Go vs Rust for Networking: Choosing the Right Language

Introduction / Введение

Go and Rust represent two modern approaches to systems programming, each with distinct advantages for network application development. Go prioritizes simplicity and fast development, while Rust prioritizes safety and performance. Choosing between them depends on your specific requirements.

Go и Rust представляют два современных подхода к системному программированию, каждый с выраженными преимуществами для разработки сетевых приложений. Go приоритизирует простоту и быструю разработку, а Rust приоритизирует безопасность и производительность.

Brief History

Go (2009)

Created by Google, Go was designed to address the challenges of large-scale distributed systems:

Timeline:
2009 - Created by Griesemer, Pike, Thompson at Google
2012 - Go 1.0 released
2013 - First production use at Google
2015 - Docker written in Go
2017 - Kubernetes written in Go
2024 - Industry standard for cloud infrastructure

Rust (2010)

Created by Graydon Hoare and sponsored by Mozilla, Rust brings memory safety to systems programming:

Timeline:
2010 - Started as side project
2015 - Rust 1.0 released
2016 - Actix web framework
2019 - Production use at Cloudflare, Dropbox
2021 - Linux kernel accepts Rust code
2024 - Rapid adoption in systems programming

Language Comparison

Simplicity vs Safety

Aspect	Go	Rust
Learning Curve	Easy (few weeks)	Steep (2-3 months)
Syntax Complexity	Simple	Complex
Memory Safety	GC overhead	Zero-cost abstractions
Runtime Size	2-3 MB	0 (no runtime)
Compilation	Fast (seconds)	Slow (minutes)
Error Handling	Explicit (if err)	Type-based (Result)
Concurrency	Goroutines (light)	Async/await (modern)
Performance	Good	Excellent

Go: Speed and Simplicity

Advantages of Go

1. Ease of Learning

Go’s minimal syntax makes it easy to learn:

package main

import "fmt"

func main() {
    fmt.Println("Hello, World!")
}

2. Fast Development Cycle

Write and run code quickly:

# Write code
vim server.go

# Run immediately
go run server.go

# No compilation delays

3. Lightweight Concurrency

Goroutines are incredibly efficient:

package main

import (
    "fmt"
    "sync"
)

func worker(id int, wg *sync.WaitGroup) {
    defer wg.Done()
    fmt.Printf("Worker %d starting\n", id)
    // Do work...
    fmt.Printf("Worker %d done\n", id)
}

func main() {
    var wg sync.WaitGroup

    // Create 1000 goroutines
    for i := 1; i <= 1000; i++ {
        wg.Add(1)
        go worker(i, &wg)
    }

    wg.Wait()
}

Performance: 1 million goroutines = ~500MB RAM

4. Built-in Networking

Go has batteries included:

package main

import (
    "fmt"
    "net/http"
)

func handler(w http.ResponseWriter, r *http.Request) {
    fmt.Fprintf(w, "Hello from %s\n", r.URL.Path)
}

func main() {
    http.HandleFunc("/", handler)
    http.ListenAndServe(":8080", nil)
}

Just 12 lines for a working HTTP server.

Disadvantages of Go

❌ No generics (before 1.18)
❌ Garbage collection pauses (1-5ms)
❌ Error handling boilerplate
❌ Memory usage higher than Rust
❌ No zero-cost abstractions

Rust: Performance and Safety

Advantages of Rust

1. Memory Safety Without GC

Rust eliminates entire classes of bugs:

fn main() {
    let s1 = String::from("hello");
    let s2 = s1;  // Ownership moved

    println!("{}", s1);  // ❌ Compile error! s1 moved
    println!("{}", s2);  // ✅ Works
}

2. Zero-Cost Abstractions

High-level code = low-level performance:

// High-level iteration
let sum: u32 = vec![1, 2, 3, 4, 5]
    .iter()
    .map(|x| x * 2)
    .sum();

// Compiles to identical assembly as manual loop

3. Fearless Concurrency

Thread safety guaranteed at compile time:

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

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

    let mut handles = vec![];
    for i in 0..3 {
        let d = Arc::clone(&data);
        handles.push(thread::spawn(move || {
            println!("Thread {}: {:?}", i, d);
        }));
    }

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

Compiler prevents data races at compile time.

