terraform-aws-modules / terraform-aws-lambda

# AWS Lambda Terraform module
Terraform module, which creates almost all supported AWS Lambda resources as well as taking care of building and packaging of required Lambda dependencies for functions and layers.
This Terraform module is the part of serverless.tf framework, which aims to simplify all operations when working with the serverless in Terraform:
1. Build and install dependencies - read more. Requires Python 3.6 or newer.
2. Create, store, and use deployment packages - read more.
3. Create, update, and publish AWS Lambda Function and Lambda Layer - see usage.
4. Create static and dynamic aliases for AWS Lambda Function - see usage, see modules/alias.
5. Do complex deployments (eg, rolling, canary, rollbacks, triggers) - read more, see modules/deploy.
6. Use AWS SAM CLI to test Lambda Function - read more.
## Features
- Build dependencies for your Lambda Function and Layer.
- Support builds locally and in Docker (with or without SSH agent support for private builds) for any runtime and architecture supported by AWS Lambda.
- Create deployment package or deploy existing (previously built package) from local, from S3, from URL, or from AWS ECR repository.
- Store deployment packages locally or in the S3 bucket.
- Support almost all features of Lambda resources (function, layer, alias, etc.)
- Lambda@Edge
- Conditional creation for many types of resources.
- Control execution of nearly any step in the process - build, package, store package, deploy, update.
- Control nearly all aspects of Lambda resources (provisioned concurrency, VPC, EFS, dead-letter notification, tracing, async events, event source mapping, IAM role, IAM policies, and more).
- Support integration with other `serverless.tf` modules like HTTP API Gateway (see examples there).
## Usage
### Lambda Function (store package locally)
 [code] 
### Lambda Function and Lambda Layer (store packages on S3)
 [code] 
### Lambda Functions with existing package (prebuilt) stored locally
 [code] 
### Lambda Function or Lambda Layer with the deployable artifact maintained separately from the infrastructure
If you want to manage function code and infrastructure resources (such as IAM permissions, policies, events, etc) in separate flows (e.g., different repositories, teams, CI/CD pipelines).
Disable source code tracking to turn off deployments (and rollbacks) using the module by setting `ignore_source_code_hash = true` and deploy a _dummy function_.
When the infrastructure and the dummy function is deployed, you can use external tool to update the source code of the function (eg, using AWS CLI) and keep using this module via Terraform to manage the infrastructure.
Be aware that changes in `local_existing_package` value may trigger deployment via Terraform.
 [code] 
### Lambda Function with existing package (prebuilt) stored in S3 bucket
Note that this module does not copy prebuilt packages into S3 bucket. This module can only store packages it builds locally and in S3 bucket.
 [code] 
### La