Build a Serverless Image Processing Pipeline with Azure Functions

In this lab, you will build a fully serverless image processing pipeline on Azure. When an image is uploaded to a Blob Storage "uploads" container, a blob-triggered Azure Function automatically detects the new file, generates multiple thumbnail sizes, stores them in an "output" container, and writes metadata (original filename, dimensions, thumbnail URLs, processing timestamp) to Azure Table Storage. This pattern mirrors how services like Cloudinary and Imgix work behind the scenes and is widely used by content platforms, SaaS applications, and media pipelines.

You will work with Azure Functions blob triggers on the Flex Consumption plan, the Sharp image processing library in Node.js, Azure Blob Storage and Table Storage output bindings, and Azure Event Grid subscriptions for low-latency event delivery. Along the way, you will learn how Event Grid pushes blob events to your function, how to process binary data inside a serverless function, and how to write structured metadata for downstream consumers.

Objectives

Upon completing this Intermediate level lab, you will be able to:

• Build a blob-triggered Azure Function that uses the Sharp library to generate multiple thumbnail sizes and write them to Blob Storage
• Persist image metadata (filename, dimensions, sizes, timestamps) to Azure Table Storage using output bindings
• Wire blob events from a Storage Account to a Flex Consumption Function App by creating an Event Grid subscription
• Validate the end-to-end serverless pipeline by uploading images and confirming thumbnails and metadata appear automatically

Who is this lab for?

This lab is designed for:

• Cloud developers who want hands-on experience building event-driven serverless pipelines on Azure
• Full-stack and SaaS engineers looking to implement automated image processing without managing servers
• Content platform builders who need scalable, cost-effective media processing patterns