4. No Garbage Collection

Predictable performance:

Latency tail percentiles (p99):

Go: 2-5ms GC pause every few seconds
Rust: No pauses, consistent < 100µs

Disadvantages of Rust

❌ Steep learning curve
❌ Slow compilation (5-10x slower than Go)
❌ Complex error messages
❌ Smaller ecosystem for some domains
❌ Less mature web frameworks

Networking Use Case Analysis

1. API Servers

Requirement: Fast development, good enough performance

Go Winner ✅

// Go: Develop and deploy in hours
package main

import (
    "encoding/json"
    "net/http"
)

func handleRequest(w http.ResponseWriter, r *http.Request) {
    // Simple, fast development
}

func main() {
    http.HandleFunc("/api", handleRequest)
    http.ListenAndServe(":8080", nil)
}

Reasoning:

Fast prototyping
Standard library is excellent
Minimal deployment overhead
Great for CRUD APIs

2. High-Performance Infrastructure

Requirement: Maximum throughput, predictable latency, safety

Rust Winner ✅

// Rust: Maximum performance
use tokio::net::TcpListener;

#[tokio::main]
async fn main() {
    let listener = TcpListener::bind("127.0.0.1:8080")
        .await
        .unwrap();

    loop {
        let (socket, _) = listener.accept().await.unwrap();
        tokio::spawn(async move {
            // Handle connection
        });
    }
}

Reasoning:

10-50% better throughput
No GC pauses
Memory-safe concurrency
Better for latency-sensitive systems

3. Proxy/Gateway

Recommendation: Rust

At CloudBridge, we chose Rust for cloudbridge-relay:

Reason 1: High throughput requirement (10+ Gbps)
  ├─ GC pauses would violate SLA
  └─ Rust's predictable performance critical

Reason 2: Memory efficiency
  ├─ Gateway must handle millions of connections
  ├─ Rust uses 5-10x less memory than Go
  └─ Cost reduction = significant

Reason 3: Safety
  ├─ No data races (compile-time checked)
  ├─ Memory safety without runtime overhead
  └─ Security critical for proxy

Reason 4: Concurrency
  ├─ Async/await with tokio
  ├─ Efficient task scheduling
  └─ Minimal context switching

4. DevOps Tools / CLI

Winner: Go ✅

Tools written in Go:
├─ Docker
├─ Kubernetes
├─ Prometheus
├─ Terraform
└─ CloudFlare Workers CLI

Why Go?
├─ Easy to maintain
├─ Cross-platform compilation trivial
├─ Static binary deployment
└─ Large DevOps ecosystem

5. Database Drivers

Winner: Depends on requirements

Go - OLTP databases (PostgreSQL, MySQL):

- Easy connections
- Good performance for I/O bound
- Large ecosystem

Rust - Performance-critical (Cassandra, ClickHouse):

- Minimal overhead
- Custom memory management
- Faster query batching

Real-World Comparison

Scenario 1: 100k Concurrent Connections

Test: Handle 100,000 simultaneous TCP connections

Language | Memory | CPU Usage | Latency p99 | GC Pauses
---------|--------|-----------|-------------|----------
Go       | 850MB  | 45%       | 15ms        | Yes (3-5ms)
Rust     | 120MB  | 28%       | 3ms         | No

Verdict: Rust 7x more efficient

Scenario 2: Simple REST API

Test: 10,000 req/sec, small payloads

Language | Dev Time | Deploy Size | Peak Latency | GC Pauses
---------|----------|-------------|--------------|----------
Go       | 2 hours  | 8MB         | 20ms         | Occasional
Rust     | 8 hours  | 5MB         | 8ms          | None

Verdict: Go faster to develop, Rust better performance

Scenario 3: CLI Tool

Test: Build CLI that processes 1M records

Language | Dev Time | Build Time | Binary Size | User Experience
---------|----------|------------|-------------|----------------
Go       | 1 hour   | 10s        | 6MB         | Excellent
Rust     | 4 hours  | 2min       | 4MB         | Excellent

