Deploy a Serverless Image Processing Pipeline

INTERMEDIATE

120 minutes

3 tasks

Build a serverless image processing pipeline using AWS services. This project will guide you through setting up an automated workflow to process images uploaded to an S3 bucket, using Lambda, and store processed images in another S3 bucket.

Sandbox access coming soon

Scenario

Acme Corp, a digital media company, requires an automated solution to process client-uploaded images. The task is to build a serverless pipeline that resizes images upon upload to a specific S3 bucket, applying filters and saving the processed images to a different bucket for easy retrieval.

Learning Objectives

Understand AWS serverless architecture
Implement AWS Lambda functions for image processing
Configure S3 buckets and event notifications
Deploy and test serverless workflows

tasks (3)

task 1: Set up two S3 buckets: one for input images and another for output images. Configure the first bucket to trigger a Lambda function upon file upload.

20 min

task 2: Write a Lambda function in Python to resize images and apply a grayscale filter.

30 min

task 3: Test the Lambda function by uploading sample images to the input S3 bucket.