SpectreDev | High-Performance Systems Engineering Alternative: SpectreDev

// PUBLISHED02.02.26

// TIME10 MINS

// TAGS

#GOLANG#WEBSOCKETS#PERFORMANCE

// AUTHOR

Spectre Command

// EXECUTIVE SUMMARY

>Goroutines start with a 2KB stack, compared to 1MB for OS threads.
>Use Worker Pools to cap concurrency and prevent CPU starvation.
>Zero-Copy networking libraries are essential for high-throughput websocket servers.

The Single-Threaded Event Loop is a brilliant architecture for I/O-bound microservices. It is a catastrophe for stateful, long-lived connections at scale.

When building real-time infrastructure (Signaling Servers, Market Data Feeds), we observed Node.js explicitly failing at the 10k concurrent connection mark due to GC pauses and context switching overhead.

We migrated the core websocket layer to Go. This is the architectural post-mortem.

The Memory Penalty

In V8 (Node.js), every WebSocket connection is an Object. At 100k connections, the heap size explodes, triggering the Garbage Collector to pause the world for hundreds of milliseconds. In a trading environment, a 200ms pause is unacceptable.

Go handles concurrency differently. It uses Goroutines—lightweight threads managed by the Go Runtime, not the OS.

Diagram comparing heavy OS threads consuming 1MB stack vs lightweight Goroutines consuming 2KB stack — FIG 1.0—FIG 2.1: OS THREADS VS GOROUTINES

The Worker Pool Pattern

Spawning a Goroutine per request is cheap, but not free. To handle 100k concurrents without exhausting system resources, we implement a strict Worker Pool pattern to cap active processing.

worker_pool.go

1package main
2
3import "sync"
4
5type Job interface {
6  Process()
7}
8
9type WorkerPool struct {
10  maxWorkers int
11  jobQueue   chan Job
12  wg         sync.WaitGroup
13}
14
15func NewWorkerPool(maxWorkers int) *WorkerPool {
16  pool := &WorkerPool{
17      maxWorkers: maxWorkers,
18      jobQueue:   make(chan Job),
19  }
20  // Initialize the fixed number of workers immediately
21  pool.start()
22  return pool
23}
24
25func (wp *WorkerPool) start() {
26  for i := 0; i < wp.maxWorkers; i++ {
27      wp.wg.Add(1)
28      go func() {
29          defer wp.wg.Done()
30          for job := range wp.jobQueue {
31              job.Process()
32          }
33      }()
34  }
35}

Ensure your jobQueue is buffered. If the buffer fills up, the producer will block, causing backpressure that can cascade upstream to your API Gateway. Always implement a select with a default/timeout case for non-blocking pushes.

Zero-Copy Upgrades

Standard Go net/http creates a new goroutine for every request. For WebSockets, we utilize Gobwas/ws or Gnet (event-loop networking for Go) to perform "Zero-Copy" upgrades. This allows us to read the frame header without allocating memory for the payload until we determine routing logic.

Benchmark Results (AWS c5.large)

| Metric | Node.js (ws) | Go (Goroutines) | Diff | | :--- | :--- | :--- | :--- | | Idle Memory (10k Conns) | 600MB | 85MB | -85% | | CPU (Message Broadcast) | 85% | 15% | -70% | | Max Concurrents | ~18k | ~150k | 8x |

Conclusion