How Dream11 Transforms User Experience: How Dream11 Leverages Intelligent Image Delivery
Original post Transforming User Experience: How Dream11 Leverages Intelligent Image Delivery | by Dream Blog | Dream Locker Room | Medium
Article Summary
Dream11 serves 15 million concurrent users during IPL peaks. Their image delivery costs were spiraling until they made one architectural change.
Dream11's engineering team tackled a classic mobile performance problem: delivering high-resolution player images across diverse devices without killing load times or bandwidth budgets. They turned to AWS Serverless Image Handler to dynamically optimize images based on device capabilities.
Key Takeaways
- Reduced image payload by 300 images per session through device-specific optimization
- Cut egress costs by 70% using CloudFront CDN with Lambda@Edge processing
- Converted images to WebP and resized based on device pixel density
- Built URL mapping system to route images across multiple S3 buckets
- Excluded GIF formats while optimizing JPG and PNG assets automatically
Dream11 slashed bandwidth usage and cut cloud egress costs by 70% while improving load times through intelligent, device-aware image delivery.
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What This Article Covers
Dream11 was struggling with high network usage and slow load times. Delivering high-resolution images to Android and iOS devices with different screen sizes and pixel densities was expensive in terms of egress costs.
Dream11 set up AWS Serverless Image Handler using CloudFormation templates. They connected CloudFront CDN and Lambda@Edge functions, then added the Sharp image processing library to resize images and convert them to WebP format based on what device was requesting them.
After the changes, image payload dropped by about 300 images per session. Egress costs fell by roughly 70%. Image quality stayed the same and pages loaded faster for users.
This page summarizes “Transforming User Experience: How Dream11 Leverages Intelligent Image Delivery | by Dream Blog | Dream Locker Room | Medium” by Dream11, published Mar 13, 2025. All credit for the original work goes to the authors.
