Endpoint

class verta.endpoint.Endpoint(conn, conf, workspace, id)

Object representing an endpoint for deployment.

There should not be a need to instantiate this class directly; please use Client.get_or_create_endpoint().

New in version 0.19.0: The kafka_settings attribute.

Variables:
  • id (int) – ID of this endpoint.

  • kafka_settings (verta.endpoint.KafkaSettings or None) – Kafka settings on this endpoint.

  • path (str) – Path of this endpoint.

  • url (str) – Verta web app URL.

create_access_token(token)

Create an access token for the endpoint.

Parameters:

token (str) – Token to create.

delete()

Delete this endpoint.

get_access_token()

Get an arbitrary access token of the endpoint.

Returns:

str or None

get_access_tokens()

Return all existing tokens of the endpoint.

Returns:

list of str

get_current_build()

Retrieve the currently deployed build for this endpoint.

May return None if no build has been deployed to this endpoint.

Returns:

Build or None – A build object with an id and status.

get_deployed_model(credentials=None)

Return an object for making predictions against the deployed model.

Parameters:

credentials (Credentials, optional) – Authentication credentials to use with this deployed model. Credentials will be inferred from the environment if not explicitly provided.

Returns:

DeployedModel

Raises:

RuntimeError – If the model is not currently deployed.

get_logs()

Get runtime logs of this endpoint.

Returns:

list of str – Lines of this endpoint’s runtime logs.

get_status()

Get status of the endpoint.

Returns:

status (dict of str to {None, bool, float, int, str, list, dict})

get_update_status()

Get update status on the endpoint.

Returns:

update_status (dict of str to {None, bool, float, int, str, list, dict})

property kafka_settings

Get the Kafka settings for this endpoint.

property path

Get the HTTP path of this endpoint.

update(model_reference, strategy=None, wait=False, resources=None, autoscaling=None, env_vars=None, kafka_settings=None)

Update the endpoint with a model logged in an Experiment Run or a Model Version.

New in version 0.19.0: The kafka_settings parameter.

Parameters:
  • model_reference (ExperimentRun or RegisteredModelVersion or Build) – An Experiment Run, Model Version with a model logged, or a Build.

  • strategy (update, default DirectUpdateStrategy()) – Strategy (direct or canary) for updating the endpoint.

  • wait (bool, default False) – Whether to wait for the endpoint to finish updating before returning.

  • resources (Resources, optional) – Resources allowed for the updated endpoint.

  • autoscaling (Autoscaling, optional) – Autoscaling condition for the updated endpoint.

  • env_vars (dict of str to str, optional) – Environment variables.

  • kafka_settings (verta.endpoint.KafkaSettings or False, optional) – Kafka settings. If False, clears this endpoint’s existing Kafka settings.

Returns:

status (dict of str to {None, bool, float, int, str, list, dict})

update_from_config(filepath, wait=False)

Update the endpoint via a YAML or JSON config file.

Parameters:
  • filepath (str) – Path to the YAML or JSON config file.

  • wait (bool, default False) – Whether to wait for the endpoint to finish updating before returning.

Returns:

status (dict of str to {None, bool, float, int, str, list, dict})

Raises:

ValueError – If the file is not JSON or YAML.

wait_for_build(polling_seconds=5, msg=None)

Poll the endpoint status API until a build completes successfully or with an error.

Parameters:
  • polling_seconds (float, optional) – Number of seconds to sleep in between API calls.

  • msg (str, optional) – Progress string to print in between polling calls.

Returns:

Build – A completed build.