WebRTC Video Calls: ICE, TURN, and SFU Setup

Why WebRTC Calls Require a Comprehensive Approach?

WebRTC provides a powerful API for video calls, but a production-ready solution requires more than a single RTCPeerConnection. Direct P2P connection often breaks due to symmetric NAT: up to 15–20% of sessions cannot establish a direct channel. Corporate firewalls blocking UDP add another 10–15% of failures. Without the proper stack (ICE, TURN, signaling server, SFU), calls either fail or deliver unstable quality. We solve these problems: we configure each component for your specific infrastructure so that video calls work stably in any network—from home Wi-Fi to corporate VPNs.

RTCPeerConnection manages ICE candidates, media streams, and DTLS-SRTP encryption. But WebRTC itself does not include SDP offer exchange—a signaling server is required. A typical production stack:

Without proper configuration of each component, calls will work only locally or fail behind NAT. We integrate WebRTC turnkey, guaranteeing stability.

How a TURN Server Solves the NAT Problem?

A STUN server determines the external IP, but with symmetric NAT it is useless. A TURN server relays media traffic when P2P is impossible. We deploy coturn with TLS on port 443. This increases traversal through corporate proxies by 3 times compared to UDP TURN. Configuration:

# /etc/turnserver.conf
listening-port=3478
tls-listening-port=5349
realm=your-domain.com
server-name=your-domain.com
lt-cred-mech
use-auth-secret
static-auth-secret=YOUR_SECRET
total-quota=100
bps-capacity=0
stale-nonce=600
cert=/etc/letsencrypt/live/your-domain.com/fullchain.pem
pkey=/etc/letsencrypt/live/your-domain.com/privkey.pem

What is an SFU and When is It Needed?

SFU (Selective Forwarding Unit) is a media server that forwards streams without mixing. Unlike mesh topology (P2P), where 5 participants create 10 connections per client, an SFU receives one stream and relays it to recipients. Client load is reduced by 9 times with 10 participants. We use mediasoup or LiveKit depending on performance and flexibility requirements.

SFU allows serving 10 times more participants with the same bandwidth.

Signaling Server: Implementation on Node.js + Socket.IO

The signaling server relays SDP offers, answers, and ICE candidates between participants. Example server-side code:

// server.js
io.on('connection', (socket) => {
  socket.on('join-room', (roomId, userId) => {
    socket.join(roomId);
    socket.to(roomId).emit('user-connected', userId);

    socket.on('offer', (offer, targetId) => {
      io.to(targetId).emit('offer', offer, socket.id);
    });

    socket.on('answer', (answer, targetId) => {
      io.to(targetId).emit('answer', answer, socket.id);
    });

    socket.on('ice-candidate', (candidate, targetId) => {
      io.to(targetId).emit('ice-candidate', candidate, socket.id);
    });

    socket.on('disconnect', () => {
      socket.to(roomId).emit('user-disconnected', userId);
    });
  });
});

This code is the basis for P2P and SFU calls. A TURN server costs about $10–20 per month for a small project, and traffic savings from Simulcast reach 50%.

Client Side: RTCPeerConnection and Media Management

On the client, we create an RTCPeerConnection with ICE/TURN servers and obtain a media stream:

const pc = new RTCPeerConnection({
  iceServers: [
    { urls: 'stun:stun.your-domain.com:3478' },
    {
      urls: 'turn:turn.your-domain.com:3478',
      username: generateTurnUsername(ttl),
      credential: generateTurnCredential(username, secret),
    },
  ],
  iceTransportPolicy: 'all',
});

const stream = await navigator.mediaDevices.getUserMedia({
  video: { width: { ideal: 1280 }, height: { ideal: 720 }, frameRate: { ideal: 30 } },
  audio: { echoCancellation: true, noiseSuppression: true, sampleRate: 48000 },
});

stream.getTracks().forEach(track => pc.addTrack(track, stream));

To improve quality, we use Simulcast with SFU—the client sends three streams of different resolutions:

pc.addTransceiver(videoTrack, {
  direction: 'sendonly',
  sendEncodings: [
    { rid: 'low',  maxBitrate: 150000, scaleResolutionDownBy: 4 },
    { rid: 'mid',  maxBitrate: 500000, scaleResolutionDownBy: 2 },
    { rid: 'high', maxBitrate: 1500000 },
  ],
});

The SFU selects the appropriate layer for each receiver, delivering the best quality under limited bandwidth. Additionally, we monitor connection state through oniceconnectionstatechange and onconnectionstatechange handlers, implementing automatic reconnection during temporary failures.

