This is Part 3 of my series building Loom.
π Missed Part 2? Read it here
Today: Building the real-time browser UI with SSE, goroutines, and channels. One request β three outputs simultaneously.
joshuabvarghese
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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)
β
Web Inspector
http://localhost:9998
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 protoβ¦
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
EventSourceAPI 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
}
}
}
}
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)
}
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
};
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()
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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