Scalable Web Servers: Load Balancing and Caching

Scaling a web service means more users, more data, and more demand on servers. A good setup uses load balancing to spread work and caching to reduce repeated tasks.

Load balancing distributes requests across servers. A simple approach uses DNS round robin; a more reliable option uses a reverse proxy like Nginx or a dedicated load balancer such as HAProxy or Envoy. Health checks keep traffic away from unhealthy nodes.

There are Layer 4 and Layer 7 options. L4 balances by IP and port; L7 looks at HTTP data and can route by path, headers, or cookies. Start with a basic round robin and add health checks, sticky sessions when needed, and automatic scaling rules.

Caching sits at several levels. Browser caching saves a page on the user device. A CDN stores copies near users and reduces distance. Server-side caches speed up dynamic pages. Use cache-control headers, ETag, and Last-Modified to help browsers know when to fetch fresh data.

Plan cache invalidation carefully. Time-based TTLs are simple. For deployments, purge caches on new releases. Distributed caches like Redis or Memcached help share data between servers; set eviction policies and understand consistency limits.

In practice, start small: one load balancer, a few app servers, and a CDN for static files. Monitor latency and error rates. Add a distributed cache and autoscaling rules as traffic grows.

Security and privacy should guide design. Use HTTPS, rotate credentials, and log access patterns to detect unusual requests. Example: three app servers behind a load balancer. The proxy health checks remove failed nodes. Cache headers keep pages fresh without wasting bandwidth. For user sessions, consider a stateless design; if you need sessions, use a shared store like Redis.

Conclusion: scalable systems use both good routing and smart caching. Plan, monitor, and adjust as traffic changes.

Key Takeaways

  • Load balancing and caching work together to improve performance.
  • Start simple and add layers like CDN and distributed caches as needed.
  • Monitor latency, errors, and cache hit rates to guide tuning.