Real-Time Streaming Systems (WebRTC + Live Data) · Lesson

Sharing Application State Live

Explore techniques for using live data to synchronize application state, enabling collaborative features and shared experiences.

Sharing Application State Live is a free Real-Time Streaming Systems (WebRTC + Live Data) lesson on CoddyKit — lesson 3 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Real-Time Streaming Systems (WebRTC + Live Data) learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.

What is Shared State?

Imagine multiple people working on the same document or playing the same game. They need to see the same information and changes in real-time. This common, synchronized information is called shared application state.

It's the data that reflects the current status of an application, accessible and modifiable by all connected participants.

Why Share State Live?

Sharing state live is crucial for creating truly collaborative and interactive experiences. Think about:

Collaborative Editing: Multiple users typing in a document simultaneously.
Multi-user Drawing: Everyone sees lines appear as they are drawn.
Online Games: Synchronizing player positions, scores, and game events.
Shared Whiteboards: Real-time updates to drawings and notes.

It makes applications feel responsive and connected.

Data Channels for State Sync

In WebRTC, RTCDataChannel is your go-to tool for sharing application state. Unlike media streams (audio/video), data channels are designed for sending arbitrary data, from text messages to binary files.

They provide a fast, direct, and secure peer-to-peer connection, making them ideal for small, frequent state updates without latency.

Representing Application State

Before sending, you need to decide how to structure your application state. A common and flexible way is using plain JavaScript objects or JSON (JavaScript Object Notation).

This allows you to easily store different types of data like text, numbers, and nested objects, ready for serialization.

Try running this example of a simple state object:

let sharedAppState = {
  documentTitle: "My Collaborative Doc",
  cursorPosition: { x: 0, y: 0 },
  selectedTool: "pen",
  version: 1
};

console.log("Initial state:");
console.log(sharedAppState);

Sending State Updates

When a user makes a change, you update your local state. Then, you need to send this change to other peers. Data Channels expect string or binary data.

We use JSON.stringify() to convert our JavaScript object into a JSON string before sending it via dataChannel.send() (conceptually).

Here's how to prepare an update:

let localState = { counter: 5 };

// Simulate a data channel send function
function sendData(data) {
  console.log("Sending data:", data);
}

// A change occurs
localState.counter++; // counter is now 6

// Create an object for the update
let update = { counter: localState.counter };

// Convert the update to a JSON string
let jsonUpdate = JSON.stringify(update);

sendData(jsonUpdate);
// Expected output: Sending data: {"counter":6}

Receiving & Applying Updates

When another peer sends an update, your dataChannel.onmessage event handler will receive it. The received data will be a string (or ArrayBuffer).

You then use JSON.parse() to convert the JSON string back into a JavaScript object. Finally, you apply these changes to your local application state, often using Object.assign() for merging.

See how to process a received update:

let appState = { message: "Hello", count: 0 };

// Simulate receiving a message from a data channel
let receivedMessage = '{"message": "World", "count": 1}';

// When a message is received:
function handleMessage(eventData) {
  let update = JSON.parse(eventData);
  // Merge the received update into the current state
  Object.assign(appState, update);
  console.log("State after update:");
  console.log(appState);
}

handMessage(receivedMessage);
// Expected output:
// State after update:
// { message: 'World', count: 1 }

Full State vs. Delta Updates

When sharing state, you can either send the entire application state every time a change occurs, or just send the "diff" (delta update), which is only the part of the state that changed.

For large states or frequent small changes, sending only diffs is more efficient as it uses less bandwidth. However, sending the full state can be simpler to implement and more robust against missed messages in some scenarios.

Handling State Conflicts

What happens if two users try to change the same part of the state at the exact same time? This is a state conflict.

Simple solutions include "last write wins" (the last received update overrides previous ones). More advanced systems use techniques like CRDTs (Conflict-free Replicated Data Types), which are data structures designed to merge changes from different sources automatically without conflicts.

Shared Counter Example Flow

Let's imagine a simple shared counter application. Each peer has a button to increment the counter.

Initial State: Both peers start with counter: 0.
User Action: Peer A clicks "Increment". Local counter becomes 1.
Send Update: Peer A sends {"counter": 1} via Data Channel.
Receive Update: Peer B receives {"counter": 1}, parses it, and updates its local counter to 1.
Synchronization: Both peers now show counter: 1.

This simple flow demonstrates the core of live state synchronization.

Check Your Understanding

When building a collaborative application that uses WebRTC Data Channels to synchronize application state, which of the following are key considerations?

Recap: Shared Live State

In this lesson, you learned about the importance of sharing application state live for collaborative features. We covered how RTCDataChannel is ideal for this, and the process of representing, sending, and receiving state updates using JSON serialization.

You also explored challenges like state conflicts and strategies for choosing between full state and delta updates. These techniques are fundamental for building responsive, multi-user applications.

Frequently asked questions

Is the “Sharing Application State Live” lesson free?

Yes — the full text of “Sharing Application State Live” is free to read here on the web, and the Real-Time Streaming Systems (WebRTC + Live Data) course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Real-Time Streaming Systems (WebRTC + Live Data) course, upgrade to CoddyKit PRO.

What will I learn in “Sharing Application State Live”?

Explore techniques for using live data to synchronize application state, enabling collaborative features and shared experiences. You practise Real-Time Streaming Systems (WebRTC + Live Data) with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.

Do I need any experience to start Real-Time Streaming Systems (WebRTC + Live Data)?

No prior experience is required. Real-Time Streaming Systems (WebRTC + Live Data) on CoddyKit is structured for beginners through advanced learners; this is — lesson 3 of 4, so you can start here or from the beginning and move at your own pace.

How long does the “Sharing Application State Live” lesson take?

Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.

Can I write and run code in this Real-Time Streaming Systems (WebRTC + Live Data) lesson?

Yes. Every Real-Time Streaming Systems (WebRTC + Live Data) lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.

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