Can you build a video streaming platform?

Yes. We implement video upload, transcoding to HLS/DASH adaptive bitrate streams, DRM protection, thumbnail generation, and video player integration. The architecture scales from hundreds to millions of concurrent viewers.

How do you handle image processing for thousands of concurrent uploads?

Processing jobs are queued and executed by auto-scaling workers. Each upload generates a processing job that runs independently, so the system handles concurrent uploads naturally. Backpressure and priority queues prevent overload.

Can you add watermarking to images and videos?

Yes. We implement configurable watermarking with text or image overlays, adjustable positioning, opacity, and size. Watermarks can be applied during processing or on-the-fly during delivery.

Process Images and Video at Scale Without Infrastructure Pain

Automatic resizing, format conversion, video transcoding, watermarking, and CDN delivery. Bookuvai builds media pipelines that handle millions of assets efficiently.

Feature: Image & Video Processing

Image and video processing is essential for any media-rich application, from social platforms to e-commerce product galleries. A production media pipeline handles upload, validation, transformation, optimization, and delivery with minimal latency and cost. Bookuvai builds processing systems that run asynchronously, scale horizontally, and deliver optimized media to users worldwide via CDN.

Benefits

Automatic Optimization: Images are automatically resized, compressed, and converted to modern formats (WebP, AVIF) for optimal loading speed without visible quality loss.
Video Transcoding: Transcode uploaded videos to HLS/DASH for adaptive streaming, generate thumbnails, and extract metadata automatically.
On-the-Fly Transformations: URL-based image transformations for resizing, cropping, and filtering without pre-generating every variant.
Cost-Efficient Architecture: Serverless processing with queue-based scaling ensures you only pay for actual processing time, not idle infrastructure.
Content Moderation: Optional AI-based content moderation to detect and flag inappropriate images or videos before they reach your users.

How It Works

Pipeline Design: Define media types, transformation presets, output formats, quality targets, and delivery requirements for your application.
Upload & Validation: Build upload endpoints with file type validation, size limits, virus scanning, and metadata extraction.
Processing Engine: Implement image processing with Sharp and video transcoding with FFmpeg, running as async jobs with progress tracking.
Storage & CDN: Store originals and variants in object storage, configure CDN delivery with cache policies, and set up signed URLs for private media.
Integration & Monitoring: Connect the media pipeline to your application models, add processing status webhooks, and set up monitoring for failed jobs.

Technology Options

Sharp + FFmpeg: High-performance Node.js image processing with Sharp (libvips) and video transcoding with FFmpeg. Maximum control and no per-image costs. (Best for: Self-hosted applications wanting maximum performance and zero per-asset pricing)
Cloudinary: Managed media platform with URL-based transformations, AI-powered cropping, video transcoding, and global CDN delivery. (Best for: Teams wanting a fully managed solution with extensive transformation features)
AWS MediaConvert + Lambda: Serverless video transcoding with MediaConvert and image processing with Lambda + Sharp. Pay-per-use with automatic scaling. (Best for: AWS-native applications with high-volume video processing needs)
imgproxy: Open-source, fast image processing server that generates transformations on the fly via URL parameters. Easy to deploy and scale. (Best for: Applications needing on-the-fly image resizing without storing every variant)

Estimated Hours

Simple: 10-18 hours | Moderate: 18-35 hours | Complex: 35-70 hours

Frequently Asked Questions

Can you build a video streaming platform?: Yes. We implement video upload, transcoding to HLS/DASH adaptive bitrate streams, DRM protection, thumbnail generation, and video player integration. The architecture scales from hundreds to millions of concurrent viewers.
How do you handle image processing for thousands of concurrent uploads?: Processing jobs are queued and executed by auto-scaling workers. Each upload generates a processing job that runs independently, so the system handles concurrent uploads naturally. Backpressure and priority queues prevent overload.
Can you add watermarking to images and videos?: Yes. We implement configurable watermarking with text or image overlays, adjustable positioning, opacity, and size. Watermarks can be applied during processing or on-the-fly during delivery.