Project Overview
We have an existing Computer Vision & Live Streaming Platform that integrates WebRTC, FFMPEG, NVR/DVR sources, Django, FastAPI, React, and more. However, we are facing several technical challenges that are preventing us from scaling and deploying across multiple use cases.
We are seeking a highly experienced individual or team specializing in real-time video streaming, scalability, and fault tolerance to troubleshoot, optimize, and enhance the system for production readiness.
Retry logic implemented but not functioning reliably
Intermittent stream failures
Need a strong auto-recovery fault-tolerant solution
2. Camera Scalability
Current limit: ~8 camera streams per server
Must scale far beyond this while optimizing CPU/GPU/memory usage
The same setup behaves differently on different servers
3. Configurable Multi-Use Case UI
Need a single UI framework that can be configured for multiple CV use cases, such as:
-Attendance tracking
-Construction site monitoring
-Fire detection
-Theft / pickpocket analytics
-Number plate recognition (ANPR)
-Rather than writing new code per use case, we need a config-driven or drag-and-drop solution for:
1-Dashboards
2-Alerting
3-Reporting
4-Layouts
4. Environment Consistency / Deployment
Code behaves differently across servers
Need standard deployment scripting or containerization
Prefer Docker/Kubernetes CI/CD approach
What We Expect
✔ Deep troubleshooting of reliability and retry logic
✔ Scalability optimization (more cameras per server)
✔ Environment standardization: Docker/K8s CI/CD
✔ Modular configurable UI design
✔ Documentation + Knowledge Transfer
Ideal Candidate
-Proven experience with WebRTC + FFMPEG + NVR/DVR
-Past work scaling video streaming systems in production
-Strong in Python (Django / FastAPI) + React
Cloud DevOps (AWS, Azure, GCP)
-Microservice architecture, Docker & Kubernetes
Strong problem-solving skills & ability to deliver production-quality solutions
Deliverables
-Reliable live streaming with working retry logic
-Scalable architecture supporting higher camera loads
-Configurable UI framework for multiple use cases
-Deployment documentation
-Knowledge transfer session
Screening Questions (Must Answer)
1-Describe your experience using WebRTC + FFMPEG for live streaming from NVR/DVR sources.
2-Have you scaled camera streaming beyond 8–10 streams per server? What approach did you use?
3-How do you ensure environment consistency across multiple deployment servers?
4-Share an example of a configurable UI/dashboard you built that supports multiple use cases without additional coding.
5-What techniques or tools do you use for real-time monitoring and fault tolerance in streaming systems?
6-How do you ensure security in live streaming and NVR/DVR integrations?
How to Apply
Please include:
1-Relevant project examples
2-High-level approach to solve our challenges
3-Estimated timeline & pricing model
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