Why We Built an AI Gateway in Rust: A Performance-Centric Decision

When building our AI gateway, we knew performance would be a critical factor. Unlike most AI software written in Python, an AI gateway acts as the proxy layer between users and inference engines. This gateway must handle high concurrency, low latency, and large data volumes efficiently. Python, while dominant in the AI ecosystem, struggles under these demands due to its runtime overhead and limitations with concurrency.

To demonstrate why we chose Rust, we benchmarked three popular programming environments—Rust, Python, and JavaScript (Node.js)—to evaluate their performance under high-load conditions. Rust emerged as the clear winner, offering predictable and stable performance even at scale.

Benchmark Setup: Simulating Real-World AI Traffic

We built an HTTP/2 streaming server and a corresponding client to mimic real-world AI workloads. Here’s how the setup worked:

Server:

• Streams tokens at a fixed inter-token latency of 25ms, similar to the tokenized output of an AI inference engine.

• Uses HTTP/2 to deliver tokenized data efficiently to multiple clients.

• Implements asynchronous programming to support thousands of connections concurrently.

Client:

• Gradually establishes up to 15,000 simultaneous connections to the server.

• Measures the intra-token latency—the time between consecutive tokens received from the server. This metric reflects the server’s ability to scale under increasing load.

• Ensures that connections remain stable and records latency for each connection.

Test Workflow:

1. The server was implemented in Rust, Python, and JavaScript (Node.js) to ensure a fair comparison.

2. The client progressively increased the number of active connections, starting with a small number and scaling up to 15,000.

3. Intra-token latency measurements were collected for each implementation to evaluate performance under load.

Results: Rust vs. Python vs. JavaScript (Node.js)

The chart below illustrates the intra-token latency (in milliseconds) as the number of concurrent connections increases:

Key Observations:

• Rust:

  • Rust exhibited the most stable performance, maintaining a near-linear increase in latency as connections scaled.
  • At 15,000 connections, Rust's intra-token latency reached approximately 75ms, only 3x the baseline inter-token latency of 25ms.
  • Rust’s efficiency highlights its ability to handle high concurrency without significant degradation.

• Python:

  • Python's intra-token latency grew exponentially, exceeding 200ms at 15,000 connections.
  • This exponential growth demonstrates Python's inherent limitations in managing large-scale concurrency and resource contention.

• JavaScript (Node.js):

  • Node.js initially performed better than Python, maintaining lower latency up to 7,500 connections.

  However, its performance began to degrade significantly beyond this point, reaching over 150ms at 15,000 connections.

  • This result underscores Node.js’s event-driven model, which works well for moderate concurrency but struggles under extreme loads.

Why Rust is the Best Choice for an AI Gateway

1. Predictable, Scalable Performance:

   Rust’s ability to maintain 75ms latency at 15,000 connections demonstrates its scalability. Its near-linear latency growth makes it ideal for high-concurrency systems.

2. Concurrency Without Compromise:

   Rust’s async programming model (e.g., Tokio) efficiently manages thousands of simultaneous connections. Unlike Python, Rust avoids the bottlenecks of the Global Interpreter Lock (GIL) and utilizes system resources optimally.

3. Resource Efficiency:

   Rust compiles directly to machine code, ensuring minimal runtime overhead. Its memory safety and zero-cost abstractions allow for predictable and efficient resource management.

4. Low-Level Control:

   Rust provides fine-grained control over threading and memory, making it the best choice for performance-critical applications like AI gateways.

Why Python and JavaScript Fall Short

1. Python:

   Concurrency Limitations: The GIL prevents true multi-threading, causing severe bottlenecks under high load.

   Runtime Overhead: Python's interpreted nature adds significant latency, making it unsuitable for latency-sensitive applications.

   Exponential Growth: As connections increase, Python's performance deteriorates rapidly, with latency exceeding acceptable thresholds.

2. JavaScript (Node.js):

   Event-Driven Model: Node.js performs well under moderate concurrency but struggles as the number of simultaneous connections grows beyond 7,500.

   Resource Contention: While Node.js handles asynchronous I/O well, it lacks the low-level control offered by Rust, leading to degraded performance at scale.

Why AI Gateways Must Be Built with Performance in Mind

An AI gateway is more than a simple intermediary. It plays a critical role in ensuring:

• Real-Time Responses: Users expect tokenized outputs to arrive with minimal delay, making low latency essential.

• Scalability: AI gateways must handle thousands or tens of thousands of simultaneous connections to accommodate large-scale applications.

• Reliability: Inconsistent performance or connection drops can severely impact user experience and application reliability.

Rust excels in all these areas, delivering predictable, stable performance at scale, making it the ideal language for building high-performance AI gateways.

The Takeaway: Rust is the Future of AI Gateways

Our benchmark results clearly show that while Python and JavaScript (Node.js) have their strengths, they are ill-suited for building performance-critical AI gateways:

• Python struggles with concurrency and runtime overhead, leading to exponential latency growth.

• Node.js performs better but falters under extreme loads, making it unreliable for high-concurrency scenarios.

Rust, on the other hand, delivers consistent, scalable performance with low latency, even at 15,000 connections. By choosing Rust for our AI gateway, we’ve built an infrastructure that can handle the demands of modern AI applications with ease.

If you’re building an AI gateway or any performance-critical infrastructure, Rust isn’t just an option—it’s the solution. When every millisecond matters, Rust is the language that ensures you meet the challenge head-on.