Hi <!channel>! We have just released BentoML 1.0.0rc2 with an exciting lineup of improvements. Checkout it out with the following command!

$ pip install -U bentoml --pre

• Standardized logging configuration and improved logging performance. ◦ If imported as a library, BentoML will no longer configure logging explicitly and will respect the logging configuration of the importing Python process. To customize BentoML logging as a library, configurations can be added for the

bentoml

logger.

formatters:
  ...
handlers:
  ...
loggers:
  ...
  bentoml:
    handlers: [...]
    level: INFO
    ...

◦ If started as a server, BentoML will continue to configure logging format and output to

stdout

at

INFO

level. All third party libraries will be configured to log at the

WARNING

level. • Added LightGBM framework support. 🎉 • Updated model and bento creation timestamps CLI display to use the local timezone for better use experience, while timestamps in metadata will remain in the UTC timezone. • Improved the reliability of bento build with advanced options including base_image and dockerfile_template. Beside all the exciting product work, we also started a blog at modelserving.com sharing our learnings gained from building BentoML and supporting the MLOps community. Checkout our latest blog Breaking up with Flask &amp; FastAPI: Why ML model serving requires a specialized framework (share your thoughts with us on our LinkedIn post). Lastly, a big shoutout to @Mike Kuhlen for adding the LightGBM framework support. 🥂