Edge Computing with Cloudflare Workers & Deno · Pelajaran

Pemantauan & Pencatatan

Siapkan pemantauan dan pencatatan untuk aplikasi tepi Anda guna melacak kinerja dan menelusuri masalah.

Pemantauan & Pencatatan adalah pelajaran Edge Computing with Cloudflare Workers & Deno gratis di CoddyKit. Ini adalah pelajaran 3 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.

Why Monitor & Log Edge Apps?

When your applications run at the edge, they're distributed globally. This makes it challenging to know what's happening without good visibility.

Monitoring helps you track performance metrics like request times and error rates across your entire system. Logging gives you detailed records of individual events, like requests or errors, which are crucial for debugging.

Basic Logging: console.log

The simplest way to log information in a Cloudflare Worker is by using console.log(). This works much like logging in a browser or Node.js environment.

Messages sent to console.log() are captured by Cloudflare and can be viewed in your Worker's dashboard or exported using Logpush.

Basic Logging in Action

Try running this Worker. It logs the incoming request's URL to the console. When you test it, check your Worker's logs in the Cloudflare dashboard to see the output.

export default {
  async fetch(request, env, ctx) {
    console.log("Request received for:", request.url);
    return new Response("Hello from basic logging!");
  }
};

The Need for Structured Logs

While console.log() is easy, plain text logs can be hard to parse and analyze at scale. Imagine sifting through thousands of lines of text!

Structured logging involves outputting logs in a consistent, machine-readable format, like JSON. This makes it much easier for monitoring tools to process and query your logs.

Cloudflare Logpush Overview

Cloudflare's Logpush service allows you to export your Worker logs to various destinations, such as cloud storage (AWS S3, Google Cloud Storage) or analytics platforms.

This is essential for long-term storage, advanced querying, and integrating with your existing monitoring infrastructure.

What to Include in Logs?

Good structured logs contain useful context. Consider including:

Timestamp: When the event occurred.
Level: (e.g., INFO, WARN, ERROR) for severity.
Request ID: To trace a single request through its lifecycle.
URL & Method: Details of the incoming request.
Latency: How long the operation took.
Error Details: Stack traces, error messages.

Structured Logging Example

This Worker logs request details as a JSON string, including a simple latency measurement. This format is easily parsable by log analysis tools.

export default {
  async fetch(request, env, ctx) {
    const start = Date.now();
    const response = new Response("Hello from structured logs!");
    const latency = Date.now() - start;

    const logEntry = {
      timestamp: new Date().toISOString(),
      level: "INFO",
      url: request.url,
      method: request.method,
      latencyMs: latency,
      requestId: crypto.randomUUID()
    };
    console.log(JSON.stringify(logEntry));

    return response;
  }
};

Introduction to Edge Metrics

While logs tell you 'what happened,' metrics tell you 'how much' or 'how often.' Metrics are numerical measurements captured over time, used to track the health and performance of your application.

Common metrics include requests per second, error rates, CPU usage, and memory consumption. They are aggregated and visualized in dashboards.

Custom Metrics in Workers

Cloudflare Workers provide built-in analytics, but you can also add custom metrics. One simple way is to use response headers to expose performance data that can be scraped or analyzed.

Here, we add a X-Worker-Latency header. More advanced metrics might use external services or Cloudflare's ctx.waitUntil to send data.

export default {
  async fetch(request, env, ctx) {
    const start = Date.now();
    const response = new Response("Hello from custom metrics!");
    const latency = Date.now() - start;

    // Add a custom header as a simple metric
    response.headers.set("X-Worker-Latency", latency.toString());

    console.log(`Request processed in ${latency}ms`);
    return response;
  }
};

Monitoring Tools & Dashboards

Once you have logs and metrics, you need tools to make sense of them. Cloudflare provides basic analytics, but for advanced analysis, you'll integrate with:

Log Management Systems: Splunk, ELK Stack, DataDog, Sumo Logic.
Monitoring Platforms: Grafana, Prometheus, New Relic, Dynatrace.

These tools help you visualize trends, set up alerts, and quickly identify issues.

Quick Check on Logging

You are debugging an intermittent error in your Cloudflare Worker. You've been using console.log("Error occurred!") to catch issues.

Which change would MOST improve your ability to diagnose the problem quickly?

Recap: Monitoring & Logging

Great job! In this lesson, you learned about the critical role of monitoring and logging for edge applications.

console.log() is your basic logging tool.
Structured logging (e.g., JSON) provides machine-readable, actionable insights.
Cloudflare Logpush helps export logs for advanced analysis.
Metrics track performance trends, often exposed via custom headers or dedicated services.
Using external monitoring tools can greatly enhance visibility and debugging capabilities.

Keeping an eye on your edge apps ensures they perform optimally!

Pertanyaan yang Sering Diajukan

Apakah pelajaran “Pemantauan & Pencatatan” gratis?

Ya — teks lengkap “Pemantauan & Pencatatan” 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 “Pemantauan & Pencatatan”?

Siapkan pemantauan dan pencatatan untuk aplikasi tepi Anda guna melacak kinerja dan menelusuri masalah. 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 3 dari 4.

Berapa lama pelajaran “Pemantauan & Pencatatan” 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.

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