Unleashing JavaScript for WebSocket load testing

As modern applications demand real-time communication at scale, WebSocket has become a foundational protocol for delivering interactive, low-latency user experiences. From multiplayer games to collaborative tools, and increasingly, AI-driven interfaces, developers are turning to WebSockets to meet rising performance expectations.

But building a fast, responsive system is only half the challenge. The real question is: can it scale under pressure?

That’s where WebSocket load testing becomes essential. Unlike traditional HTTP testing, simulating thousands of concurrent, long-lived WebSocket connections introduces a unique set of challenges, especially when your architecture needs to handle real-time bi-directional messaging.

Take AI-powered chatbots, for example. Whether it’s a healthcare assistant answering benefit questions or a retail concierge guiding customers to the right product, these systems often rely on persistent WebSocket connections to maintain smooth, back-and-forth conversations. But what happens when your chatbot needs to juggle 10,000+ conversations at once?

In this post, we’ll discuss how you can use Gatling’s JavaScript SDK to unleash full control over WebSocket behavior in your load tests, including a working example simulating a high-volume AI chatbot workload.

The real-time imperative

Traditional HTTP APIs fall short in scenarios that demand continuous, instantaneous interaction. WebSocket, with their persistent connections and bidirectional data flow, are the backbone of real-time chatbot performance. They ensure:

• Reduced latency for user inputs and AI-generated responses
• Seamless conversational flows without re-establishing connections
• Efficient bandwidth usage and scalability

But with great power comes great complexity. WebSocket introduces new performance testing challenges that standard HTTP load tests can't account for.

AI inference: A double-edged sword

Adding AI to the mix introduces another variable: model inference time. Unlike static responses, AI replies are dynamic and may involve streaming partial results, interacting with third-party services, or running heavy computations. These behaviors can vary wildly depending on the model, the query, or the infrastructure.

If you aren’t testing these patterns under realistic conditions, you risk discovering performance bottlenecks in production when it’s too late.

Why Gatling’s JavaScript SDK changes the game

The release of WebSocket support in Gatling’s JavaScript SDK opens a new world of possibilities for developers and QA engineers:

• Test in the same language as your chatbot frontend: JavaScript is the lingua franca for web-based bots. Now, you can write and simulate realistic usage patterns directly in JS.
• Model complex user flows: Simulate typing delays, mid-conversation disconnects, or even concurrent sessions per user.
• Measure what matters: Correlate test results with your server-side observability tools and go beyond transport-level metrics. Observe backend performance, AI latency, and session stability under load.

A sample scenario: Open enrollment chaos

Imagine a large health insurance provider that offers a chatbot to help users navigate benefit options during open enrollment season. A fine-tuned LLM powers the chatbot and uses WebSocket for real-time interaction.

At peak, thousands of users are asking nuanced questions, uploading documents, and requesting help. Concurrent WebSocket sessions, AI inference requests, and integration with eligibility databases strain the backend.

By simulating this traffic with Gatling’s JavaScript SDK:

• The dev team identifies that inference latency spikes after 7,500 concurrent users
• The ops team pinpoints memory leaks in session state handling
• The product team gains confidence before go-live

Don't forget: Test what you ship

Real-time AI chat is no longer experimental; it’s becoming the default experience. But with more complexity comes greater risk. Gatling’s new WebSocket testing capabilities empower teams to validate performance and reliability at scale proactively.

If your chatbot uses WebSocket and AI, you can’t afford to skip this step. Load testing isn't just about keeping servers up; it's about ensuring your users stay engaged, supported, and delighted.

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