This repo provides a customizable stack for starting new ML projects on Databricks that follow production best-practices out of the box.
This module sets up multi-workspace model registry between an Azure Databricks development (dev) workspace, staging workspace, and production (prod) workspace, allowing READ access from dev/staging workspaces to staging & prod model registries. It also links pre-existing Azure Active Directory (AAD) applications to the service principals.
This module sets up multi-workspace model registry between a Databricks AWS development (dev) workspace, staging workspace, and production (prod) workspace, allowing READ access from dev/staging workspaces to staging & prod model registries.
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This repo provides a customizable stack for starting new ML projects on Databricks that follow production best-practices out of the box.
Last updated: 6 days agoThis module sets up multi-workspace model registry between an Azure Databricks development (dev) workspace, staging workspace, and production (prod...
Last updated: 6 days agoThis module sets up multi-workspace model registry between a Databricks AWS development (dev) workspace, staging workspace, and production (prod) w...
Last updated: 6 days agoBazel rules for building Protobuf and gRPC code and libraries from proto_library targets
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