🚀 Enterprise-Grade FFmpeg Processing API

A high-performance, production-ready FFmpeg API designed to replace complex CLI workflows with a modern, scalable, developer-friendly solution. Built for professional video processing with enterprise features.

• 🎬 Complete FFmpeg Capability - Full CLI parity with REST API convenience
• ⚡ Hardware Acceleration - NVENC, QSV, VAAPI, VideoToolbox support
• 📊 Quality Metrics - Built-in VMAF, PSNR, SSIM analysis
• 🔄 Async Processing - Non-blocking operations with real-time progress
• 🛡️ Enterprise Security - API keys, rate limiting, input validation
• 📈 Production Monitoring - Prometheus metrics, health checks, alerting
• 🌐 Multi-Cloud Storage - S3, Azure, GCP, and local filesystem
• 🐳 Container Native - Optimized Docker deployment with orchestration

git clone <repository-url> cd ffmpeg-api # Choose your deployment type ./setup.sh --development # Local development (SQLite) ./setup.sh --standard # Production (PostgreSQL + Redis) ./setup.sh --gpu # Hardware accelerated processing

# API available at curl http://localhost:8000/api/v1/health # Interactive documentation open http://localhost:8000/docs

curl -X POST "http://localhost:8000/api/v1/convert" \\ -H "Content-Type: application/json" \\ -H "X-API-Key: your-api-key" \\ -d '{  "input": "/storage/input.mp4",  "output": "mp4"  }'

POST /api/v1/convert # Universal media conversion POST /api/v1/analyze # Quality metrics (VMAF, PSNR, SSIM) POST /api/v1/stream # HLS/DASH adaptive streaming POST /api/v1/estimate # Processing time/cost estimation

GET  /api/v1/jobs # List and filter jobs GET  /api/v1/jobs/{id} # Job status and progress GET  /api/v1/jobs/{id}/events # Real-time progress (SSE) DELETE /api/v1/jobs/{id} # Cancel job

GET  /api/v1/health # Health check GET  /api/v1/capabilities # Supported formats and features GET  /docs # Interactive API documentation

• NVIDIA NVENC/NVDEC - GPU encoding and decoding
• Intel Quick Sync Video - Hardware-accelerated processing
• AMD VCE/VCN - Advanced media framework
• Apple VideoToolbox - macOS hardware acceleration

• VMAF - Perceptual video quality measurement
• PSNR - Peak Signal-to-Noise Ratio
• SSIM - Structural Similarity Index
• Bitrate Analysis - Compression efficiency metrics

• API Key Authentication with role-based permissions
• Rate Limiting with configurable thresholds
• Input Validation prevents command injection
• HTTPS/SSL with automatic certificate management
• Security Headers (HSTS, CSP, XSS protection)

• Prometheus Metrics - 50+ metrics tracked
• Grafana Dashboards - Real-time visualization
• Health Checks - Comprehensive system monitoring
• Structured Logging - Centralized log management
• Alerting Rules - Proactive issue detection

Production Stack: ├── Traefik (SSL/Load Balancer) ├── KrakenD (API Gateway) ├── FastAPI (Core API) ├── Celery Workers (CPU/GPU) ├── PostgreSQL (Database) ├── Redis (Queue/Cache) ├── Prometheus (Metrics) └── Grafana (Monitoring)

• Multi-stage builds for optimized images
• Security hardening with non-root users
• Health checks with automatic restarts
• Resource limits and monitoring
• Log rotation and management

Video: MP4, AVI, MOV, MKV, WebM, FLV, WMV, MPEG, TS, VOB, 3GP, MXF Audio: MP3, WAV, FLAC, AAC, OGG, WMA, M4A, Opus, ALAC, DTS

Containers: MP4, WebM, MKV, MOV, HLS, DASH, AVI Video Codecs: H.264, H.265/HEVC, VP9, AV1, ProRes Audio Codecs: AAC, MP3, Opus, Vorbis, FLAC

# Core Configuration API_HOST=0.0.0.0 API_PORT=8000 DEBUG=false # Database DATABASE_URL=postgresql://user:pass@localhost:5432/ffmpeg_api REDIS_URL=redis://localhost:6379/0 # Security ENABLE_API_KEYS=true RATE_LIMIT_CALLS=2000 RATE_LIMIT_PERIOD=3600 # FFmpeg FFMPEG_HARDWARE_ACCELERATION=auto FFMPEG_THREADS=0

# config/storage.yml - Multi-cloud storage storage: backends: s3: bucket: my-video-bucket region: us-west-2 azure: container: videos local: path: /storage

# Scale API instances docker compose up -d --scale api=4 # Scale workers based on load docker compose up -d --scale worker-cpu=8 docker compose up -d --scale worker-gpu=2

• Connection pooling for database and Redis
• Async processing with non-blocking I/O
• Hardware acceleration auto-detection
• Caching layers for frequently accessed data
• Resource management with limits and monitoring

# Development environment ./setup.sh --development # Install development dependencies pip install -r requirements.txt -r requirements-dev.txt # Run tests pytest tests/ -v # Code formatting black api/ worker/ tests/ flake8 api/ worker/ tests/

# Unit tests pytest tests/unit/ -v # Integration tests pytest tests/integration/ -v # Performance tests pytest tests/performance/ -v

• CPU: 4 cores
• RAM: 8GB
• Storage: 50GB SSD
• Network: 1Gbps

• CPU: 8+ cores
• RAM: 32GB
• GPU: NVIDIA RTX 3080+ (8GB+ VRAM)
• Storage: 200GB NVMe SSD
• Network: 10Gbps

Supports deployment on all major cloud platforms:

• AWS (EC2, ECS, EKS)
• Google Cloud (GCE, GKE)
• Azure (VM, AKS)
• DigitalOcean (Droplets, Kubernetes)

We welcome contributions! Please see our Contributing Guide for details.

This project is licensed under the MIT License - see the LICENSE file for details.

• Complete CLI Parity - No feature compromises
• Production Ready - Battle-tested in enterprise environments
• Developer Friendly - Modern REST API with great docs
• Cost Effective - Self-hosted, no per-minute charges
• Highly Secure - Enterprise-grade security features

Transform your video processing workflow with production-ready FFmpeg API.

Production-ready FFmpeg API for professional video processing