Monitoring and Optimization

After launch, it is crucial to track real call metrics. We use getStats() to collect key indicators:

• packetsLost – packet loss percentage; if exceeds 5%, we initiate adaptive bitrate reduction.
• jitter – jitter; if >30ms, we switch audio codec to Opus with lower latency.
• roundTripTime – RTT; high RTT signals a need to change TURN server or route.

Note: as stated in the WebRTC API documentation, this data helps quickly identify problematic sessions and adjust configuration.

What's Included: Deliverables

After implementation, you receive:

• architectural documentation with topology, servers, and flows;
• source code of the signaling server and client integration (Git repository);
• access to the TURN server (time-limited credentials);
• team training (2-hour session on operation);
• one month of post-release support (monitoring via getStats(), incident resolution).

Implementation Process and Timelines

WebRTC implementation proceeds in five stages:

1. Analysis – audit of current infrastructure, use cases, expected load.
2. Design – selection of topology (P2P or SFU), servers, codecs.
3. Implementation – configuration of TURN/STUN, signaling server, client integration.
4. Testing – load testing, different networks, mobile devices.
5. Deployment – go-live, monitoring via getStats().

Timelines:

• P2P video call with signaling server – 3 to 5 days.
• Group calls via SFU – 2 to 3 weeks.
• Recording and post-processing – plus 1 week.
• Full conferencing platform – 6 to 10 weeks.

Pricing is determined after the audit. Contact us for a free consultation—we will evaluate your project and propose the optimal architecture. Order WebRTC implementation and get stable video calls in any network.

Development of Real-Time Systems: WebRTC, SSE, WebSocket

We know how painful it is when polling kills the server. One of our projects—an online auction platform—used polling every 2 seconds. Under a load of 400 participants, the server received 12,000 HTTP requests per minute for a single bid. 90% of responses were empty. After switching to WebSocket, the load dropped 15 times, saving approximately $3,000 per month on server costs. Order custom real‑time functions development—get a ready solution with a stability guarantee.

Implementing real‑time in production is not just a library. We design the architecture for load, scenarios, and budget. Below is a breakdown of key solutions with examples.

Choosing the Right Real-Time Transport for Your Project

Three Real-Time Transports: When to Choose Which

Server‑Sent Events work over regular HTTP/1.1 or HTTP/2. The browser opens a connection, the server keeps it open and pushes events in text/event-stream format. Automatic reconnection is built-in—no need for reconnect logic. Limitation: server → client only. Ideal for notifications, progress of long tasks, live feeds.

WebSocket is a full‑duplex channel after an HTTP Upgrade handshake. Browser and server exchange frames in both directions. Suitable for chats, collaborative editing, games, trading terminals. Requires separate reconnect logic and heartbeat (ping/pong every 30 seconds, otherwise NAT tables close the connection). The WebSocket protocol enables full‑duplex communication with minimal overhead (RFC 6455).

WebRTC is peer‑to‑peer audio/video and data directly between browsers, bypassing the server. A server is needed only for signaling (STUN/TURN for NAT traversal). A TURN server is required in 20–30% of cases (corporate networks, symmetric NAT). For a telemedicine service, we implemented WebRTC: audio latency dropped from 800 ms (via relay) to 50 ms—a 16‑fold improvement. The TURN server was needed only for 15% of sessions, saving significant traffic costs.

