Overview

Festival spikes caused app/API slowdowns and order failures. The platform implemented layered caching, autoscaling, and queue‑based workflows to stabilize.

Key Strategies for Scaling

  • Layered Caching (The Web Layer): Static assets (menus, photos) are cached at the Edge (CDN) to offload the origin server. For dynamic data like daily specials, Server-side Caching (Redis) is used to avoid repeated database hits.
  • Message Queues for Order Events: To handle spikes, the platform moved to an Asynchronous Architecture. When an order is placed, it enters a queue (e.g., RabbitMQ/Kafka). The dispatch system processes the queue as riders become available, preventing the application server from crashing under load.
  • Database Optimization: Use of Read Replicas for non-critical tasks (browsing menus) and Connection Pooling to manage high concurrent user sessions.
  • Dispatch Optimization & Traffic Shaping: Software uses Geofencing to limit orders to areas with available riders. During extreme peaks, “Traffic Shaping” (pausing new orders or increasing delivery fees) is used to maintain service for existing orders.

Outcomes

  • Performance Stability: P95 latency (the response time for 95% of requests) improved by 45% during peak festival hours.
  • Resilience: Failed orders due to system timeouts were reduced by 70%, directly improving customer trust.
  • Operational Efficiency: Automated “batching” allowed a smaller rider fleet to handle a higher volume of orders through optimized routing.

Lessons (Unit 3 Lens)

  • Caching + Queues are Fundamental: Under bursty, location-dependent traffic, standard web servers are insufficient without asynchronous processing.
  • Separate Read vs. Write Paths: High-traffic e-commerce systems must prioritize “Reading” (browsing) performance via caches, so the “Write” (order placement) resources are protected.
  • Logistics is the Final Bottleneck: No matter how fast the web server is, the “Last-Mile” (the physical delivery) remains the most fragile part of the value chain.

Chapters covered

  • Web performance and scalability (3.2–3.4)
  • Mobile considerations for high‑traffic events (3.5)