Rust for Backend Services: When and Why

March 5, 2018

Rust has moved from systems programming curiosity to serious contender for backend services. Companies like Dropbox, Discord, and Cloudflare run Rust in production. The promise is compelling: memory safety without garbage collection, with C-like performance.

But is Rust right for your backend services? Let’s examine honestly.

What Rust Offers

Memory Safety Without GC

Rust’s ownership system prevents memory errors at compile time:

This happens without garbage collection pauses.

fn process_data(data: Vec<u8>) -> Result<String, Error> {
    // data is moved here, original owner can't use it
    let processed = transform(data)?; // Error handling is explicit
    Ok(String::from_utf8(processed)?)
}

Predictable Performance

No GC pauses means:

For latency-sensitive services, this matters.

Zero-Cost Abstractions

High-level abstractions compile to efficient code:

// This is as fast as hand-written loops
let sum: i64 = values
    .iter()
    .filter(|x| x.is_valid())
    .map(|x| x.value())
    .sum();

Excellent Error Handling

Errors are explicit and must be handled:

fn fetch_user(id: UserId) -> Result<User, FetchError> {
    let response = http_client.get(&format!("/users/{}", id))?;
    let user: User = response.json()?;
    Ok(user)
}

No hidden exceptions, no null returns. The type system enforces error handling.

Strong Concurrency Story

Rust prevents data races at compile time:

use std::sync::Arc;
use std::thread;

let data = Arc::new(vec![1, 2, 3]);

let handles: Vec<_> = (0..10).map(|_| {
    let data = Arc::clone(&data);
    thread::spawn(move || {
        // data is safely shared across threads
        println!("{:?}", data);
    })
}).collect();

for handle in handles {
    handle.join().unwrap();
}

“Fearless concurrency” is real—the compiler catches data race bugs.

When Rust Makes Sense

Performance-Critical Services

If you’re counting microseconds:

Rust’s performance characteristics matter here.

Latency-Sensitive Services

GC pauses create latency spikes. If your SLOs are tight:

Rust’s predictability helps meet stringent latency requirements.

Resource-Constrained Environments

Low memory, limited CPU:

Rust’s efficiency means more with less.

Security-Critical Services

Memory safety prevents entire vulnerability classes:

If a memory safety vulnerability would be catastrophic, Rust’s guarantees provide value.

When Rust Doesn’t Make Sense

Team Inexperience

Rust has a steep learning curve:

A team learning Rust while building production services will be slow and make mistakes. Consider whether the learning investment is justified.

Rapid Prototyping

When velocity matters most:

Python, Go, or Node.js will get you there faster.

Most CRUD Applications

Standard web applications with:

Performance isn’t the bottleneck. Developer velocity is. Rails, Django, or Go are likely better choices.

Small Teams

Rust requires more expertise. Small teams may not have:

The hiring pool is also smaller.

Practical Considerations

Ecosystem Maturity

Rust’s ecosystem is younger than Go, Java, or Python:

Strong areas:

Weaker areas:

Evaluate your specific dependencies.

Build Times

Rust builds are slow compared to Go:

Mitigation strategies:

Learning Curve

Expect 3-6 months before a team is productive:

Factor this into timelines.

Hiring

The Rust talent pool is smaller:

Consider whether you can attract and retain Rust talent.

A Balanced Approach

Gradual Introduction

Start with low-risk, high-value components:

Learn before betting production services.

Polyglot Strategy

Use Rust where it shines, other languages elsewhere:

You don’t need to go all-in.

FFI for Hot Paths

Call Rust from other languages:

# Python calling Rust via PyO3
import my_rust_lib

result = my_rust_lib.process_data(data)  # Fast path in Rust

Get Rust benefits without rewriting everything.

Example Architecture

┌─────────────────────────────────────────────────┐
│                    API Gateway                  │
│                     (Go)                        │
└─────────────────────────────────────────────────┘
                        │
        ┌───────────────┼───────────────┐
        │               │               │
   ┌────▼────┐    ┌────▼────┐    ┌────▼────┐
   │  User   │    │  Order  │    │ Payment │
   │ Service │    │ Service │    │ Service │
   │  (Go)   │    │  (Go)   │    │  (Go)   │
   └────┬────┘    └────┬────┘    └────┬────┘
        │              │              │
        │         ┌────▼────┐         │
        │         │  Fraud  │         │
        │         │Detection│         │
        │         │ (Rust)  │         │
        │         └─────────┘         │
        │                             │
   ┌────▼────────────────────────────▼────┐
   │           Message Broker              │
   │              (Kafka)                  │
   └──────────────────────────────────────┘
                     │
              ┌──────▼──────┐
              │   Stream    │
              │  Processor  │
              │   (Rust)    │
              └─────────────┘

Rust for fraud detection (latency-critical) and stream processing (throughput-critical). Go for typical services.

Getting Started

If you decide to try Rust:

Start with CLI Tools

Internal tools with clear requirements:

Low risk, good learning opportunity.

Invest in Training

Don’t expect immediate productivity:

Join the Community

The Rust community is helpful:

Measure Carefully

Validate that Rust delivers expected benefits:

Key Takeaways

Rust is a powerful tool for the right problems. The key is honest assessment of whether your problems are the right ones.