Two Lambda functions use the same large Python library, and both deployment packages are approaching the zipped size limit. To reduce package size with the least operational overhead, what should the developer do?

Creating a Lambda layer for the shared Python library is the most efficient solution. Lambda layers allow you to centralize common code and dependencies, reducing the size of individual deployment packages and promoting code reuse. This approach has minimal operational overhead because you manage the library once in the layer, and both functions automatically inherit it. Packaging each library in its own .zip file and deploying copies defeats the purpose of reducing package size and increases redundancy. Merging the two functions into one might exceed memory or execution time limits, and it couples unrelated logic. Uploading the library to S3 and referencing it at runtime is not a standard or performant way to include dependencies for Lambda functions; dependencies should be part of the deployment package or a layer.