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Joshua Varghese
Joshua Varghese

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Building Loom (Part 3): Real-Time Browser UI with SSE, Goroutines, and Channels

This is Part 3 of my series building Loom.

πŸ‘‰ Missed Part 2? Read it here

Today: Building the real-time browser UI with SSE, goroutines, and channels. One request β†’ three outputs simultaneously.

GitHub logo joshuabvarghese / Loom

gRPC L7 Debugging Proxy

Loom

A gRPC debugging proxy. Point it at your backend, point your client at Loom, and watch every call decoded in a browser tab.

Your gRPC Client  β†’  Loom (:9999)  β†’  Your Backend (:50051)
                          ↓
                    Web Inspector
                  http://localhost:9998

Go Version License: MIT


Why

gRPC traffic is binary. Wireshark can't read it. grpcurl is great for one-off calls but you can't watch a flow. I kept running it over and over trying to understand what was happening between services.

Loom sits transparently between your client and backend. It uses Server Reflection to decode every frame on the fly β€” no .proto files required β€” and streams the results into a browser UI. You see the JSON payloads, the status codes, how long each call took, and a ready-to-copy grpcurl command to replay any of them.

What it does

  • Intercepts all four gRPC stream types β€” unary, server-streaming, client-streaming, bidi
  • Auto-decodes using Server Reflection (no proto…

The requirement

I wanted a browser UI that shows every gRPC call in real time. No page refresh. No polling. Just instant updates.

The challenge: One incoming gRPC request needs to go to three places at once:

  • Browser UI (SSE stream)
  • Console logs
  • Recorder for replay

Why SSE over WebSockets?

WebSockets are great for two-way communication. But I just needed server β†’ browser.

SSE advantages:

  • Simpler protocol (just HTTP)
  • Auto-reconnection built in
  • Native EventSource API in browsers
  • Perfect for "fire and forget" updates

The hub pattern

The core insight: one goroutine that owns all client connections and broadcasts to them.

type Hub struct {
    clients      map[chan]bool  // Active connections
    broadcast    chan []byte    // Incoming messages
    register     chan chan      // New clients
    unregister   chan chan      // Leaving clients
}

func (h *Hub) Run() {
    for {
        select {
        case ch := <-h.register:
            h.clients[ch] = true
        case ch := <-h.unregister:
            delete(h.clients, ch)
            close(ch)
        case msg := <-h.broadcast:
            for ch := range h.clients {
                ch <- msg  // Send to every client
            }
        }
    }
}

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How it works: Any goroutine can push to broadcast. The hub sends it to ALL connected clients. No locks. No race conditions.

Fanning out to multiple sinks

When a gRPC request comes in, I fan it out:

func (p *Proxy) handleRequest(req *Request) {
    // Same data to three places
    go p.sseHub.Broadcast(req)     // Browser UI
    go p.logger.Log(req)           // Console
    go p.recorder.Record(req)      // For replay

    // Forward to backend
    p.backend.Call(req)
}

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Each sink runs in its own goroutine. If one blocks, the others keep going.

The 40KB UI file

The frontend is a single HTML file (40KB) that:

Opens an EventSource connection to /events
Listens for new gRPC calls
Renders them as cards in real time

const source = new EventSource('/events');
source.onmessage = (event) => {
    const call = JSON.parse(event.data);
    addCallCard(call);  // Render to page
};

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No React. No build step. Just vanilla JS that works.

What I learned

Channels as connection managers β€” The hub pattern feels unnatural at first, then becomes obvious
Fan-out is trivial in Go β€” go func() for each sink, done
SSE is underrated β€” For logs, metrics, UIs, it's perfect
One file is fine β€” My 40KB UI never needed splitting
Performance

With 100 concurrent gRPC requests:

Component Latency added
SSE broadcast ~2ms
Logger ~1ms
Recorder ~3ms
Total overhead ~6ms
All three run in parallel thanks to goroutines.

The aha! moment

Coming from Node.js, I would've used callbacks or promises. In Go, I just wrote:

go doSomething()
go doSomethingElse()
go doAnotherThing()
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And it worked. No thinking about event loops. Just concurrency.

Key takeaways

SSE > WebSockets for one-way real-time updates
The hub pattern is Go's answer to connection management
Fan-out with goroutines is trivial β€” don't overthink it
Single-file UIs are fine for internal tools

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