# Amazon S3 and AWS Step Functions Express Workflow for processing large files

This pattern creates a Lambda function that puts an object to S3 and starts a synchronous Step Functions Express Workflow.

This pattern is useful when processing uploaded files larger than the current [task execution limits](https://docs.aws.amazon.com/step-functions/latest/dg/limits.html#service-limits-task-executions).

Learn more about this pattern at Serverlessland Patterns: https://serverlessland.com/patterns/lambda-s3-sfn.

Important: this application uses various AWS services and there are costs associated with these services after the Free Tier usage - please see the [AWS Pricing page](https://aws.amazon.com/pricing/) for details. You are responsible for any AWS costs incurred. No warranty is implied in this example.

## Requirements

* [Create an AWS account](https://portal.aws.amazon.com/gp/aws/developer/registration/index.html) if you do not already have one and log in. The IAM user that you use must have sufficient permissions to make necessary AWS service calls and manage AWS resources.
* [AWS CLI](https://docs.aws.amazon.com/cli/latest/userguide/install-cliv2.html) installed and configured
* [Git Installed](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)
* [AWS Serverless Application Model](https://docs.aws.amazon.com/serverless-application-model/latest/developerguide/serverless-sam-cli-install.html) (AWS SAM) installed

## Deployment Instructions

1. Create a new directory, navigate to that directory in a terminal and clone the GitHub repository:
    ``` 
    git clone https://github.com/aws-samples/serverless-patterns
    ```
1. Change directory to the pattern directory:
    ```
    cd lambda-s3-sfn
    ```
1. From the command line, use AWS SAM to deploy the AWS resources for the pattern as specified in the template.yml file:
    ```
    sam deploy --guided
    ```
1. During the prompts:
    * Enter a stack name
    * Enter the desired AWS Region
    * Allow SAM CLI to create IAM roles with the required permissions.

    Once you have run `sam deploy --guided` mode once and saved arguments to a configuration file (samconfig.toml), you can use `sam deploy` in future to use these defaults.

1. Note the outputs from the SAM deployment process. These contain the resource names and/or ARNs which are used for testing.

## How it works

* Invoke SavePayloadAndStartStateMachineFunction Lambda function with a "payload" string in the input payload
* SavePayloadAndStartStateMachineFunction stores the payload in S3 and starts an Express Workflow passing the bucket and key
* Express Workflow calls the ProcessFileFunction, retrieves the uploaded json using the bucket/key, converts to uppercase, and returns it
* Express Workflow calls the AddFooterFunction function, adds a footer and returns it
* Express Workflow ends and returns the result to the client

## Testing

Run the following AWS CLI command to invoke function to start the Step Functions workflow. Note, you must edit the {SavePayloadAndStartStateMachineFunction} placeholder with the ARN of the deployed lambda function. This is provided in the stack outputs.
You can also replace payload with something that is bigger than the current task execution limit (262kb).
```bash
aws lambda invoke --function-name {SavePayloadAndStartStateMachineFunction}  --payload '{ "payload": "hello world"}' --cli-binary-format raw-in-base64-out response.json
```

## Cleanup
 
1. Empty/delete S3 bucket and delete the stack:
    ```bash
   aws s3 rm s3://lambda-s3-sfn-uploads --recursive && aws cloudformation delete-stack --stack-name STACK_NAME 
    ```
1. Confirm the stack has been deleted:
    ```bash
    aws cloudformation list-stacks --query "StackSummaries[?contains(StackName,'STACK_NAME')].StackStatus"
    ```
----
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