[ ARCHITECTURE CASE STUDY ]

Streamify Case Study | Sarthak Joshi — Backend Developer

Social Learning & Low-Latency Streaming

Overview & Domain

Explore Streamify: real-time social learning platform with instant JWT messaging, presence detection, and sub-100ms video rooms by Sarthak Joshi.

Primary Technology Stack: React.js, Node.js, Express.js, MongoDB, Stream SDK, JWT

The Engineering Challenge

Scaling real-time chat with presence detection while maintaining per-room authorization and low-latency video streams requires enterprise messaging SDK integration. Users need seamless transitions between text conversations and video calls without connection drops.

Architectural Solution

Integrated Stream Chat & Video APIs with a custom JWT-authenticated Express.js backend. Added friend request workflows, message history persistence, presence indicators, and dynamic room creation with granular security policies.

Technical Architecture & System Specifications

  • JWT-authenticated Express.js backend coordinating user authentication, relationship graphs, and room tokens.
  • Stream Chat & Video SDK pipelines delivering sub-100ms group video calling and persistent channel messaging.
  • Real-time user presence detection system monitoring active, away, and offline connection states.
  • MongoDB schemas tracking mutual friend connections, user profiles, and room memberships.
  • Robust error-handling middleware preventing unhandled promise rejections and ensuring continuous server availability.

Measured Performance & Production Metrics

  • Sub-100ms video call room initialization latency for multi-party language study sessions.
  • Granular per-conversation access control preventing unauthorized participant intrusion.
  • Reliable message delivery with client-side optimistic UI updates.

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