# Running locally

You can start the application on `localhost:8080` with SAM CLI. If you haven't installed SAM CLI, please refer to the README.md in the root of this project.
```shell script
sam local start-api --port 8080 --env-vars env.json
```

# training-pipeline

This project contains source code and supporting files for a serverless application that you can deploy with the SAM CLI. It includes the following files and folders:

- functions - Code for the application's Lambda functions 
- statemachine - Definition for the state machine that orchestrates the training workflow.
- tests - Example payload for testing function locally with `sam local invoke`.
- template.yaml - A template that defines the application's AWS resources.

This application creates a training pipeline (with AWS Step Functions), DynamoDB tables, and APIs.

AWS Step Functions lets you coordinate multiple AWS services into serverless workflows so you can build and update apps quickly. Using Step Functions, you can design and run workflows that stitch together services. In our case, the workflow will run AWS SageMaker for training and creating ML resources, and AWS DynamoDB to persist status of each step. 

## IDE Integration

If you prefer to use an integrated development environment (IDE) to build and test the Lambda functions within your application, you can use the AWS Toolkit. The AWS Toolkit is an open source plug-in for popular IDEs that uses the SAM CLI to build and deploy serverless applications on AWS. The AWS Toolkit also adds a simplified step-through debugging experience for Lambda function code. See the following links to get started:

* [PyCharm](https://docs.aws.amazon.com/toolkit-for-jetbrains/latest/userguide/welcome.html)
* [IntelliJ](https://docs.aws.amazon.com/toolkit-for-jetbrains/latest/userguide/welcome.html)
* [VS Code](https://docs.aws.amazon.com/toolkit-for-vscode/latest/userguide/welcome.html)
* [Visual Studio](https://docs.aws.amazon.com/toolkit-for-visual-studio/latest/user-guide/welcome.html)

The AWS Toolkit for VS Code includes full support for state machine visualization, enabling you to visualize your state machine in real time as you build. The AWS Toolkit for VS Code includes a language server for Amazon States Language, which lints your state machine definition to highlight common errors, provides auto-complete support, and code snippets for each state, enabling you to build state machines faster.

## Deploy the sample application

This application requires resources in <root>/shared-infra to work. Please refer to README.md in the root folder of this project for instruction. 

## Use the SAM CLI to build locally

Build the Lambda functions in your application with the `sam build --use-container` command.

```bash
sam build --use-container
```

The SAM CLI installs dependencies defined in `functions/*/requirements.txt`, creates a deployment package, and saves it in the `.aws-sam/build` folder.


## Fetch, tail, and filter Lambda function logs

To simplify troubleshooting, SAM CLI has a command called `sam logs`. `sam logs` lets you fetch logs generated by your deployed Lambda function from the command line. In addition to printing the logs on the terminal, this command has several nifty features to help you quickly find the bug.

`NOTE`: This command works for all AWS Lambda functions; not just the ones you deploy using SAM.

```bash
sam logs -n $FUNCTION_NAME --stack-name $STACK_NAME --tail
```

You can find more information and examples about filtering Lambda function logs in the [SAM CLI Documentation](https://docs.aws.amazon.com/serverless-application-model/latest/developerguide/serverless-sam-cli-logging.html).

## Cleanup

To delete the sample application that you created, use the AWS CLI. Assuming you used your project name for the stack name, you can run the following:

```bash
aws cloudformation delete-stack --stack-name $STACK_NAME
```

## Resources

See the [AWS SAM developer guide](https://docs.aws.amazon.com/serverless-application-model/latest/developerguide/what-is-sam.html) for an introduction to SAM specification, the SAM CLI, and serverless application concepts.

Next, you can use AWS Serverless Application Repository to deploy ready to use Apps that go beyond hello world samples and learn how authors developed their applications: [AWS Serverless Application Repository main page](https://aws.amazon.com/serverless/serverlessrepo/)