `openai_api_base` (string, optional) This is a field to provide a customized base URl for the OpenAI API. For Azure OpenAI, this field is required, and is the base URL for the Azure OpenAI API service provided by Azure. For other OpenAI API types, this field is optional, and if left unspecified, the standard OpenAI base URL is used. Example: `https://api.openai.com/v1` - `openai_api_version` (string, optional) This is an optional field to specify the OpenAI API version. For Azure OpenAI, this field is required, and is the version of the Azure OpenAI service to utilize, specified by a date. Example: `2023-11-01` - `openai_deployment_name` (string, optional) This field is only required for Azure OpenAI and is the name of the deployment resource for the Azure OpenAI service. Example: `my_deployment_resource` - `openai_organization` (string, optional) This is an optional field to specify the organization in OpenAI or Azure OpenAI. Example: `Databricks` - `microsoft_entra_tenant_id` (string, optional) This field is only required for Azure AD OpenAI and is the Microsoft Entra Tenant ID. Example: `12345678-abcd-1234-5678-12345678abcd` - `microsoft_entra_client_id` (string, optional) This field is only required for Azure AD OpenAI and is the Microsoft Entra Client ID. Example: `12345678-abcd-1234-5678-12345678abcd` - `microsoft_entra_client_secret` (string, optional) The Databricks secret key reference for a client secret used for Microsoft Entra ID authentication. If you prefer to paste your client secret directly, see `microsoft_entra_client_secret_plaintext`. You must provide an API key using one of the following fields: `microsoft_entra_client_secret` or `microsoft_entra_client_secret_plaintext`. Example: `{{secrets/my_scope/my_microsoft_entra_client_secret}}` - `openai_api_key_plaintext` (string, optional, Input only) The OpenAI API key using the OpenAI or Azure service provided as a plaintext string. If you prefer to reference your key using Databricks Secrets, see `openai_api_key`. You must provide an API key using one of the following fields: `openai_api_key` or `openai_api_key_plaintext`. Example: `Your API Key` - `microsoft_entra_client_secret_plaintext` (string, optional, Input only) The client secret used for Microsoft Entra ID authentication provided as a plaintext string. If you prefer to reference your key using Databricks Secrets, see `microsoft_entra_client_secret`. You must provide an API key using one of the following fields: `microsoft_entra_client_secret` or `microsoft_entra_client_secret_plaintext`. Example: `Your Microsoft Entra Client Secret` - `palm_config` (object, optional) PaLM Config. Only required if the provider is 'palm'. - `palm_api_key` (string, optional) The Databricks secret key reference for a PaLM API key. If you prefer to paste your API key directly, see `palm_api_key_plaintext`. You must provide an API key using one of the following fields: `palm_api_key` or `palm_api_key_plaintext`. Example: `{{secrets/my_scope/my_palm_api_key}}` - `palm_api_key_plaintext` (string, optional, Input only) The PaLM API key provided as a plaintext string. If you prefer to reference your key using Databricks Secrets, see `palm_api_key`. You must provide an API key using one of the following fields: `palm_api_key` or `palm_api_key_plaintext`. Example: `Your API Key` - `custom_provider_config` (object, optional) Custom Provider Config. Only required if the provider is 'custom'. - `custom_provider_url` (string, required) This is a field to provide the URL of the custom provider API. Example: `https://custom-provider.com` - `bearer_token_auth` (object, optional) This is a field to provide bearer token authentication for the custom provider API. You can only specify one authentication method. - `token` (string, optional) The Databricks secret key reference for a token. If you prefer to paste your token directly, see `token_plaintext`. Example: `{{secrets/my_scope/my_openai_api_key}}` - `token_plaintext` (string, optional, Input only) The token provided as a plaintext string. If you prefer to reference your token using Databricks Secrets, see `token`. Example: `Your API Key` - `api_key_auth` (object, optional) This is a field to provide API key authentication for the custom provider API. You can only specify one authentication method. - `key` (string, required) The name of the API key parameter used for authentication. Example: `api-key` - `value` (string, optional) The Databricks secret key reference for an API Key. If you prefer to paste your token directly, see `value_plaintext`. Example: `{{secrets/my_scope/my_api_key}}` - `value_plaintext` (string, optional, Input only) The API Key provided as a plaintext string. If you prefer to reference your token using Databricks Secrets, see `value`. Example: `Your API Key` - `entity_name` (string, optional) The name of the entity to be served. The entity may be a model in the Databricks Model Registry, a model in the Unity Catalog (UC), or a function of type FEATURE_SPEC in the UC. If it is a UC