Webservice Class
Defines base functionality for deploying models as web service endpoints in Azure Machine Learning.
Webservice constructor is used to retrieve a cloud representation of a Webservice object associated with the provided Workspace. Returns an instance of a child class corresponding to the specific type of the retrieved Webservice object. The Webservice class allows for deploying machine learning models from either a Model or Image object.
For more information about working with Webservice, see Deploy models with Azure Machine Learning.
Initialize the Webservice instance.
The Webservice constructor retrieves a cloud representation of a Webservice object associated with the provided workspace. It will return an instance of a child class corresponding to the specific type of the retrieved Webservice object.
- Inheritance
-
Webservice
Constructor
Webservice(workspace, name)Parameters
Remarks
The following sample shows the recommended deployment pattern where you first create a configuration object
with the deploy_configuration method of the child class of Webservice (in this case
AksWebservice) and then use the configuration with the deploy method of
the Model class.
# Set the web service configuration (using default here)
aks_config = AksWebservice.deploy_configuration()
# # Enable token auth and disable (key) auth on the webservice
# aks_config = AksWebservice.deploy_configuration(token_auth_enabled=True, auth_enabled=False)
Full sample is available from https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/deployment/production-deploy-to-aks/production-deploy-to-aks.ipynb
The following sample shows how to find an existing AciWebservice in a workspace and delete it if it exists so the name can be reused.
from azureml.core.model import InferenceConfig
from azureml.core.webservice import AciWebservice
service_name = 'my-custom-env-service'
inference_config = InferenceConfig(entry_script='score.py', environment=environment)
aci_config = AciWebservice.deploy_configuration(cpu_cores=1, memory_gb=1)
service = Model.deploy(workspace=ws,
name=service_name,
models=[model],
inference_config=inference_config,
deployment_config=aci_config,
overwrite=True)
service.wait_for_deployment(show_output=True)
Full sample is available from https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/deployment/deploy-to-cloud/model-register-and-deploy.ipynb
There are a number of ways to deploy a model as a webservice, including with the:
deploymethod of the Model for models already registered in the workspace.deploy_from_imagemethod of Webservice for images already created from a model.deploy_from_modelmethod of Webservice for models already registered in the workspace. This method will create an image.deploymethod of the Webservice, which will register a model and create an image.
For information on working with webservices, see
The Variables section lists attributes of a local representation of the cloud Webservice object. These variables should be considered read-only. Changing their values will not be reflected in the corresponding cloud object.
Variables
- auth_enabled
- bool
Whether or not the Webservice has auth enabled.
- compute_type
- str
What type of compute the Webservice is deployed to.
- created_time
- datetime
When the Webservice was created.
- azureml.core.Webservice.description
A description of the Webservice object.
- azureml.core.Webservice.tags
A dictionary of tags for the Webservice object.
- azureml.core.Webservice.name
The name of the Webservice.
- azureml.core.Webservice.properties
Dictionary of key value properties for the Webservice. These properties cannot be changed after deployment, however new key value pairs can be added.
- created_by
- str
The user that created the Webservice.
- error
- str
If the Webservice failed to deploy, this will contain the error message for why it failed.
- azureml.core.Webservice.state
The current state of the Webservice.
- updated_time
- datetime
The last time the Webservice was updated.
- azureml.core.Webservice.workspace
The Azure Machine Learning Workspace which contains this Webservice.
- token_auth_enabled
- bool
Whether or not the Webservice has token auth enabled.
Methods
| check_for_existing_webservice |
Check webservice exists. |
| delete |
Delete this Webservice from its associated workspace. This function call is not asynchronous. The call runs until the resource is deleted. A WebserviceException is raised if there is a problem deleting the model from the Model Management Service. |
| deploy |
Deploy a Webservice from zero or more Model objects. This function will register any models files provided and create an image in the process, all associated with the specified Workspace. Use this function when you have a directory of models to deploy that haven't been previously registered. The resulting Webservice is a real-time endpoint that can be used for inference requests. For more information, see Consume a model deployed as a web service. |
| deploy_from_image |
Deploy a Webservice from an Image object. Use this function if you already have an Image object created for a model. The resulting Webservice is a real-time endpoint that can be used for inference requests. For more information, see Consume a model deployed as a web service. |
| deploy_from_model |
Deploy a Webservice from zero or more Model objects. This function is similar to deploy, but does not register the models. Use this function if you have model objects that are already registered. This will create an image in the process, associated with the specified Workspace. The resulting Webservice is a real-time endpoint that can be used for inference requests. For more information, see Consume a model deployed as a web service. |
| deploy_local_from_model |
Build and deploy a LocalWebservice for testing. Requires Docker to be installed and configured. |
| deserialize |
Convert a Model Management Service response JSON object into a Webservice object. Will fail if the provided workspace is not the workspace the Webservice is registered under. |
| get_keys |
Retrieve auth keys for this Webservice. |
| get_logs |
Retrieve logs for this Webservice. |
| get_token |
Retrieve auth token for this Webservice, scoped to the current user. |
| list |
List the Webservices associated with the corresponding Workspace. The results returned can be filtered using parameters. |
| regen_key |
Regenerate one of the Webservice's keys, either the 'Primary' or 'Secondary' key. A WebserviceException is raised if |
| run |
Call this Webservice with the provided input. Abstract method implemented by child classes of Webservice. |
| serialize |
Convert this Webservice object into a JSON serialized dictionary. Use deserialize to convert back into a Webservice object. |
| update |
Update the Webservice parameters. This is an abstract method implemented by child classes of Webservice. Possible parameters to update vary based on Webservice child type. For example, for Azure Container Instances webservices, see update for specific parameters. |
| update_deployment_state |
Refresh the current state of the in-memory object. Perform an in-place update of the properties of the object based on the current state of the corresponding cloud object. Primarily useful for manual polling of creation state. |
| wait_for_deployment |
Automatically poll on the running Webservice deployment. Wait for the Webservice to reach a terminal state. Will throw a WebserviceException if it reaches a non-successful terminal state or exceeds the provided timeout. |
check_for_existing_webservice
Check webservice exists.
