Anadi Aakar Dewan
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Project

Elastic Auction Room Sharding for Peak Traffic

Revmax Technologies
Apr 2024 – Aug 2024
PythonFlaskRedisWebSockets

Auto-partitioned bidders into isolated rooms when demand exceeded capacity; scaled to N rooms to sustain peak events.

Problem

Scheduled auctions caused sudden surges where a single room could not handle all users without performance degradation.

Solution

Implemented dynamic room partitioning: users were placed into multiple isolated rooms with separate bid visibility, scaling room count based on load.

Impact

  • Sustained peak-time events by distributing load across rooms (no cross-room bid/user visibility).
  • Enabled scaling to N rooms based on participant count, improving stability at peak.