Edge Computing with Cloudflare Workers & Deno · Pelajaran

Arsitektur Berbasis Peristiwa

Bangun sistem berbasis peristiwa menggunakan Workers dan Deno yang merespons data waktu nyata serta tindakan pengguna.

Arsitektur Berbasis Peristiwa adalah pelajaran Edge Computing with Cloudflare Workers & Deno gratis di CoddyKit. Ini adalah pelajaran 2 dari 4. Kamu bisa membaca pelajaran lengkapnya di bawah secara gratis — lalu praktikkan langsung di browser dengan editor kode bawaan dan tutor AI 24/7. Ini adalah bagian dari jalur belajar Edge Computing with Cloudflare Workers & Deno, dan progresmu tersinkronisasi di web dan aplikasi CoddyKit. Kursus Edge Computing with Cloudflare Workers & Deno mencakup 4 pelajaran total.

Bagian dari pelajaran ini belum diterjemahkan dan ditampilkan dalam bahasa Inggris.

What is Event-Driven Architecture?

Welcome! Today we'll explore Event-Driven Architecture (EDA). It's a design pattern where services communicate by producing and consuming events, rather than direct calls.

Think of it like a news channel: producers (reporters) publish news (events), and consumers (viewers) react to the news they're interested in.

Event: A significant change in state, like 'user registered'.
Producer: The system that generates and sends an event.
Consumer: The system that listens for and reacts to an event.

Why Event-Driven at the Edge?

EDA shines brightly at the edge, offering significant benefits for performance and scalability:

Decoupling: Services operate independently, reducing dependencies.
Scalability: Individual components can scale up or down based on event load.
Real-time Responsiveness: React to user actions or data changes instantly.
Resilience: If one consumer fails, others can still process events.

This makes your edge applications more robust and flexible.

Cloudflare Workers as Event Reactors

Cloudflare Workers are perfect for event-driven systems because they are inherently reactive. They spring into action when triggered by an event!

Common events that trigger Workers include:

Incoming HTTP requests (e.g., an API call)
Messages from a queue (e.g., Cloudflare Queues)
Scheduled cron jobs
Other Cloudflare service bindings

They act as lightweight, distributed consumers.

Code: Worker Reacting to HTTP Event

Here's a basic Worker that processes an incoming HTTP request as an 'event'. It reads a custom header to identify the event type and logs it.

Try changing the X-Event-Type header when you test it!

export default {
  async fetch(request, env, ctx) {
    const eventType = request.headers.get('X-Event-Type') || 'unknown_event';
    const eventData = await request.json().catch(() => ({}));

    console.log(`Worker received event: ${eventType}`);
    console.log(`Event data: ${JSON.stringify(eventData)}`);

    // In a real app, you'd process eventData here
    return new Response(`Event '${eventType}' processed!`, { status: 200 });
  },
};

Deno as an Event Originator

Just as Workers consume events, Deno applications can act as event producers. A Deno backend service or a CLI tool might generate events.

For instance, a Deno script could:

Detect a file change and send an event.
Process data and publish a 'data_processed' event.
Handle a user action and send a 'user_activity' event to your edge Worker.

Code: Deno Sends Event to Worker

This Deno script acts as a producer, sending a 'user_registered' event to our Cloudflare Worker via an HTTP POST request. The Worker then acts as the consumer.

Remember to replace 'YOUR_WORKER_URL' with your deployed Worker's URL!

// main.ts
async function sendUserRegisteredEvent() {
  const workerUrl = "https://your-worker-name.your-account.workers.dev"; // Replace this!

  const response = await fetch(workerUrl, {
    method: "POST",
    headers: {
      "Content-Type": "application/json",
      "X-Event-Type": "user_registered"
    },
    body: JSON.stringify({ userId: "user_abc", timestamp: Date.now() })
  });

  if (response.ok) {
    console.log("User registered event sent successfully!");
  } else {
    console.error("Failed to send event:", response.status, await response.text());
  }
}

sendUserRegisteredEvent();

Cloudflare Queues for Robust Events

For truly robust event-driven systems, especially at the edge, Cloudflare Queues are invaluable. They act as an event bus, providing a reliable buffer between producers and consumers.

Asynchronous: Producers don't wait for consumers to finish.
Guaranteed Delivery: Messages are durably stored until processed.
Load Leveling: Handles bursts of events without overwhelming consumers.
Decoupling: Producers and consumers don't need to know about each other directly.

