feast-dev/feast

AI Summary: Improve the error message when input columns don't match expected columns during data insertion into the Feast feature store. The current error message is difficult to read, especially with many features. The task involves modifying the exception handling in the Feast Python SDK to clearly list missing and extra columns.

AI Summary: Create a dedicated documentation page for deploying and managing Feast on Kubernetes, covering the Feast operator and related Kubernetes deployment aspects. This involves consolidating existing information from the current 'Running Feast in Production' guide and expanding it into a comprehensive, standalone page.

AI Summary: The task is to refactor the Feast library to make the `transformers` library an optional dependency. This will improve the import time for users who don't need the NLP features provided by `transformers`, allowing for a faster startup time for basic feature management tasks.