FlowGuard

🎯 About the Project Created and developed by: Cleiton Augusto Correa Bezerra Adaptive Concurrency Control and Backpressure for Axum/Tower

The Problem: Static Limits are a Guessing Game

When building resilient microservices in Rust, setting a static concurrency limit (like semaphore::Permits or a fixed worker pool) is a common but fragile approach.

• Set the limit too high, and a sudden spike can overwhelm your database or external API, causing a cascading failure.
• Set it too low, and you're wasting resources and unnecessarily throttling valid traffic.

You're left tuning a magic number based on guesses rather than the actual health of your system.

The Solution: Adapt Based on Latency

FlowGuard is a Tower service layer that implements adaptive concurrency control. Instead of a fixed limit, it dynamically adjusts the number of concurrent in-flight requests by monitoring their latency (round-trip time).

• When latency increases, it reduces the concurrency limit, applying backpressure at the edge of your service.
• When the system is responsive, it cautiously increases the limit to utilize available capacity.

The core algorithm is inspired by TCP Vegas, a congestion control algorithm known for its efficiency and low latency.

Quick Start with Axum

Add FlowGuard to your Cargo.toml:

[dependencies]
flow-guard = "0.1"
Protect an Axum router in minutes:

rust
use axum::{routing::get, Router};
use flow_guard::{FlowGuardLayer, strategy::VegasStrategy};
use tower::ServiceBuilder;

#[tokio::main]
async fn main() {
    // Start with an initial limit of 10 concurrent requests.
    let strategy = VegasStrategy::new(10);
    let app = Router::new()
        .route("/api", get(|| async { "Hello, guarded world!" }))
        .layer(ServiceBuilder::new().layer(FlowGuardLayer::new(strategy)));

    // ... bind and serve as usual
}
When the limit is reached, the layer returns a 503 Service Unavailable response, signaling to callers (or upstream load balancers) to back off.

How It Works: The Vegas Strategy
The Vegas strategy inside FlowGuard maintains two key metrics:

Base RTT: The minimum observed round-trip time (system's healthy baseline).

Current RTT: The latency of recent requests.

The algorithm continuously compares them. If the current RTT consistently exceeds the base RTT by a certain threshold (alpha), it infers the system is congested and reduces the concurrency limit. If everything is fast, it slowly probes for more capacity.

You can tune the sensitivity:

rust
let strategy = VegasStrategy::new(10)
    .with_alpha(2)   // Lower = more sensitive to latency increases
    .with_beta(4);   // Higher = more aggressive in adding capacity
Core Features
Adaptive, Not Static: Eliminates the need for static concurrency limits.

Tower & Axum Native: Works seamlessly with the Rust service ecosystem.

Minimal Overhead: Built with performance in mind using efficient data structures.

Informative Errors: Integrates with Tower's error handling to provide clear backpressure signals.

Is This Production Ready?
FlowGuard is a young crate (v0.1.x). It implements a proven algorithm, but its integration and edge cases are being refined. The current version is best suited for:

Evaluation and testing in staging environments.

Services where the primary risk is overloading a downstream dependency (like a database).

Important considerations:

The state is per-service-instance. For a cluster-wide limit, you need a distributed coordinator (a planned future feature).

Like any adaptive system, it needs traffic to "learn". Its behavior with very low traffic or bursty patterns is still being observed.

Contributions, bug reports, and real-world deployment stories are incredibly valuable to help mature this project.

🤝 Contributing
Contributions are the heart of the Rust community! Feel free to submit pull requests or open issues.

Author: Cleiton Augusto Correa Bezerra
Email: augusto.cleiton@gmail.com
LinkedIn: cleiton-augusto-b619435b

📄 License
This project is licensed under the MIT License - see the LICENSE file for details.

Made with ❤️ and Rust