Real-Time Features Done Right: WebSockets, SSE, and Beyond

Not All Real-Time Is Created Equal

"We need real-time" is one of the most common client requests we hear. But what does "real-time" actually mean for your specific use case? The answer determines which technology you should reach for — and getting it wrong can cost you months of refactoring.

The Technology Landscape

Server-Sent Events (SSE)

SSE is the unsung hero of real-time web development. It's a simple, HTTP-based protocol for one-way server-to-client streaming. No special libraries, no connection upgrades, and it works through most proxies and load balancers without configuration.

We use SSE for:

• Live dashboards with updating metrics

• Notification feeds

• Progress indicators for long-running operations

• AI response streaming (like ChatGPT-style UIs)

The key advantage is simplicity. SSE uses standard HTTP, so your existing authentication, logging, and monitoring infrastructure works without modification.

WebSockets

WebSockets provide full-duplex communication — both client and server can send messages at any time. This makes them essential for truly interactive features.

We use WebSockets for:

• Real-time chat and messaging

• Collaborative editing (multiple users editing the same document)

• Multiplayer features

• Live auction or trading systems

The trade-off is complexity. WebSocket connections are stateful, which complicates load balancing, requires sticky sessions or a pub/sub layer, and makes horizontal scaling more involved.

Long Polling

Sometimes the simplest solution wins. Long polling — where the client makes a request and the server holds it until there's new data — is surprisingly effective for low-frequency updates.

We use long polling for:

• Systems where SSE isn't supported (rare, but it happens)

• Features where updates happen every few seconds at most

• Environments with restrictive proxy configurations

Architecture Patterns

The Pub/Sub Layer

For any real-time system beyond a single server, you need a pub/sub layer. We typically use Redis Pub/Sub for simple cases and NATS for high-throughput scenarios. This decouples the event producers from the consumers and enables horizontal scaling.

Connection Management

Real-time connections need careful management:

• Implement heartbeat/ping-pong to detect dead connections

• Use exponential backoff for reconnection logic

• Set maximum connection limits per user to prevent resource exhaustion

• Track connection metrics (count, duration, message throughput)

Graceful Degradation

Not every user will maintain a stable real-time connection. Design your system so that missed real-time events don't cause data inconsistency. We use a pattern where real-time updates are optimistic — the actual source of truth is always a REST endpoint that the client can poll as a fallback.

Performance Considerations

Real-time features can be surprisingly expensive at scale:

• Each WebSocket connection consumes a file descriptor and memory on the server

• A server handling 50,000 concurrent WebSocket connections needs careful tuning

• Message serialization/deserialization becomes a bottleneck before network bandwidth does

• Consider binary protocols (MessagePack, Protocol Buffers) for high-throughput scenarios

Our Recommendation

Start with SSE. It covers 70% of real-time use cases with 20% of the complexity. Upgrade to WebSockets only when you genuinely need bidirectional communication. And always build your real-time features on top of a solid pub/sub layer — you'll thank yourself when it's time to scale.