Communication Patterns in Distributed Systems
Understand the core communication patterns such as, push, pull, WebSockets, and webhooks, and discover how they power scalable, real-time distributed systems.
The difference between a seamless real-time experience and a frustrating delay often comes down to one invisible choice: how a system communicates.
Behind every new message alert or live-updating feed is a design pattern that governs when data is sent, how often, and at what cost. For example, a newsfeed that refreshes too slowly, a chat message that arrives late, or a dashboard that feels outdated, all of these are symptoms of a poorly chosen communication pattern.
System design doesn’t focus only on storage, APIs, or scaling servers.
It’s also about interaction, ensuring that data flows in a way that keeps users engaged without overwhelming the infrastructure. Understanding these patterns is essential for anyone building or evaluating modern systems, and it’s a core part of what separates intermediate engineers from senior ones.
With that context in mind, let’s now explore the two fundamental communication patterns, pull and push.
Push and pull interaction models
At the highest level, communication follows two fundamental interaction models: pull, where the client asks for updates, and push, where the server delivers them.
The key difference is which side initiates the exchange. Understanding these models and their trade-offs is the first step toward building scalable, resilient systems. In a pull model, the client requests updates from the server. This is the default pattern on the web.
A basic form of polling is where the client repeatedly asks the server for new data at fixed intervals (e.g., every 5 seconds).
While simple, this can be inefficient if no new data is available. A more efficient variation is long-polling, where the client makes a request and the server holds the connection open until new data is ready to be sent. In a push model, the server proactively sends updates to the client without waiting for a request.
This is ideal for real-time scenarios, such as instant messaging or live score updates.
Educative byte: Long-polling is often a good middle-ground. If we need lower latency than regular polling but want to avoid the complexity of a persistent connection, such as a WebSocket, long-polling is a strong candidate.
The following diagram visually contrasts these communication patterns.
The table below summarizes these patterns and their specific trade-offs.
Pattern | Mechanism | Latency | Scalability and State | Typical Use Cases |
Pull (Polling) | The client repeatedly sends HTTP requests at a fixed interval | High | High (stateless) | Dashboards, weather updates |
Pull (long-polling) | Client sends a request; server holds it open until data is available | Medium | Moderate (some states) | Simple chat, notifications |
Push (WebSocket) | A persistent, bidirectional connection is established | Low | Complex (stateful) | Live chat, online gaming |
As the table shows, the push pattern is a powerful tool for ...