实时系统负载测试
学习如何模拟数千个并发连接，在真实用户遇到问题之前找出 WebRTC 和实时数据系统的性能极限。
实时系统负载测试 是 CoddyKit 上的免费 Real-Time Streaming Systems (WebRTC + Live Data) 课时。 这是第 4 节课，共 4 节。 你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。 这是 Real-Time Streaming Systems (WebRTC + Live Data) 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 Real-Time Streaming Systems (WebRTC + Live Data) 课程共包含 4 节课。
本课时的部分内容尚未翻译，以英文显示。
Why Real-Time Is Hard to Test
A REST endpoint can be load tested with simple request bursts. Real-time systems hold thousands of long-lived connections, each pushing and pulling continuously.
Load testing must model that sustained, stateful traffic, not just request counts.
What to Measure
- Concurrent connections the system holds.
- Messages per second in and out.
- End-to-end latency under load.
- Resource use: CPU, memory, file descriptors.
Connection Storms
Test not only steady state but the ramp: what happens when 10,000 clients reconnect at once after a deploy or network blip? This thundering herd often breaks systems that handle steady load fine.
Tools for WebSocket/SSE Load
Use tools built for persistent connections such as k6, Artillery, or Gatling. They open many sockets and script message flows.
A k6 WebSocket Script
Here is a minimal k6 scenario that opens a socket, sends a message, and listens for replies.
import ws from 'k6/ws';
export default function () {
ws.connect('wss://example.com/live', null, (socket) => {
socket.on('open', () => socket.send('hello'));
socket.on('message', (m) => console.log(m));
socket.setTimeout(() => socket.close(), 10000);
});
}Load Testing WebRTC
WebRTC is heavier: each virtual user needs a peer connection and media. Tools like KITE or headless browser farms simulate real media flows, while SFU-level harnesses inject synthetic RTP to stress forwarding.
Distributed Load Generation
One machine cannot open hundreds of thousands of sockets. Run load generators across many nodes so the generator is not the bottleneck. Aggregate their metrics centrally.
Watch the OS Limits
Each connection consumes a file descriptor. Raise ulimit -n and tune ephemeral port ranges on both the server and load generators, or you will hit artificial ceilings.
ulimit -n 1000000Defining Pass/Fail Thresholds
Set explicit SLOs so a test objectively passes or fails, for example p95 latency under 200ms and zero dropped connections up to 50k clients.
thresholds: {
ws_session_duration: ['p(95)<200'],
ws_connecting: ['p(99)<500']
}Find the Knee
Ramp connections steadily and watch where latency or errors spike, the knee of the curve. That number is your safe capacity per node and drives autoscaling thresholds.
Test in Production-Like Conditions
Run against the same instance sizes, load balancer, and TURN setup as production. A test on a laptop tells you little about cloud behavior under real network egress limits.
Quick Check
Test your understanding of load testing real-time systems.
Recap
Load test real-time systems by simulating sustained concurrent connections and reconnect storms with tools like k6 or Artillery, distributing generators, tuning OS limits, and ramping until you find the capacity knee against production-like infrastructure.
常见问题解答
「实时系统负载测试」课时是免费的吗？
是的 — 「实时系统负载测试」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 Real-Time Streaming Systems (WebRTC + Live Data) 课程的其余内容，请升级到 CoddyKit PRO。 Real-Time Streaming Systems (WebRTC + Live Data) 课程共包含 4 节课。
「实时系统负载测试」这节课中我会学到什么？
学习如何模拟数千个并发连接，在真实用户遇到问题之前找出 WebRTC 和实时数据系统的性能极限。 你通过在浏览器中直接运行的动手代码来练习 Real-Time Streaming Systems (WebRTC + Live Data)，全天候 AI 导师会在你学习这节课的过程中回答你的问题。
学习 Real-Time Streaming Systems (WebRTC + Live Data) 需要有经验吗？
无需任何先前经验。CoddyKit 上的 Real-Time Streaming Systems (WebRTC + Live Data) 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。 这是第 4 节课，共 4 节。
「实时系统负载测试」课时需要多长时间？
大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。
我能在这节 Real-Time Streaming Systems (WebRTC + Live Data) 课中编写并运行代码吗？
能。每节 Real-Time Streaming Systems (WebRTC + Live Data) 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。