Amazon Web Services
docs.aws.amazon.com › aws lambda › developer guide › managing lambda dependencies with layers
Managing Lambda dependencies with layers - AWS Lambda
Using layers reduces your package size and can unlock usage of the code editor. To lock an embedded SDK version.The embedded SDKs may change without notice as AWS releases new services and features. You can lock a version of the SDK by creating a Lambda layer with the specific version needed.
Lambda Layers and CDK
Lambda layers is one of those features that _seem_ useful and turns out to be a nightmare in practice. Say for instance you keep your layers and functions using cloudformation. IaC, sane enough idea. layer L v1 is up. You deploy lambda A using it, all good and working. You update L so now it's v2. Next stack update for A has an issue, unrelated to the layer. Anything, random aws hiccup. The deployment rolls back. Ops, L v1 no longer exists, rollback failed, stack stuck.... Remove it all and do it again.... More on reddit.com
Is there any reason to use Lambda layers while using bundlers?
layers are just an orchestration tool, once the function is put together, it behaves very much like one package (aside from irrelevant differences). so the short answer is you don't need it if you already use an orchestration tool. More on reddit.com
Using multiple lambda functions to get around the size cap for layers.
This seems like a horribly unmaintainable messy solution when the correct solution is just to spend a day learning how containers work and implement things that way. More on reddit.com
Create Multiple lambda layers with serverless-framework
Just look at the aws layer documentation and create that resource in your serverless file under resources. That’s how I do it at least. In may just be my inexperience with layers but you can’t require dependencies in them, at least I wasn’t able to figure that out. I still list them as dependencies in the layer, but as long as the dependencies are in the lambda you are using that layer with it works. I don’t use layers much so take this with a grain of salt as I’m not sure if there’s a better/easier way. It’s pretty easy tho IMO which is why I’ve stuck with this process. And then I use yarn workspaces for local dev/testing to actually use those layers just as they would on aws. So it all works the same whether it’s local or cloud. More on reddit.com
Videos
08:56
How to create & use Lambda layers using AWS - YouTube
17:38
AWS Lambda Layers Step by Step Tutorial | Python Libraries Management ...
06:43
How to create and use Lambda Layers in AWS in under 7 minutes - ...
11:07
AWS Lambda Layers Crash Course - YouTube
09:30
Create Lambda Layers | Easily Add Python Dependencies to Lambda ...
06:40
AWS Lambda Layers | How to create and use Layers in Lambda Functions ...
Keras
keras.io › api › layers › core_layers › lambda
Keras documentation: Lambda layer
Wraps arbitrary expressions as a Layer object. The Lambda layer exists so that arbitrary expressions can be used as a Layer when constructing Sequential and Functional API models.
GeeksforGeeks
geeksforgeeks.org › devops › layers-in-aws-lambda
Layers in AWS Lambda - GeeksforGeeks
July 23, 2025 - AWS Lambda refers to the compute service without servers that allows you to execute codes without needing to setup or maintain the digital machines. One of the great feature it has is Lambda Layers which enables people to package and distribute libraries, custom runtime, as well as other dependencies between various Lambda functions.
Amazon Web Services
docs.aws.amazon.com › aws lambda › developer guide › building lambda functions with python › working with layers for python lambda functions
Working with layers for Python Lambda functions - AWS Lambda
Use Lambda layers to package code and dependencies that you want to reuse across multiple functions. Layers usually contain library dependencies, a custom runtime, or configuration files.
GitHub
github.com › mthenw › awesome-layers
GitHub - mthenw/awesome-layers: λ A curated list of awesome AWS Lambda Layers. Sponsored by https://cloudash.dev · GitHub
Lambda Layers are a new type of artifact that can contain arbitrary code and data, and may be referenced by zero, one, or more functions at the same time. Lambda functions in a serverless application typically share common dependencies such ...
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Amazon Web Services
docs.aws.amazon.com › aws lambda › developer guide › managing lambda dependencies with layers › adding layers to functions
Adding layers to functions - AWS Lambda
A Lambda layer is a .zip file archive that contains supplementary code or data.
Reddit
reddit.com › r/aws › lambda layers and cdk
r/aws on Reddit: Lambda Layers and CDK
May 16, 2024 -
I'm struggling to understand the best way to utilize Lambda Layers shared by multiple CDK stacks. Currently, I have a stack which only deploys the new layer versions. Then I pass the ARN of these layers to the stacks which will use them. But I'm running into an issue where the Layer stack can then not be updated because there are functions using them. I would have thought that this was similar to ECR where you can create a new version but you cannot delete the version being used by a deployment. Sorry I have no code I can share, but I am using the `PythonVersionConstruct` to create the layers.
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Lambda layers is one of those features that _seem_ useful and turns out to be a nightmare in practice. Say for instance you keep your layers and functions using cloudformation. IaC, sane enough idea. layer L v1 is up. You deploy lambda A using it, all good and working. You update L so now it's v2. Next stack update for A has an issue, unrelated to the layer. Anything, random aws hiccup. The deployment rolls back. Ops, L v1 no longer exists, rollback failed, stack stuck.... Remove it all and do it again....
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Issues like this are a big reason why we stopped using layers. Do you actually need them? https://aaronstuyvenberg.com/posts/why-you-should-not-use-lambda-layers