How to do it...

1. Create the project from the following template:

$ sls create --template-url https://github.com/danteinc/js-cloud-native-cookbook/tree/master/ch2/data-lake-s3 --path cncb-data-lake-s3

2. Navigate to the cncb-data-lake-s3 directory with cd cncb-data-lake-s3.
3. Review the file named serverless.yml with the following content:

service: cncb-data-lake-s3

provider:
  name: aws
  runtime: nodejs8.10

functions:
  transformer:
    handler: handler.transform
    timeout: 120

resources:
  Resources:
    Bucket:
      Type: AWS::S3::Bucket
      DeletionPolicy: Retain
    DeliveryStream:
      Type: AWS::KinesisFirehose::DeliveryStream
      Properties:
        DeliveryStreamType: KinesisStreamAsSource      
        KinesisStreamSourceConfiguration: 
          KinesisStreamARN: ${cf:cncb-event-stream-${opt:stage}.streamArn}
          ...
        ExtendedS3DestinationConfiguration:
          BucketARN:
            Fn::GetAtt: [ Bucket, Arn ]
          Prefix: ${cf:cncb-event-stream-${opt:stage}.streamName}/
          ...

  Outputs:
    DataLakeBucketName:
      Value:
        Ref: Bucket

4. Review the file named handler.js with the following content:

exports.transform = (event, context, callback) => {
  const output = event.records.map((record, i) => {
    // store all available data
    const uow = {
      event: JSON.parse((Buffer.from(record.data, 'base64')).toString('utf8')),
      kinesisRecordMetadata: record.kinesisRecordMetadata,
      firehoseRecordMetadata: {
        deliveryStreamArn: event.deliveryStreamArn,
        region: event.region,
        invocationId: event.invocationId,
        recordId: record.recordId,
        approximateArrivalTimestamp: record.approximateArrivalTimestamp,
      }
    };

    return {
      recordId: record.recordId,
      result: 'Ok',
      data: Buffer.from(JSON.stringify(uow) + '\n', 'utf-8').toString('base64'),
    };
  });

  callback(null, { records: output });
};

5. Install the dependencies with npm install.
6. Run the tests with npm test -- -s $MY_STAGE.
7. Review the contents generated in the .serverless directory.
8. Deploy the stack:

$ npm run dp:lcl -- -s $MY_STAGE

> cncb-data-lake-s3@1.0.0 dp:lcl <path-to-your-workspace>/cncb-data-lake-s3
> sls deploy -v -r us-east-1 "-s" "john"

Serverless: Packaging service...
...
Serverless: Stack update finished...
...
Stack Outputs
DataLakeBucketName: cncb-data-lake-s3-john-bucket-1851i1c16lnha
...

9. Review the stack, data lake bucket, and Firehose delivery stream in the AWS Console.
10. Publish an event from a separate Terminal with the following commands:

$ cd <path-to-your-workspace>/cncb-event-stream
$ sls invoke -r us-east-1 -f publish -s $MY_STAGE -d '{"type":"thing-created"}'
{
    "ShardId": "shardId-000000000000",
    "SequenceNumber": "49582906351415672136958521360120605392824155736450793474"
}

11. Allow the Firehose buffer time to process and then review the data lake contents created in the S3 bucket.

12. Remove the stack once you have finished with npm run rm:lcl -- -s $MY_STAGE.