object, the full name of the object should be given in the form of **catalog_name.schema_name.model_name**. Example: `ads-model` - `entity_version` (string, optional) Example: `3` - `min_provisioned_throughput` (int32, optional) The minimum tokens per second that the endpoint can scale down to. Example: `970` - `max_provisioned_throughput` (int32, optional) The maximum tokens per second that the endpoint can scale up to. Example: `1960` - `min_provisioned_concurrency` (int32, optional) The minimum provisioned concurrency that the endpoint can scale down to. Do not use if workload_size is specified. Example: `8` - `max_provisioned_concurrency` (int32, optional) The maximum provisioned concurrency that the endpoint can scale up to. Do not use if workload_size is specified. Example: `32` - `workload_size` (string, optional) The workload size of the served entity. The workload size corresponds to a range of provisioned concurrency that the compute autoscales between. A single unit of provisioned concurrency can process one request at a time. Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). Additional custom workload sizes can also be used when available in the workspace. If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each workload size is 0. Do not use if min_provisioned_concurrency and max_provisioned_concurrency are specified. - `provisioned_model_units` (int64, optional, Public Preview) The number of model units provisioned. Example: `100` - `burst_scaling_enabled` (boolean, optional, Public Preview, Input only) Whether burst scaling is enabled. When enabled (default), the endpoint can automatically scale up beyond provisioned capacity to handle traffic spikes. When disabled, the endpoint maintains fixed capacity at provisioned_model_units. Example: `true` - `scale_to_zero_enabled` (boolean, optional) Whether the compute resources for the served entity should scale down to zero. Example: `false` - `model_name` (string, required) - `model_version` (string, required) - `environment_vars` (object, optional) An object containing a set of optional, user-specified environment variable key-value pairs used for serving this entity. Note: this is an experimental feature and subject to change. Example entity environment variables that refer to Databricks secrets: `{"OPENAI_API_KEY": "{{secrets/my_scope/my_key}}", "DATABRICKS_TOKEN": "{{secrets/my_scope2/my_key2}}"}` - `instance_profile_arn` (string, optional, Public Preview) ARN of the instance profile that the served entity uses to access AWS resources. - `foundation_model` (object, optional, Public Preview) - `name` (string, optional, Public Preview) - `display_name` (string, optional, Public Preview) - `docs` (string, optional, Public Preview) - `description` (string, optional, Public Preview) - `state` (object, optional) - `deployment` (string, optional) Possible values: - `DEPLOYMENT_UNKNOWN` - `DEPLOYMENT_CREATING` - `DEPLOYMENT_RECOVERING` - `DEPLOYMENT_READY` - `DEPLOYMENT_FAILED` - `DEPLOYMENT_ABORTED` - `DEPLOYMENT_STOPPED` - `deployment_state_message` (string, optional) - `creator` (string, optional) - `creation_timestamp` (int64, optional) - `traffic_config` (object, optional) The traffic configuration associated with the serving endpoint config. - `routes` (array of object, optional) The list of routes that define traffic to each served entity. - `served_model_name` (string, optional) The name of the served model this route configures traffic for. Example: `ads-model-3` - `traffic_percentage` (int32, required) The percentage of endpoint traffic to send to this route. It must be an integer between 0 and 100 inclusive. Example: `100` - `served_entity_name` (string, optional) Example: `ads-model-3` - `auto_capture_config` (object, optional, Deprecated) Configuration for legacy Inference Tables which automatically log requests and responses to Unity Catalog. Deprecated: please use AI Gateway inference tables instead. See https://docs.databricks.com/aws/en/ai-gateway/inference-tables. - `catalog_name` (string, optional) The name of the catalog in Unity Catalog. NOTE: On update, you cannot change the catalog name if the inference table is already enabled. Example: `my-catalog` - `schema_name` (string, optional) The name of the schema in Unity Catalog. NOTE: On update, you cannot change the schema name if the inference table is already enabled. Example: `my-schema` - `table_name_prefix` (string, optional) The prefix of the table in Unity Catalog. NOTE: On update, you cannot change the prefix name if the inference table is already enabled. Example: `my-prefix-` - `state` (object, optional) - `payload_table` (object, optional) - `name` (string, optional) - `status` (string, optional) - `status_message` (string, optional) - `enabled` (boolean, optional) Indicates whether the inference table is enabled. Example: `true` ## Returns Returns the InferenceEndpointDetailed object. ## Request ### External model endpoint ```json { "served_entities": [ { "external_model": { "name": "gpt-4", "openai_config": { "openai_api_key": "{{secrets/my_scope/my_openai_api_key}}" }, "provider": "openai", "task": "llm/v1/chat" }, "name": "openapi_chat" } ] } ``` ### Feature Serving endpoint ```json { "served_entities": [ { "entity_name": "feature_store.me.transport_spec", "name": "feature-spec-transport", "scale_to_zero_enabled": true, "workload_size": "Small" } ] } ``` ### Models in Unity Catalog endpoint ```json { "served_entities": [ { "entity_name": "myCatalog.mySchema.my-ads-model", "entity_version": "3", "scale_to_zero_enabled": true, "workload_size": "Small" }, { "entity_name": "myCatalog.mySchema.my-ads-model", "entity_version": "4", "scale_to_zero_enabled": true, "workload_size": "Small" } ], "traffic_config": { "routes": [ { "served_model_name": "my-ads-model-3", "traffic_percentage": 80 }, { "served_model_name": "my-ads-model-4", "traffic_percentage": 20 } ] } } ``` ### Workspace model endpoint ```json { "served_entities": [ { "entity_name": "my-ads-model", "entity_version": "5", "scale_to_zero_enabled": true, "workload_size": "Small" } ], "traffic_config": { "routes": [ { "served_model_name": "my-ads-model-5", "traffic_percentage": 100 } ] } } ``` ## Response ### External model endpoint ```json { "config": { "config_version": 1, "served_entities": [ { "creation_timestamp": 1699617587000, "creator": "user@email.com", "external_model": { "name": "gpt-4", "openai_config": { "openai_api_key": "{{secrets/my_scope/my_openai_api_key}}" }, "provider": "openai", "task": "llm/v1/chat" }, "name": "openai_chat", "state": { "deployment": "DEPLOYMENT_READY", "deployment_state_message": "" } } ], "traffic_config": { "routes": [ { "served_model_name": "openai_chat", "traffic_percentage": 100 } ] } }, "creation_timestamp": 1699617587000, "creator": "user@email.com", "id": "69962db6b9db47c4a8a222d2ac79d7f8", "last_updated_timestamp": 1699617587000, "name": "openai_endpoint", "permission_level": "CAN_MANAGE", "route_optimized": false, "state": { "ready": "READY" } } ``` ### Feature Serving endpoint ```json { "config": { "config_version": 1, "served_entities": [ { "creation_timestamp": 1700089760000, "creator": "user@email.com", "entity_name": "feature_store.me.travel_spec", "name": "feature-spec-travel", "scale_to_zero_enabled": true, "state": { "deployment": "DEPLOYMENT_READY", "deployment_state_message": "" }, "workload_size": "Small", "workload_type": "CPU" } ], "traffic_config": { "routes": [ { "served_model_name": "feature-spec-travel", "traffic_percentage": 100 } ] } }, "creation_timestamp": 1700089637000, "creator": "user@email.com", "id": "e3bd3e471d6045d6b75f384279e4b6ab", "last_updated_timestamp": 1700089760000, "name": "feature-spec-endpoint", "permission_level": "CAN_MANAGE", "route_optimized": false, "state": { "config_update": "NOT_UPDATING", "ready": "READY" }, "tags": [ { "key": "team", "value": "data science" } ] } ``` ### Models in Unity Catalog endpoint ```json { "config": { "config_version": 1, "served_entities": [ { "creation_timestamp": 1700089760000, "creator": "user@email.com", "entity_name": "myCatalog.mySchema.my-ads-model", "entity_version": "10", "name": "my-ads-model-10", "scale_to_zero_enabled": true, "state": { "deployment": "DEPLOYMENT_READY", "deployment_state_message": "" }, "workload_size": "Small", "workload_type": "CPU" } ], "traffic_config": { "routes": [ { "served_model_name": "my-ads-model-10", "traffic_percentage": 100 } ] } }, "creation_timestamp": 1700089637000, "creator": "user@email.com", "id": "e3bd3e471d6045d6b75f384279e4b6ab", "last_updated_timestamp": 1700089760000, "name": "uc-model-endpoint", "permission_level": "CAN_MANAGE", "route_optimized": false, "state": { "config_update": "NOT_UPDATING", "ready": "READY" }, "tags": [ { "key": "team", "value": "data science" } ] } ``` ### Workspace model endpoint ```json { "config": { "config_version": 1, "served_entities": [ { "creation_timestamp": 1700089760000, "creator": "user@email.com", "entity_name": "my-ads-model", "entity_version": "3", "name": "my-ads-model-3", "scale_to_zero_enabled": true, "state": { "deployment": "DEPLOYMENT_READY", "deployment_state_message": "" }, "workload_size": "Small", "workload_type": "CPU" }, { "creation_timestamp": 1700089760000, "creator": "user@email.com", "entity_name": "my-ads-model", "entity_version": "4", "name": "my-ads-model-4", "scale_to_zero_enabled": true, "state": { "deployment": "DEPLOYMENT_READY", "deployment_state_message": "" }, "workload_size": "Small", "workload_type": "CPU" } ], "traffic_config": { "routes": [ { "served_model_name": "my-ads-model-3", "traffic_percentage": 80 }, { "served_model_name": "my-ads-model-4", "traffic_percentage": 20 } ] } }, "creation_timestamp": 1700089637000, "creator": "user@email.com", "id": "e3bd3e471d6045d6b75f384279e4b6ab", "last_updated_timestamp": 1700089760000, "name": "workspace-model-endpoint", "permission_level": "CAN_MANAGE", "route_optimized": false, "state": { "config_update": "NOT_UPDATING", "ready": "READY" }, "tags": [ { "key": "team", "value": "data science" } ] } ```