hotpath - Rust Profiler for Easy Performance Debugging

A simple Rust profiler that shows exactly why your code is slow.

Performance feedback for developers and coding agents. Find CPU, memory, async, SQL, I/O and contention bottlenecks with a single Rust profiler. Export metrics to Prometheus and Grafana when you need production monitoring.

Try the TUI demo via SSH - no installation required:

ssh demo.hotpath.rs

Or let your own AI agent configure profiling in a repo:

cargo install hotpath
hotpath init --agent claude # or --agent codex / --agent opencode

hotpath-rs is an easy-to-configure Rust performance profiling toolkit that shows exactly where your code spends time, burns CPU, and allocates memory.

It helps you distinguish between functions that are slow because they wait on I/O and those that are CPU-intensive. Instrument functions, channels, futures, streams, SQL queries, HTTP calls, and byte-level I/O to find bottlenecks and focus optimizations where they matter most. Get actionable insights into time, memory, and async data flow with minimal setup.

Explore the full documentation at hotpath.rs. See CONTRIBUTING.md for development setup and guidelines.

You can use it to produce one-off performance (timing, memory or CPU) reports:

correlate all performance signals in Grafana with minimal profiling overhead:

catch performance regressions on every pull request with a simple CI integration:

inspect throughput and latency of network, file or compression I/O streams:

analyze SQL/HTTP calls performance with automatic source function attribution:

monitor throughput, performance and max queue depth of instrumented channels:

or use the live TUI dashboard to monitor real-time performance and async data flow metrics with debug info:

https://github.com/user-attachments/assets/2e890417-2b43-4b1b-8657-a5ef3b458153

Features

• Time, CPU & memory profiling - identify expensive functions, allocation hotspots, and investigate memory leaks.
• Async observability - futures, channels and streams.
• I/O monitoring - bytes, throughput, latency of any sync or async IO stream like files, TCP, or compression.
• SQL query profiling - query performance metrics for sqlx and Diesel.
• HTTP calls profiling - per-endpoint latency and error metrics for reqwest and ureq.
• HTTP server profiling - per-route response time and error metrics for axum.
• Concurrency metrics - Mutex/RwLock wait time and contention.
• Tokio runtime monitoring - workers, scheduling and queues.
• Prometheus & Grafana integration - export profiling metrics to your existing dashboards.
• Live TUI dashboard & static reports - real-time or one-off analysis.
• CI regression detection - benchmark every PR automatically.
• MCP server for AI agents - query profiling data in real time.
• Zero cost when disabled - fully feature-gated.

Getting Started

AI Setup (Recommended)

The quickest way to set up hotpath is to let your own AI coding agent do it. Install the hotpath CLI and run init inside your project repo:

cargo install hotpath --version '^0.28'
hotpath init --agent claude # or --agent codex / --agent opencode