Google Cloud has announced the launch of Cloud AI Platform Pipelines, to help deploy machine learning (ML) pipelines.
“A machine learning workflow can involve many steps with dependencies on each other, from data preparation and analysis, to training, to evaluation, to deployment, and more,” writes Anusha Ramesh, Product Manager, TFX. “It’s hard to compose and track these processes in an ad-hoc manner—for example, in a set of notebooks or scripts—and things like auditing and reproducibility become increasingly problematic.”
Cloud AI Platform Pipelines is designed to help alleviate the challenges of creating an ML pipeline with all the necessary dependencies. The new platform provides a way to “deploy robust, repeatable machine learning pipelines along with monitoring, auditing, version tracking, and reproducibility, and delivers an enterprise-ready, easy to install, secure execution environment for your ML workflows.”
The new tool has two parts. The first is the enterprise-ready infrastructure the ML workflows will run on, and the second is the tools for creating the ML pipelines and components. Cloud AI Platform Pipelines has push-button installation in the Google Cloud Console and supports both the Kubeflow Pipelines SDK and the TFX SDK.
Google Cloud’s new tool is available as a beta and should be a welcome addition for customers eager to add artificial intelligence and ML workflows to their cloud environments.
