Rust in Backend Production — Why We're Switching

Rust is no longer just a language for systems programmers and enthusiasts. In 2026, we’re deploying it in production backends — and the numbers speak clearly. Why we’re switching from Go and Java, what surprised us, and where Rust still doesn’t make sense.

Why Rust in the Backend — Now¶

Rust was long considered too complex for enterprise environments. The borrow checker, lifetimes, no garbage collector — all of this deterred teams used to Go or Java. What changed?

• The ecosystem matured: Axum, Actix-web, and Tokio are battle-tested frameworks in 2026 with rich documentation
• AI-assisted coding: Claude, Copilot, and Cursor dramatically reduce the learning curve — the borrow checker errors are resolved by AI for you
• Cloud costs: For the same workload, Rust consumes 3–10× less RAM and CPU than Java/Go, which at 2026 cloud prices is not negligible
• Supply chain security: Cargo and crates.io have the best security audit tooling in the entire ecosystem

Real Numbers: API Gateway Migration¶

One of our clients operated an API gateway in Go (Gin framework), processing 15,000 req/s. After migration to Rust (Axum + Tokio):

• P99 Latency: from 45 ms to 8 ms (5.6× improvement)
• Memory: from 2.4 GB to 180 MB (13× savings)
• CPU: from 8 vCPU to 2 vCPU at the same load
• Cloud costs: -62% monthly

The migration took 3 months with 2 Rust developers. Payback period: 4 months thanks to infrastructure savings.

Where Rust Excels¶

Not every backend needs Rust. Based on our experience, we identify sweet spots:

• High-throughput API: Gateway, proxy, real-time streaming — anything with >5000 req/s
• Data processing pipeline: ETL, transformations, aggregation of large datasets
• Edge services: Low latency, limited resources, WASM deployment
• Security-critical: Authentication, encryption, token validation — zero memory bugs
• Long-running services: No GC pauses, predictable latency

Where Rust Doesn’t (Yet) Make Sense¶

Let’s be honest — Rust isn’t always the right choice:

• CRUD microservices: Simple REST API with a database? Go or TypeScript will be faster to develop
• Rapid prototyping: A startup that needs an MVP in 2 weeks doesn’t have time for the borrow checker
• Small teams without Rust experience: The learning curve is real, even with AI help count on 2–3 months to productivity

Practical Tips for Migration¶

If you’re considering Rust in production, we recommend a gradual strategy:

1. Strangler fig pattern: Migrate individual services, not the entire system at once
2. Start with the performance-critical path: You’ll get the biggest ROI from the most loaded services
3. Invest in tooling: cargo-watch, cargo-nextest, flamegraph — productivity depends on tools
4. Shared libraries: Create an internal crate with common patterns (error handling, config, telemetry)
5. CI/CD pipeline: Rust compilation is slow — cache dependencies, use sccache

Rust Ecosystem in 2026¶

The ecosystem has advanced significantly in the past year:

• SQLx 0.9: Compile-time checked SQL queries, zero-cost abstraction over PostgreSQL
• Axum 0.8: Stable, ergonomic web framework with excellent tower middleware compatibility
• OpenTelemetry Rust: Full support for traces, metrics, and logs
• Shuttle & Spin: Serverless Rust deployment — deploy in seconds

Rust Is an Investment That Pays Off¶

Higher initial development costs are compensated by lower operational costs, better performance, and elimination of entire categories of bugs. In 2026, it’s a legitimate choice for production backends — not an experiment.

Our tip: Pick one performance-critical service, migrate it to Rust, and measure the results. The numbers speak for themselves.