Utilities for connection mlrun to cloud services
Project description
mlrun_connect
A collection of tools to simplify integration between MLRun and services from cloud providers.
Quickstart
The package can be installed using:
pip install mlrun_connect
MLRun is an open-source MLOps orchestration framework. It enables end-to-end development of machine learning models, from exploratory data analysis to prototyping to operationalization.
A common use case would be to install MLRun on-premise or with a cloud provider, and connect to data sources for exploratory analysis. While the Nuclio library offers a HTTP-based approach to integration with external services, there are a variety of other approaches that may be prefered (i.e. messaging systems).
mlrun_connect will provide tools to ease integration with these services.
Azure Service Bus Queue
The AzureSBTMLRun class can be in conjunction with a Nuclio function to initiate the execution of a mlrun pipeline based on an incoming message. The AzureSBToMLRun object becomes the parent to a new class that is instantiated within the Nuclio init_context function, as follows:
from mlrun_connect.azure import AzureSBToMlrun
def init_context(context):
pipeline = load_project(<PATH_TO_MLRUN_PROJECT>)
class SBHandler(AzureSBToMLRun):
def run_pipeline(self, event):
arguments = {"incoming_data": event["key"]}
workflow_id = pipeline.run(arguments = arguments)
return workflow_id
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