I'm not aware of a publicly available tool that does this (without bringing in a big clumsy framework), but internally we just use a script that idempotently re

I'm not aware of a publicly available tool that does this (without bringing in a big clumsy framework), but internally we just use a script that idempotently redeploys all the lambdas by calling update_function_code on them. It ingests package dependency changes by running "python setup.py install" and grabbing the resulting site-packages contents. This script can be subscribed to an SNS-SQS bus that listens to GitHub notifications for changes on a branch, etc. This will flush hot lambdas, so if you have a lot of traffic it can be a bit disruptive. I can imagine comparing deployment and commit timetamps make-style, or calling update_function_configuration(Description=...) to save and later compare version/commit metadata. AWS recently came out with https://github.com/awslabs/chalice https://github.com/awslabs/chalice, which is pretty sweet if you're using Python (although it doesn't seem to directly address the concern of deployment orchestration).