Serverless Pipeline using AWS CDK and Lambda in Python

In this project, we will create a serverless pipeline using AWS CDK (Cloud Development Kit) and Lambda in Python. As a part of this, we will create a simple pipeline that triggers a Lambda function when a change is made to a specific S3 bucket. For this pipeline, we will use AWS CDK to define and deploy the infrastructure in the form of stacks.

To begin with, make sure you have the AWS CDK installed and configured on your system. Check the gettingstartedwithcdk.md file in this repository if you haven't.You'll also need to have Python and Node.js installed. Let's understand each step in detail as follows:

Step 1: Create a New AWS CDK Project

Open a terminal and create a new AWS CDK Project as follows:

mkdir serverless-pipeline
cd serverless-pipeline
cdk init app --language=python

Step 2: Install necessary CDK and AWS SDK libraries

The next step includes installing necessary CDK and AWS SDK libraries required for the project

pip install aws-cdk.core aws-cdk.aws-s3 aws-cdk.aws-lambda aws-cdk.aws-events aws-cdk.aws-events-targets

Step 3: Define the CDK Stack

In this, we'll be using Python to define and deploy the stack to AWS.The code used to define the stack in this project is included in the CDK-stack file of this repository. In your project directory, open the serverless_pipeline/serverless_pipeline_stack.py file and define the stack.

Step 4: Create the Lambda function

In the root of your project directory, create a folder named lambda. Inside this folder, create a lambda.py file and define the Lambda function using Python.

Step 5: Deploy the CDK Stack

Deploy the Stack by running

cdk deploy

Step 6: Testing the Pipeline

Upload a file to the S3 bucket you created earlier using the Stack, and you should see the Lambda function being triggered by the S3 event.

This created a simple serverless pipeline using AWS CDK and Lambda in Python. You can expand upon this example by adding more stages to your pipeline or integrating with other AWS services as needed for your specific use case.