static check_for_existing_webservice(workspace, name, overwrite=False, request_func=None, check_func=None)Parameters
- workspace
- Workspace
- name
- str
- overwrite
- bool
- request_func
- <xref:function>
function to request service to check if service name exists
- check_func
- <xref:function>
function to check response content of request_func
Exceptions
delete
Delete this Webservice from its associated workspace.
This function call is not asynchronous. The call runs until the resource is deleted. A WebserviceException is raised if there is a problem deleting the model from the Model Management Service.
delete()Exceptions
deploy
Deploy a Webservice from zero or more Model objects.
This function will register any models files provided and create an image in the process, all associated with the specified Workspace. Use this function when you have a directory of models to deploy that haven't been previously registered.
The resulting Webservice is a real-time endpoint that can be used for inference requests. For more information, see Consume a model deployed as a web service.
static deploy(workspace, name, model_paths, image_config, deployment_config=None, deployment_target=None, overwrite=False)Parameters
- name
- str
The name to give the deployed service. Must be unique to the workspace, only consist of lowercase letters, numbers, or dashes, start with a letter, and be between 3 and 32 characters long.
A list of on-disk paths to model files or folder. Can be an empty list.
- image_config
- ImageConfig
An ImageConfig object used to determine required Image properties.
- deployment_config
- WebserviceDeploymentConfiguration
A WebserviceDeploymentConfiguration used to configure the webservice. If one is not provided, an empty configuration object will be used based on the desired target.
- deployment_target
- ComputeTarget
A ComputeTarget to deploy the Webservice to. As Azure Container Instances has no associated ComputeTarget, leave this parameter as None to deploy to Azure Container Instances.
- overwrite
- bool
Overwrite the existing service if service with name already exists.
Returns
A Webservice object corresponding to the deployed webservice.
Return type
Exceptions
deploy_from_image
Deploy a Webservice from an Image object.
Use this function if you already have an Image object created for a model.
The resulting Webservice is a real-time endpoint that can be used for inference requests. For more information, see Consume a model deployed as a web service.
static deploy_from_image(workspace, name, image, deployment_config=None, deployment_target=None, overwrite=False)Parameters
- name
- str
The name to give the deployed service. Must be unique to the workspace, only consist of lowercase letters, numbers, or dashes, start with a letter, and be between 3 and 32 characters long.
- deployment_config
- WebserviceDeploymentConfiguration
A WebserviceDeploymentConfiguration used to configure the webservice. If one is not provided, an empty configuration object will be used based on the desired target.
- deployment_target
- ComputeTarget
A ComputeTarget to deploy the Webservice to. As Azure Container Instances has no associated ComputeTarget, leave this parameter as None to deploy to Azure Container Instances.
- overwrite
- bool
Overwrite the existing service if service with name already exists.
Returns
A Webservice object corresponding to the deployed webservice.
Return type
Exceptions
deploy_from_model
Deploy a Webservice from zero or more Model objects.
This function is similar to deploy, but does not register the models. Use this function if you have model objects that are already registered. This will create an image in the process, associated with the specified Workspace.
The resulting Webservice is a real-time endpoint that can be used for inference requests. For more information, see Consume a model deployed as a web service.
static deploy_from_model(workspace, name, models, image_config, deployment_config=None, deployment_target=None, overwrite=False)Parameters
- name
- str
The name to give the deployed service. Must be unique to the workspace, only consist of lowercase letters, numbers, or dashes, start with a letter, and be between 3 and 32 characters long.
