From Zero to Million Users: Engineering a Scalable, Secure, and Superfast App 🚀 - Part 2

Load Balancing & Traffic Distribution: The Backbone of Scalable Systems

Load balancing is the process of distributing incoming network traffic across multiple backend servers to ensure no single server is overloaded leading to slowness or crash. This optimizes resource use, improves response times, and enhances system reliability.

Why is Load Balancing Important?

• High Availability (HA): Ensures no single point of failure by distributing load across multiple servers.
• Scalability: Dynamically adds or removes servers based on traffic spikes.
• Performance Optimization: Reduces latency by directing requests to the best-performing server.
• Fault Tolerance: Automatically redirects traffic if a server fails, ensuring seamless user experience.
• Security: Protects against DDoS attacks by limiting requests per second and filtering malicious traffic.

Case Studies

Let’s explore how industry giants like Netflix, Uber, Shopify, and YouTube implement load balancing and traffic distribution to handle massive user traffic, ensuring scalability, availability, and performance.

Netflix: Streaming Billions of Hours with AWS Load Balancing & Edge Caching

Challenge

Netflix serves over 260M+ subscribers globally, delivering billions of hours of video content every day. With users distributed across various regions, the biggest challenge is low-latency streaming, handling peak traffic surges, and ensuring a seamless experience even when infrastructure fails.

Solution

1. AWS Elastic Load Balancer (ALB & NLB):

• Efficiently routes API requests to microservices running on AWS.
• Dynamically distributes user requests to nearest regional clusters.

2. CDN & Edge Caching (Netflix Open Connect):

• Netflix caches popular content on regional servers to reduce latency.
• Avoids origin server overload by delivering videos from geographically closer locations.

3. Auto Scaling + Load Balancing:

• Spins up EC2 instances in real-time as traffic surges.
• Load balancers redirect users away from failing servers to ensure uptime.

Result

Netflix handles 10M+ concurrent users with buffer-free streaming, even in high-traffic popular release events like Stranger Things or Squid Game 😁

Uber: Routing Millions of Rides with HAProxy & Envoy Proxy

Challenge

Uber processes millions of ride requests per second, with drivers and riders connecting in real time. The challenge is low-latency API responses, handling geographically distributed requests and ensuring ride-matching efficiency.

Solution:

1. HAProxy for API Load Balancing:

• API Gateway handles 100K+ RPS (Request Per Second) efficiently.
• Routes API calls to appropriate backend microservices (e.g., Pricing, Matching, Maps).

2. Envoy Proxy for Microservices Traffic:

• Manages 4,000+ microservices running inside Uber.
• Ensures service-to-service communication is fast and failure-resistant.

3. Geo-based Load Distribution:

• Requests are routed to nearest Uber data centers.
• AI-driven routing ensures driver-rider matching with minimal latency.

Result

Uber scales dynamically to 100M+ monthly active users, providing low-latency ride matching across 900+ cities worldwide.

Shopify: Surviving Black Friday Traffic Spikes with Kubernetes & Ingress Load Balancers

Challenge

Shopify powers over 4.5M online stores, handling Black Friday Cyber Monday (BFCM) traffic surges where sales can increase by 10x in minutes. The challenge is to ensure zero downtime, handle spikes, and optimize checkout processing speed.

Solution

• Kubernetes Load Balancing (Ingress Controller):
  • Shopify uses Nginx Ingress to route millions of checkout requests.
  • Scales horizontally by spinning up new Kubernetes pods on demand.
• Global Traffic Distribution:
  • Google Cloud Load Balancer (GCLB) ensures that traffic is distributed across multiple data centers.
• Caching for High-Speed Performance:
  • Redis and Varnish Cache reduce database queries for repeated requests.
  • GraphQL API + CDN optimizes store browsing speed.

Result

Shopify remains 100% online, handling millions of checkouts per minute during Black Friday sales.

YouTube: Handling Billions of Video Views with Google Cloud Load Balancing

Challenge

YouTube delivers 1B+ hours of video content daily while ensuring zero buffering, quick search results, and seamless live streaming to millions of users.

Solution

1. Google Cloud Load Balancer (GCLB) for API & Video Traffic:

• Routes video requests to nearest regional servers for low-latency playback.

2. Edge Computing with CDNs:

• Google’s Edge Network caches popular videos closer to users.
• Avoids direct load on primary data centers.

3. Auto Scaling with YouTube Live Streaming:

• Google Kubernetes Engine (GKE) spins up servers automatically when millions watch a live event (e.g., FIFA World Cup).
• Adaptive Bitrate Streaming optimizes bandwidth for users on slow networks.

Result

YouTube smoothly serves millions of concurrent video streams, even during viral content surges.

All the use cases discussed in brief gives the high level details on how these giants handle user traffic using load balancer technique. But there is more to their marvellous engineering and what we've seen is only the tip of the iceberg. Next we'll talk about the API Design and Scalability.