Code: Worker Publishes to a Queue

Here, a Worker receives an HTTP request (an event) and then publishes a message to a Cloudflare Queue. This offloads heavy processing to a separate consumer.

To make this runnable, you'd need to bind a Queue in your wrangler.toml file (e.g., [[queues.producers]] binding = "MY_QUEUE" queue_name = "my-event-queue").

export default {
  async fetch(request, env, ctx) {
    const eventData = await request.json().catch(() => ({}));
    const eventType = eventData.type || 'api_trigger_event';

    // Publish event to a Cloudflare Queue
    // 'env.MY_QUEUE' refers to the queue binding configured
    await env.MY_QUEUE.send({
      eventType: eventType,
      payload: eventData
    });

    return new Response(`Event '${eventType}' queued successfully!`, { status: 202 });
  },
};

Code: Worker Consuming Queue Messages

This Worker is configured to consume messages directly from a Cloudflare Queue. It processes each message in a batch, extracting the event type and payload.

This Worker would have a queue handler instead of (or in addition to) a fetch handler. You'd configure this in your wrangler.toml (e.g., [[queues.consumers]] queue = "my-event-queue").

export default {
  async queue(batch, env, ctx) {
    for (const message of batch.messages) {
      const { eventType, payload } = message.body;
      console.log(`Processing event from queue: ${eventType}`);
      console.log(`Payload: ${JSON.stringify(payload)}`);

      // Implement your actual event processing logic here
      // e.g., update a database, send a notification, call another API
    }
  },
};

Quick Check: Event-Driven Concepts

Which of the following are key benefits of using an Event-Driven Architecture at the edge?

Recap: Event-Driven Edge Apps

Great job! You've learned about Event-Driven Architectures and how they supercharge applications at the edge.

EDA uses events, producers, and consumers for decoupled communication.
Cloudflare Workers are ideal for consuming and producing edge events.
Deno applications can act as powerful event producers.
Cloudflare Queues provide robust, asynchronous event delivery for resilience and scale.

This pattern is key for building highly responsive, scalable, and fault-tolerant edge applications. Keep exploring how events can transform your architecture!

Pertanyaan yang Sering Diajukan

Apakah pelajaran “Arsitektur Berbasis Peristiwa” gratis?

Ya — teks lengkap “Arsitektur Berbasis Peristiwa” gratis dibaca di sini di web. Untuk praktiknya secara interaktif (editor kode bawaan dan tutor AI 24/7) dan buka sisa kursus Edge Computing with Cloudflare Workers & Deno, upgrade ke CoddyKit PRO. Kursus Edge Computing with Cloudflare Workers & Deno mencakup 4 pelajaran total.

Apa yang akan aku pelajari di “Arsitektur Berbasis Peristiwa”?

Bangun sistem berbasis peristiwa menggunakan Workers dan Deno yang merespons data waktu nyata serta tindakan pengguna. Kamu berlatih Edge Computing with Cloudflare Workers & Deno dengan kode praktik yang langsung kamu jalankan di browser, dan tutor AI 24/7 menjawab pertanyaanmu saat kamu mengerjakan pelajaran ini.

Apakah aku perlu pengalaman untuk memulai Edge Computing with Cloudflare Workers & Deno?

Tidak diperlukan pengalaman sebelumnya. Edge Computing with Cloudflare Workers & Deno di CoddyKit dirancang untuk pemula hingga pelajar tingkat lanjut, jadi kamu bisa memulai di sini atau dari awal dan belajar sesuai kecepatan kamu sendiri. Ini adalah pelajaran 2 dari 4.

Berapa lama pelajaran “Arsitektur Berbasis Peristiwa” memakan waktu?

Sebagian besar pelajaran CoddyKit memakan waktu sekitar 5–10 menit. Setiap pelajaran ringkas dan interaktif, jadi kamu membuat kemajuan stabil dan melanjutkan dari tempat kamu tinggalkan di web dan aplikasi.

Bisakah aku menulis dan menjalankan kode dalam pelajaran Edge Computing with Cloudflare Workers & Deno ini?

Ya. Setiap pelajaran Edge Computing with Cloudflare Workers & Deno menyertakan editor kode bawaan, jadi kamu menulis dan menjalankan kode nyata langsung di browser dan mendapatkan umpan balik AI instan — tidak diperlukan penyiapan lokal.

Semua pelajaran dalam kursus ini

Layanan Mikro di Tepi Jaringan
Arsitektur Berbasis Peristiwa
Geolokasi & Pelokalan
Durable Objects dan Koordinasi Berkeadaan

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