- image_config
- ImageConfig
An ImageConfig object used to determine required Image properties.
- deployment_config
- WebserviceDeploymentConfiguration
A WebserviceDeploymentConfiguration used to configure the webservice. If one is not provided, an empty configuration object will be used based on the desired target.
- deployment_target
- ComputeTarget
A ComputeTarget to deploy the Webservice to. As ACI has no associated ComputeTarget, leave this parameter as None to deploy to ACI.
- overwrite
- bool
Overwrite the existing service if service with name already exists.
Returns
A Webservice object corresponding to the deployed webservice.
Return type
Exceptions
deploy_local_from_model
Build and deploy a LocalWebservice for testing.
Requires Docker to be installed and configured.
static deploy_local_from_model(workspace, name, models, image_config, deployment_config=None, wait=False)Parameters
- image_config
- ImageConfig
An ImageConfig object used to determine required service image properties.
- deployment_config
- LocalWebserviceDeploymentConfiguration
A LocalWebserviceDeploymentConfiguration used to configure the webservice. If one is not provided, an empty configuration object will be used.
- wait
- bool
Whether to wait for the LocalWebservice's Docker container to report as healthy. Throws an exception if the container crashes. The default is False.
Return type
Exceptions
deserialize
Convert a Model Management Service response JSON object into a Webservice object.
Will fail if the provided workspace is not the workspace the Webservice is registered under.
deserialize(workspace, webservice_payload)Parameters
- cls
Indicates that this is a class method.
Returns
The Webservice representation of the provided JSON object.
Return type
Exceptions
get_keys
Retrieve auth keys for this Webservice.
get_keys()Returns
The auth keys for this Webservice.
Return type
Exceptions
get_logs
Retrieve logs for this Webservice.
get_logs(num_lines=5000, init=False)Parameters
Returns
The logs for this Webservice.
Return type
Exceptions
get_token
Retrieve auth token for this Webservice, scoped to the current user.
get_token()Returns
The auth token for this Webservice and when it should be refreshed after.
Return type
Exceptions
list
List the Webservices associated with the corresponding Workspace.
The results returned can be filtered using parameters.
static list(workspace, compute_type=None, image_name=None, image_id=None, model_name=None, model_id=None, tags=None, properties=None, image_digest=None)Parameters
- compute_type
- str
Filter to list only specific Webservice types. Options are 'ACI', 'AKS'.
- image_name
- str
Filter list to only include Webservices deployed with the specific image name.
- image_id
- str
Filter list to only include Webservices deployed with the specific image ID.
- model_name
- str
Filter list to only include Webservices deployed with the specific model name.
- model_id
- str
Filter list to only include Webservices deployed with the specific model ID.
- tags
- list
Filter based on the provided list, by either 'key' or '[key, value]'. Ex. ['key', ['key2', 'key2 value']]
- properties
- list
Filter based on the provided list, by either 'key' or '[key, value]'. Ex. ['key', ['key2', 'key2 value']]
- image_digest
- str
Filter list to only include Webservices deployed with the specific image digest.
Returns
A filtered list of Webservices in the provided Workspace.
Return type
Exceptions
regen_key
Regenerate one of the Webservice's keys, either the 'Primary' or 'Secondary' key.
A WebserviceException is raised if key is not specified or is not 'Primary'
or 'Secondary'.
regen_key(key, set_key=None)Parameters
- set_key
- str
A user specified value allowing for manual specification of the key's value
Exceptions
run
Call this Webservice with the provided input.
Abstract method implemented by child classes of Webservice.
abstract run(input)Parameters
- input
- <xref:varies>
The input data to call the Webservice with. This is the data your machine learning model expects as an input to run predictions.
Returns
The result of calling the Webservice. This will return predictions run from your machine learning model.
Return type
Exceptions
serialize
Convert this Webservice object into a JSON serialized dictionary.
Use deserialize to convert back into a Webservice object.
serialize()Returns
The JSON representation of this Webservice.
Return type
Exceptions
update
Update the Webservice parameters.
This is an abstract method implemented by child classes of Webservice. Possible parameters to update vary based on Webservice child type. For example, for Azure Container Instances webservices, see update for specific parameters.
abstract update(*args)Parameters
- args
- <xref:varies>
Values to update.
Exceptions
update_deployment_state
Refresh the current state of the in-memory object.
Perform an in-place update of the properties of the object based on the current state of the corresponding cloud object. Primarily useful for manual polling of creation state.
update_deployment_state()Exceptions
wait_for_deployment
Automatically poll on the running Webservice deployment.
Wait for the Webservice to reach a terminal state. Will throw a WebserviceException if it reaches a non-successful terminal state or exceeds the provided timeout.
wait_for_deployment(show_output=False, timeout_sec=None)Parameters
Exceptions
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