ETL pipeline with Amazon Redshift and AWS Glue

This example lives in the pulumi/examples repository. Check out just this directory to use it:

$ git clone --filter=blob:none --sparse https://github.com/pulumi/examples pulumi-examples
$ git -C pulumi-examples sparse-checkout set aws-py-redshift-glue-etl
$ cd pulumi-examples/aws-py-redshift-glue-etl

This example creates an ETL pipeline using Amazon Redshift and AWS Glue. The pipeline extracts data from an S3 bucket with a Glue crawler, transforms it with a Python script wrapped in a Glue job, and loads it into a Redshift database deployed in a VPC.

Prerequisites#

1. Install Pulumi.
2. Install Python.
3. Configure your AWS credentials.

Deploying the App#

1. Clone this repo, change to this directory, then create a new stack for the project:

   pulumi stack init

2. Specify an AWS region to deploy into:

   pulumi config set aws:region us-west-2

3. Install Python dependencies and run Pulumi:

   python3 -m venv venv
   source venv/bin/activate
   pip install -r requirements.txt
   
   pulumi up

4. In a few moments, the Redshift cluster and Glue components will be up and running and the S3 bucket name emitted as a Pulumi stack output.

   ...
   Outputs:
       dataBucketName: "events-56e424a"

5. Upload the included sample data file to S3 to verify the automation works as expected:

   aws s3 cp events-1.txt s3://$(pulumi stack output dataBucketName)

6. When you’re ready, destroy your stack and remove it:

   pulumi destroy --yes
   pulumi stack rm --yes