Managed MLflow and Managed Delta Lake on Azure Databricks are now available
Updated: June 19, 2019
Managed MLflow is now generally available on Azure Databricks and will use Azure Machine Learning to track the full ML lifecycle. This approach enables organizations to develop and maintain their machine learning lifecycle using a single model registry on Azure. The combination of Azure Databricks and Azure Machine Learning makes Azure the best cloud for machine learning. In addition to being able to deploy models from the cloud to the edge, customers benefit from an optimized, autoscaling Apache Spark based environment, collaborative workspace, automated machine learning, and end-to-end Machine Learning Lifecycle management.
Additionally, Databricks has open sourced Databricks Delta, now known as Delta Lake. Delta Lake is an engine built on top of Apache Spark for optimizing data pipelines. With Delta Lake, Azure Databricks customers get greater reliability, improved performance, and the ability to simplify their data pipelines. Azure Databricks customers have been experiencing the benefits of the Delta engine in general availability since February, and they will continue to enjoy the innovations from the community going forward with the open source Delta Lake project.