Client-Side Image Compression Before Upload: The Story Behind Compressly
How client-side image compression saves thousands in bandwidth, accelerates upload speeds tenfold, and boosts Core Web Vitals.

The Universal Developer Nightmare
If you are a Frontend or Full-Stack Engineer, this scenario has almost certainly happened to you:
A user attempts to upload a profile avatar or product image taken directly with a modern smartphone camera. Suddenly, you discover that a single photo is 18MB or even 25MB in size!
How Most Teams Traditionally Handle This:
- 1Direct Validation (The Frustrating UX):
Rejecting the file outright if it exceeds 2MB. The user gets frustrated because they don't know how to resize images on their phone.
- 1Server-Side Resizing (The Expensive Route):
Accepting the 20MB payload, consuming immense server bandwidth, and burning CPU cycles running ImageMagick or Sharp workers in the cloud.
The Engineering Solution: Client-Side Compression with Compressly
Why upload 20MB of raw data over cellular networks when the browser has access to the HTML5 Canvas API and hardware-accelerated image decoders?
By compressing images in a Web Worker before sending the multipart form data:
- Upload Speed: An image that took 12 seconds to upload over mobile networks now uploads in 400 milliseconds.
- Server Cost: Bandwidth consumption drops by over 80%.
- Zero Server Overhead: The user's device handles the compression, freeing server resources.
This architectural realization led me to build and open-source Compressly—a lightweight, zero-dependency compression library for React, Next.js, and Vanilla JS.
Referenced Resources & Repositories
Official documentation, open-source repositories, and technical resources behind this piece.

Mostafa Mohamed Abdalla
AuthorSenior Frontend Engineer & Frontend Team Lead · Founder of Shadow Coding
Specializing in large-scale modern frontend architecture, BFF systems, web performance, and developer mentorship. Maintainer of open-source libraries including Compressly, Tonely, Accessly, and React Loadly.