Enterprise Video Encoding & Multi-Channel Distribution Platform
A media company needed a comprehensive platform to manage their video content lifecycle from upload to encoding to multi-channel distribution, supporting different output specifications for each distribution partner.
讨论您的项目
挑战
Managing video content distribution across multiple channels and partners presented significant operational hurdles:
- Each distribution partner required different encoding formats, resolutions, and codecs
- Manual encoding and upload processes couldn't keep up with content volume
- No centralized system to track encoding status, failures, and retries
- Caption files needed to be discovered, processed, and bundled with video assets
- Scheduling content across multiple channels required a calendar-based workflow
我们的解决方案
We built a full-stack video production platform with automated encoding pipelines, multi-channel scheduling, and partner-specific output profiles.
Architecture
- Main Backend: NestJS 11 with TypeScript, MongoDB/Mongoose, Redis
- Encoder Backend: Specialized NestJS service for encoding orchestration
- Lambda Service: AWS Lambda for serverless encoding workflow triggers
- Frontend: React 18 + Vite with Bootstrap, React Hook Form, ApexCharts
- Encoder Dashboard: Dedicated React interface for encoding management
- Media Processing: AWS MediaConvert with FFmpeg fallback
Encoding Pipeline
- Upload - Video upload to AWS S3 (single or bulk)
- Metadata Extraction - Duration calculation, cue point generation
- Caption Discovery - Automatic caption file matching and processing
- Profile Selection - Partner-specific encoding profiles applied
- MediaConvert Job - AWS MediaConvert processes the transcode
- Quality Check - Automated verification of output specifications
- Distribution - Assets delivered to partner-specific channels
Key Features
- Partner Profiles - Custom encoding specs per distribution partner
- Bulk Upload - Handle large content libraries with batch processing
- Caption Processing - Automatic caption file discovery and format conversion
- Calendar Scheduling - FullCalendar-based content scheduling per channel
- Retry Logic - Automatic retry with error classification for failed jobs
- Analytics Dashboard - Encoding status, throughput, and error rate visualization
- Role-Based Access - JWT authentication with admin user management
成果
技术栈
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常见问题
MicrocosmWorks built an encoding profile management system with over 50 preset configurations covering broadcast (ProRes, DNxHR), OTT (CMAF with H.264/H.265), and social media (platform-optimized MP4) delivery targets. Each source video is encoded into all required formats in a single pipeline run using parallel FFmpeg workers, with automatic quality validation against each channel's specification.
MicrocosmWorks implemented per-title encoding optimization that analyzes each video's visual complexity using VMAF scoring to generate a content-aware bitrate ladder. Simple talking-head content receives fewer, lower-bitrate rungs while visually complex content like sports gets additional higher-bitrate variants, optimizing storage costs while maintaining perceptual quality above VMAF 93.
MicrocosmWorks architected the platform for horizontal scaling using Kubernetes-orchestrated encoding workers that auto-scale based on queue depth. The system has been validated processing over 1,000 hours of video per day using spot instances, with job prioritization ensuring urgent encodes are processed within minutes while bulk backlog operations use cost-effective scheduling.
MicrocosmWorks built a delivery tracking dashboard that monitors each asset's encoding status, upload progress, and publication confirmation across all distribution channels. The system provides webhook callbacks for downstream system integration and generates automated reports showing time-to-publish metrics per channel, helping operations teams identify distribution bottlenecks.
MicrocosmWorks delivers video infrastructure projects at rates of $30-$50/hr, with an enterprise encoding and distribution platform including the profile manager, autoscaling workers, VMAF optimization, and multi-channel delivery typically requiring 700-1000 development hours. Cloud encoding costs run approximately $0.01-$0.03 per minute of source video on AWS spot instances.