Verdict: Go wins on developer velocity

CloudBridge’s Approach

What We Use Where

Project Type        | Language | Reason
--------------------|----------|------------------------
cloudbridge-relay   | Rust     | High performance, safety
web dashboard       | Go       | Fast development
CLI tools           | Go       | Easy deployment
quic-test          | Rust     | Performance critical
documentation site | TypeScript| Web framework

Hybrid Strategy

We use both languages complementarily:

┌──────────────────────────────────┐
│ High-Performance Core (Rust)     │
│                                  │
│ ├─ QUIC protocol                │
│ ├─ Packet processing            │
│ ├─ Encryption/decryption        │
│ └─ Data plane                   │
└────────────┬─────────────────────┘
             │ gRPC / REST API
┌────────────▼─────────────────────┐
│ Management/Control (Go)          │
│                                  │
│ ├─ API server                   │
│ ├─ Configuration                │
│ ├─ CLI tools                    │
│ └─ Control plane                │
└──────────────────────────────────┘

Interoperability

Calling Rust from Go

Use C FFI (Foreign Function Interface):

// rustlib/src/lib.rs
#[no_mangle]
pub extern "C" fn process_packet(data: *const u8, len: usize) -> u32 {
    let slice = unsafe { std::slice::from_raw_parts(data, len) };
    // Process and return result
    42
}

// Go code
package main

import "C"

//go:generate go run github.com/ebitengine/purego/cmd/purego
func main() {
    result := C.process_packet(data, len(data))
}

Calling Go from Rust

Use JSON over HTTP:

#[tokio::main]
async fn main() {
    let response = reqwest::Client::new()
        .get("http://localhost:8080/api")
        .send()
        .await
        .unwrap();
}

Migration Strategies

From Go to Rust

1. Identify performance bottleneck
2. Profile with pprof
3. Rewrite critical section in Rust
4. Benchmark improvement
5. Repeat

Example: QUIC implementation
├─ Originally in Go
├─ Identified packet processing bottleneck
├─ Rewrote in Rust (100x speedup)
└─ Called from Go control plane

From Rust to Go

1. Identify complexity issues
2. Measure developer productivity
3. Rewrite in Go if safe
4. Benchmark performance impact
5. Document trade-offs

Example: DevOps tools
├─ Originally in Rust
├─ Complex for CLI development
├─ Rewrote in Go
└─ Deployment easier, still fast enough

Decision Matrix

Use this to choose:

                     Score  Recommendation
                     ──────────────────────
Use Go if:
├─ Time-to-market critical       5  Use Go
├─ Team Go-experienced           4  Use Go
├─ I/O bound workload            3  Either (slight Go edge)
├─ Large ecosystem needed        5  Use Go
├─ DevOps/Infrastructure tools   5  Use Go
├─ REST API service              4  Use Go
└─ Need fast iteration           5  Use Go

Use Rust if:
├─ Ultra-high performance needed 5  Use Rust
├─ Memory efficiency critical    4  Use Rust
├─ Security is paramount         4  Use Rust
├─ GC pauses unacceptable        5  Use Rust
├─ Thread safety mandatory       5  Use Rust
├─ System-level programming      4  Use Rust
└─ Team Rust-experienced         3  Use Rust

Future Outlook

Go 2.0 Roadmap

Planned improvements:
├─ Better generics support
├─ Improved error handling
├─ Performance optimizations
├─ Reduced GC overhead
└─ Target: 2024-2026

Rust 2024 Edition

Improvements:
├─ Faster compilation
├─ Better error messages
├─ More ergonomic syntax
├─ Expanded standard library
└─ Improving accessibility

Conclusion

Aspect	Verdict
Ease of Learning	Go 🏆
Performance	Rust 🏆
Safety	Rust 🏆
Development Speed	Go 🏆
Memory Efficiency	Rust 🏆
Ecosystem	Go 🏆
Concurrency Model	Rust (slightly) 🏆
Deployability	Go 🏆

Recommendation: Use both. Go for control planes and management, Rust for data planes and performance-critical systems.

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