‫Okay, so now let's talk about Lambda Layers.
‫They're a newer feature of Lambda,
‫and they allow us to do two things.
‫Number one is to create custom run times for Lambda.
‫So that means languages that are not meant
‫for Lambda initially,
‫but that the community has decided to support
‫through Lambda Layers.
‫So we have C++, and we have Rust, for example.
‫So these are two examples that allow you
‫to use a C++ language or the Rust language
‫onto Lambda functions.
‫The other more common use case for Lambda Layers
‫is to externalize dependencies in order to reuse them.
‫So, if we look at a zipped application package,
‫it could be pretty big, we have a Lambda function
‫and there'd be some heavy libraries, heavy dependencies.
‫And so that's maybe 30 megabytes.
‫And we saw that to update another function,
‫we need to re-upload that zip over and over and over again.
‫So that would mean that every time
‫we repack your application and re-upload everything,
‫but sometimes the dependencies we're using are not changing
‫or are changing very, very, very slowly.
‫And so it would be better to externalize them
‫into what's called a layer.
‫So the goal is to have your application package
‫which is what you could change very,
‫very often your code externalize.
‫So this has maybe 20 kilobytes, so very, very small.
‫And then you have created layers for your heavy libraries.
‫So you've created a first and then the layer of 10 megabyte
‫the second limited layer of 30 megabytes
‫and these layers together can be referencing your function
‫and sorry your functioning can be referencing your layers,
‫obviously, and therefore we have a much faster way to
‫deploy our functions
‫and we don't need to repackage every time our dependencies
‫and because our layers are externalized, another function
‫another application package could create another function
‫maybe 60 kilobytes and reference these, same layers.
‫So this the whole purpose
‫we are packaging our application dependencies and layers
‫and we can reuse them across Lynda functions.
‫Now let's go in the hands-on to see how that works.