Edge Computing with Cloudflare Workers & Deno · 강의

모니터링 및 로깅

엣지 애플리케이션의 성능을 추적하고 문제를 디버깅할 수 있도록 모니터링과 로깅을 설정합니다.

모니터링 및 로깅은(는) CoddyKit의 무료 Edge Computing with Cloudflare Workers & Deno 강의입니다. 이것은 4개 중 3번째 강의입니다. 아래에서 전체 강의를 무료로 읽을 수 있으며, 내장 코드 에디터와 24/7 AI 튜터와 함께 브라우저에서 직접 실습할 수 있습니다. 이 강의는 Edge Computing with Cloudflare Workers & Deno 학습 경로의 일부이며, 진행 상황이 웹과 CoddyKit 앱에 동기화됩니다. Edge Computing with Cloudflare Workers & Deno 강의에는 총 4개의 강의가 포함되어 있습니다.

이 강의의 일부는 아직 번역되지 않았으며 영어로 표시됩니다.

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!

자주 묻는 질문

“모니터링 및 로깅” 강의는 무료인가요?

네 — “모니터링 및 로깅” 전체 내용을 이 웹사이트에서 무료로 읽을 수 있습니다. 인터랙티브하게 실습하려면(내장 코드 에디터와 24/7 AI 튜터), CoddyKit PRO로 업그레이드하면 Edge Computing with Cloudflare Workers & Deno 강의 전체를 잠금 해제할 수 있습니다. Edge Computing with Cloudflare Workers & Deno 강의에는 총 4개의 강의가 포함되어 있습니다.

“모니터링 및 로깅”에서 뭘 배우나요?

엣지 애플리케이션의 성능을 추적하고 문제를 디버깅할 수 있도록 모니터링과 로깅을 설정합니다. 브라우저에서 직접 실행하는 실습 코드로 Edge Computing with Cloudflare Workers & Deno을(를) 배우며, 24/7 AI 튜터가 강의를 진행하면서 질문에 답변해줍니다.

Edge Computing with Cloudflare Workers & Deno을(를) 시작하는 데 경험이 필요한가요?

사전 경험은 필요하지 않습니다. CoddyKit의 Edge Computing with Cloudflare Workers & Deno은(는) 초급자부터 고급 학습자까지를 위해 구성되어 있으므로, 여기서 시작하거나 처음부터 시작할 수 있으며 자신의 속도대로 진행할 수 있습니다. 이것은 4개 중 3번째 강의입니다.

“모니터링 및 로깅” 강의는 얼마나 걸리나요?

대부분의 CoddyKit 강의는 약 5~10분이 소요됩니다. 각 강의는 간결하고 인터랙티브하여 꾸준한 진행이 가능하며, 웹과 앱에서 중단한 부분부터 바로 시작할 수 있습니다.

이 Edge Computing with Cloudflare Workers & Deno 강의에서 코드를 작성하고 실행할 수 있나요?

네. 모든 Edge Computing with Cloudflare Workers & Deno 강의에는 내장 코드 에디터가 포함되어 있으므로, 브라우저에서 바로 실제 코드를 작성하고 실행한 후 즉시 AI 피드백을 받을 수 있습니다 — 로컬 설정이 필요 없습니다.

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