Back to Code | Ep 13: Event-Driven Architecture — Kafka and the Async World

The 15-week technical battle of LogiFlow — a company waking up from the illusion created by artificial intelligence and returning to real engineering.

The Story

When the "Invoice" service crashed, the "Routing" service also went down — because AI had connected them with synchronous HTTP (REST). Cascade Failure.

It was 2 AM when the pager went off. The invoice service had run out of memory — a memory leak in a PDF generation library. Within seconds, the routing service started timing out. Then the tracking service. Then the customer portal. One service's failure had cascaded through the entire system like dominoes.

"Why does the routing service care if invoicing is down?" Defne asked, already knowing the answer.
"Because AI made routing call invoicing synchronously after every route calculation," Emre admitted.

Technical Autopsy: Event-Driven Architecture

// Routing service (Producer)
await kafka.send({
  topic: 'routing.events',
  messages: [{
    key: truckId,
    value: JSON.stringify({
      type: 'RouteCalculated',
      truckId,
      eta,
      timestamp: Date.now()
    })
  }]
});

// Invoice service (Consumer) — Runs independently
consumer.run({
  eachMessage: async ({ message }) => {
    const event = JSON.parse(message.value);
    if (event.type === 'RouteCalculated') {
      await generateInvoice(event);
    }
  }
});

Microservices should talk through Domain Events, not HTTP.

When the invoice service goes down now, the routing service doesn't notice. The events queue up in Kafka. When invoicing recovers, it processes the backlog. No cascade. No domino effect. No 2 AM pages.

Sync vs Async

Synchronous (HTTP)	Asynchronous (Events)
Caller waits for response	Fire and forget
Failure cascades	Failure is isolated
Tight coupling	Loose coupling
Easy to reason about	Requires event schema design
Simple for 2 services	Essential for 10+ services