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hotpath-rs

A Rust performance profiler for finding CPU, memory, async, SQL, HTTP, I/O and lock bottlenecks

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Open-source Rust profiler that shows exactly why code is slow by measuring CPU, memory, async functions, SQL queries, HTTP calls, I/O and lock contention.

Overview

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A look at hotpath.rs

hotpath-rs is a Rust performance profiling toolkit that helps developers find bottlenecks by showing where code spends time, burns CPU, and allocates memory. It can instrument functions, channels, futures, streams, SQL queries, HTTP calls, and byte-level I/O to distinguish between slow code that waits on I/O and CPU-intensive code.

The profiler offers multiple output modes: one-off performance reports, live TUI dashboards for real-time monitoring, Prometheus and Grafana integration for production, and CI regression detection. It can measure timing, memory allocations, async data flow, lock contention, SQL query performance, HTTP calls, I/O throughput, and Tokio runtime metrics.

It is designed with minimal setup overhead—features are opt-in and add no cost when disabled. Used by 192 open-source projects including PostHog, Apache OpenDAL, and MapLibre.

Feature notes

  • Time, CPU & memory profiling
  • Async observability for futures, channels and streams
  • I/O monitoring for files, TCP and compression streams
  • SQL query profiling for sqlx and Diesel
  • HTTP calls profiling for reqwest and ureq
  • HTTP server profiling for axum routes
  • Concurrency metrics for Mutex and RwLock
  • Tokio runtime monitoring
  • Prometheus & Grafana integration
  • CI regression detection with automatic benchmarking

Pricing

Pricing model: Open source

Free and open source under MIT license

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FAQ

What is the overhead of profiling with hotpath?
With the hotpath feature disabled, there is no overhead at all and every macro compiles to a no-op. With the feature enabled, overhead is a few tens of nanoseconds per instrumented operation, such as approximately 40 nanoseconds per function call and 30-90 nanoseconds per lock or channel operation.
Is it safe to profile production applications?
Yes, it is safe to profile production applications. The profiling pipeline is designed to keep a low and predictable overhead. To profile production safely, run your test suite with profiling enabled, avoid instrumenting very short hot functions, and review the metrics server configuration.
How is hotpath-rs different from Criterion.rs?
Criterion.rs is a statistics-driven benchmarking library for statistically rigorous measurements in a dedicated benchmark harness, while hotpath-rs profiles instrumented application code running real workloads to show where the program spends time, memory, and queries. hotpath-rs profiles many functions at once and collects signals beyond timing including SQL queries, HTTP calls, lock contention, and channel queues.
How is hotpath-rs different from hyperfine?
hyperfine is a command-line tool that measures whole-command performance with no code changes, while hotpath-rs requires adding instrumentation macros to show per-function timing, allocations, SQL queries, HTTP calls, locks, channels, and I/O. hyperfine treats programs as black boxes, while hotpath-rs looks inside to attribute costs to specific functions and operations.
How do I profile async Rust and Tokio applications?
Add #[hotpath::measure] to an async function to record its wall-clock time and allocations. Use #[hotpath::measure(future = true)] to also track poll counts, poll durations, and whether each call completed or was cancelled. Async function profiling works on any async runtime including Tokio and smol.

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