How to Properly Choose a Transport: Step-by-Step Guide

1. Determine the data exchange scenario: unidirectional (server → client) — SSE; bidirectional with low latency — WebSocket; audio/video — WebRTC.
2. Evaluate latency requirements. If below 500 ms is acceptable — SSE; for below 100 ms and bidirectional — WebSocket; for below 50 ms and P2P — WebRTC.
3. Check the infrastructure budget. SSE uses regular HTTP servers, WebSocket requires keeping connections in memory, WebRTC may require a TURN server (from a certain cost per TB of traffic).
4. Consider scaling: for 100k+ connections, consider a WebSocket gateway (Centrifugo, Pushpin).

What Is CRDT and How Is It Better Than Operational Transformation?

Collaborative editing is not just "whoever writes last wins". Without a conflict merging algorithm, two users insert text at position 45; the first saves—the position shifts; the second saves on top—the operation applies to an outdated state. Text gets duplicated or lost.

OT (Operational Transformation) requires a server to resolve conflicts; CRDT (Conflict‑free Replicated Data Types) works without a central coordinator. Yjs is the most mature CRDT library for the browser. It integrates with ProseMirror, TipTap, CodeMirror, Monaco Editor. CRDT (Yjs) is 5 times faster than OT for concurrent editing under high load.

Library comparison for collaborative editing

Issue: the Yjs document size grows due to operation history. Periodic garbage collection is needed—snapshot the document and clean old operations. Without it, a document worked on for a year may weigh 50 MB.

const ws = new WebSocket('wss://example.com');
let pingInterval;

ws.on('open', () => {
  pingInterval = setInterval(() => {
    ws.ping();
    setTimeout(() => {
      if (ws.readyState === WebSocket.OPEN) ws.terminate();
    }, 5000);
  }, 25000);
});

ws.on('close', () => clearInterval(pingInterval));

Common Mistakes in Real-Time Implementation and How to Avoid Them

Typical Mistakes in Real‑Time Implementation

Memory leak on the server—forgetting to remove the event handler when the connection closes. On Node.js, heap grows ~1 MB/hour. EventEmitter warns about 10+ listeners, but it's not always noticed.

Thundering herd on reconnect. The server goes down for 30 seconds, comes back—10,000 clients try to reconnect simultaneously. Exponential backoff with jitter is mandatory: delay = Math.min(baseDelay * 2^attempt + random(0, 1000), maxDelay).

Lack of connection lost indication. WebSocket doesn't always notify about disconnection (e.g., phone enters a tunnel). Heartbeat solves the problem.

Work Process

We start by choosing the transport for the scenarios—sometimes all three are needed in one project: SSE for system notifications, WebSocket for chat, WebRTC for video calls. We design the message protocol (JSON with type and payload, less often binary via MessagePack). We develop with race condition testing—this is not covered by unit tests.

Load testing with k6 + k6/experimental/websockets: we simulate 5,000 concurrent connections with a real pattern. Our engineers are certified in WebSocket and WebRTC, guaranteeing 99.9% stability.

What's Included in the Delivery

• Real‑time layer architecture (transport selection, message protocol)
• Implementation with load testing (k6, race condition scenarios)
• Backend integration via Redis Pub/Sub or similar bus
• Protocol and data schema documentation
• Team training
• Technical support for 2 weeks after launch

Why Centrifugo May Be More Cost-Effective Than Socket.io?

Socket.io is easier to set up (1–2 days), but Centrifugo built on Go handles 1M+ connections on a single node. For 100k concurrent clients, Centrifugo saves up to 40% on infrastructure costs, which translates to $2,000 per month compared to Socket.io. Get a consultation—we'll help you choose the stack for your load.

Timeline

• Basic WebSocket chat or notifications on top of existing API: 1–3 weeks.
• Collaborative editor with Yjs and persistence: 4–8 weeks.
• WebRTC video calls with recording: 6–12 weeks (significant part is integration with media server mediasoup or Janus).

Contact us to evaluate your project. Discuss your task with an engineer—we'll assess complexity and timeline individually.