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If the user is not packaging individually, then we can create one Lambda Layer with the python requirements, and the functions just use that layer, rather than having to have the packages in each function deployment.
If they are packaging individually, then maybe there's the option of specifying which ones are common and therefore can go into a layer. This will make the package and upload process faster, and also resulting lambda deployment package smaller (as they will share the layer)
whilst I write this I spotted a blog of someone else doing this:
I am flat out and have no time to do this, so I'll write it here in case someone else does - or at least start a conversation about it.
Now that Lambda has the concept of Layers, it would be great if we can utilise them for common python dependencies
https://docs.aws.amazon.com/lambda/latest/dg/configuration-layers.html#configuration-layers-path
If the user is not packaging individually, then we can create one Lambda Layer with the python requirements, and the functions just use that layer, rather than having to have the packages in each function deployment.
If they are packaging individually, then maybe there's the option of specifying which ones are common and therefore can go into a layer. This will make the package and upload process faster, and also resulting lambda deployment package smaller (as they will share the layer)
whilst I write this I spotted a blog of someone else doing this:
https://nordcloud.com/lambda-layers-for-python-runtime/
so.. what you reckon?
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