挑战
Managing streaming infrastructure for many cameras presented operational challenges:
- Manually provisioning streaming servers for each camera was unsustainable
- Idle streams wasted compute resources and bandwidth
- Cloudflare and CDN integration required HLS conversion from RTSP
- User-scoped access control needed to ensure tenants only saw their cameras
我们的解决方案
We built an orchestration layer that dynamically provisions, monitors, and cleans up MediaMTX streaming containers based on demand.
Architecture
- Orchestrator API: FastAPI microservice for stream lifecycle management
- Container Engine: Docker-based MediaMTX container provisioning
- Authentication: Supabase JWT for user-scoped camera access
- CDN Proxy: Cloudflare Workers for HLS delivery
- Health Monitoring: Periodic health checks with automatic recovery
Lifecycle Management
- On-Demand Provisioning - Streaming server created when user requests a camera feed
- RTSP-to-HLS Conversion - MediaMTX handles protocol conversion for browser playback
- Health Monitoring - Periodic checks ensure server responsiveness
- Auto-Cleanup - Idle servers terminated after configurable timeout
- Recovery - Unhealthy servers automatically restarted
Key Features
- User-Scoped Access - Each tenant sees only their authorized cameras
- Dynamic Scaling - Containers spun up and down based on viewer demand
- Quality Control - Per-stream FPS (1-60) and resolution (low/medium/high/ultra) settings
- Snapshot API - Timestamp-precise frame capture from live streams
- CDN Integration - Cloudflare Workers proxy for global low-latency HLS delivery
- RTSP Caching - Intelligent caching of camera connection details to minimize API calls
成果
技术栈
caseStudyDetail.more 案例研究
探索更多我们的技术实施案例
基于 VPN 的 RTSP 流媒体，具备自动扩展的转发、HLS 传输和录制
一个监控平台需要通过 VPN 隧道安全地接收来自远程位置的 RTSP 摄像机流，将其转发用于基于网页的查看和 AI 处理，根据需求自动扩展转发基础设施，并录制流以供存档——所有这些都要在不可预测的网络条件下保持低延迟和可靠连接。
具有双编排器和零丢包的自动扩缩容 RTSP 流媒体架构
一个监控平台需要动态扩缩容其视频流媒体基础设施，以处理从 10 到 200 多个 IP 摄像头，以及数百名并发观看者和 AI 处理工作者，同时保证在扩缩容操作期间零丢包，并保持永不改变的稳定流 URL。
常见问题
MicrocosmWorks built a multi-region orchestration layer where edge relay nodes at each physical location pull RTSP streams locally, transcode as needed, and forward them to the central platform via encrypted tunnels. This architecture eliminates the need for direct internet-exposed camera access, reduces WAN bandwidth by applying intelligent frame sampling at the edge, and maintains stream continuity even during network fluctuations between sites.
MicrocosmWorks implemented schedule-aware auto-scaling that pre-provisions processing capacity based on historical stream patterns, combined with reactive scaling that responds to real-time stream count changes within 30 seconds. The system scales down aggressively during off-peak hours to minimize cloud compute costs, and uses warm standby pods that can accept new streams instantly without the cold-start delay of provisioning new GPU instances.
MicrocosmWorks designed an admission control system that queues incoming stream connections and distributes them across available processing nodes using a weighted round-robin algorithm that accounts for each node's current CPU, GPU, and memory utilization. Streams are prioritized based on configurable rules, so high-priority cameras like entry points always get processing capacity before lower-priority feeds.
Yes, MicrocosmWorks built ONVIF discovery and RTSP pull adapters that connect to existing NVRs and VMS platforms, treating them as stream sources without requiring any changes to the existing recording infrastructure. The orchestration layer can also receive re-streamed feeds from popular VMS systems like Milestone and Genetec, allowing enterprises to add AI analytics capabilities to their current surveillance investment.
MicrocosmWorks delivers distributed streaming orchestration solutions at rates between $30-$50/hr, with a production-ready MVP typically requiring 3-4 months of development depending on the number of edge locations and integration requirements. This is substantially more cost-effective than enterprise video platform licenses that charge per-stream fees, especially at scale beyond 100 concurrent streams.