Node.js Backend Development Bootcamp · レッスン

相関IDを使った構造化ロギング

機械で解析可能なJSONログを出力し、非同期コンテキストを通じて相関IDを引き継ぎ、リクエストを追跡します。

「相関IDを使った構造化ロギング」はCoddyKit上の無料Node.js Backend Development Bootcampレッスンです。これはレッスン1/4です。下記で完全なレッスンを無料で読むことができます。その後、ブラウザ内の組み込みコードエディタと24時間対応のAIチューターでハンズオン演習できます。これはNode.js Backend Development Bootcamp学習パスの一部であり、ウェブとCoddyKitアプリ全体で進捗が同期されます。 Node.js Backend Development Bootcampコースには全4レッスンが含まれています。

このレッスンの一部はまだ翻訳されておらず、英語で表示されています。

Why Structured Logging

In production, logs are read by machines before humans. A line like console.log('User ' + id + ' failed login') is a free-form string: to find it later you must write brittle regex and you cannot aggregate or filter reliably.

Structured logging emits each log as a JSON object with consistent fields. Log aggregators (Loki, Elasticsearch, Datadog, CloudWatch) index those fields so you can query level="error" AND userId=42 instantly.

Free-form: easy to write, painful to query.
Structured: one JSON object per line (NDJSON), trivially parseable.

A Minimal JSON Logger

The core idea is small: build a plain object, stamp it with a level and timestamp, and write one JSON string per line to stdout. The runtime or container collects stdout and ships it to your aggregator.

Each log is a single line of valid JSON. This format is called NDJSON (newline-delimited JSON) and every modern log backend understands it.

function log(level, message, fields = {}) {
  const entry = {
    level,
    time: new Date().toISOString(),
    message,
    ...fields,
  };
  process.stdout.write(JSON.stringify(entry) + '\n');
}

log('info', 'server started', { port: 3000 });
log('error', 'login failed', { userId: 42, reason: 'bad_password' });

Use a Real Logger: pino

Hand-rolling works for learning, but production apps use a battle-tested logger. pino is the de-facto choice for Node.js: it is extremely fast because it serializes JSON in a worker-friendly way and writes asynchronously.

logger.info(obj, msg) — the first arg is the object of fields, the second is the message string.
Levels: trace, debug, info, warn, error, fatal.
In production you pipe stdout to pino-pretty only in dev; raw JSON goes to prod.

const pino = require('pino');
const logger = pino({ level: 'info' });

logger.info({ port: 3000 }, 'server started');
logger.error({ userId: 42, reason: 'bad_password' }, 'login failed');

// Child loggers bind fields onto every subsequent log:
const reqLog = logger.child({ requestId: 'abc-123' });
reqLog.info('handling request');

The Problem: Tracing One Request

Under load, hundreds of requests interleave their logs. When user 42 reports an error, you need to see every log line that belongs to their request — across middleware, services, and database calls.

The solution is a correlation ID (also called request ID or trace ID): a unique identifier generated once per request and attached to every log emitted while handling that request.

Query correlationId="7f3a..." and the aggregator reconstructs the whole request timeline.
If the ID arrives in an incoming header, you can correlate logs across services.

Generating and Accepting the ID

At the edge of your system, read an incoming correlation header if a caller (gateway, upstream service) already set one; otherwise generate a fresh UUID. Always echo it back in the response so clients and proxies can record it too.

Standard header names are x-request-id or x-correlation-id. Reusing an inbound ID is what makes tracing work across service boundaries.

const { randomUUID } = require('crypto');

function correlationMiddleware(req, res, next) {
  const incoming = req.headers['x-correlation-id'];
  const correlationId = incoming || randomUUID();
  req.correlationId = correlationId;
  res.setHeader('x-correlation-id', correlationId);
  next();
}

module.exports = { correlationMiddleware };

The Naive Approach and Its Pain

The obvious move is to pass req.correlationId as an argument into every function and every log call. This works but does not scale: a deep call stack (controller → service → repository → helper) forces you to thread the ID through functions that otherwise have no reason to know about it.

This is prop drilling for the backend. You want the ID available implicitly to any code running during the request — without changing every function signature.

AsyncLocalStorage to the Rescue

Node.js ships AsyncLocalStorage (in the async_hooks module). It creates a store that stays bound to the current asynchronous execution context — surviving across await, callbacks, timers, and promises — without being shared between concurrent requests.

Think of it as request-scoped thread-local storage. You call als.run(store, callback) once per request; anywhere inside that callback (no matter how deep or how many awaits later) als.getStore() returns the same store.

const { AsyncLocalStorage } = require('async_hooks');
const als = new AsyncLocalStorage();

async function deep() {
  await new Promise((r) => setTimeout(r, 10));
  // Same store, even after awaits and timers:
  return als.getStore().correlationId;
}

async function main() {
  await als.run({ correlationId: 'req-1' }, async () => {
    console.log('inside:', await deep());
  });
  console.log('outside:', als.getStore());
}

main();

Wiring AsyncLocalStorage into the Request

Replace the naive middleware: instead of attaching the ID to req, run the rest of the request inside als.run() with the ID in the store. Now every line of code executed for this request — controllers, services, DB callbacks — can reach the ID via getStore().

Crucially, you must call next() inside the run callback so the downstream handlers inherit the context.

const { AsyncLocalStorage } = require('async_hooks');
const { randomUUID } = require('crypto');

const als = new AsyncLocalStorage();

function context() {
  return als.getStore() || {};
}

function correlationMiddleware(req, res, next) {
  const correlationId = req.headers['x-correlation-id'] || randomUUID();
  res.setHeader('x-correlation-id', correlationId);
  als.run({ correlationId }, () => next());
}

module.exports = { als, context, correlationMiddleware };

Auto-Injecting the ID into Every Log

The payoff: wrap your logger so it reads the correlation ID from AsyncLocalStorage automatically. Application code calls log.info('saved order') with no ID argument, yet every emitted line carries the right correlationId.

With pino you express this declaratively using the mixin option, which merges extra fields into every log record at write time.

const pino = require('pino');
const { als } = require('./context');

const logger = pino({
  level: 'info',
  mixin() {
    const store = als.getStore();
    return store ? { correlationId: store.correlationId } : {};
  },
});

// Anywhere deep in the request, no ID passed explicitly:
function saveOrder(order) {
  logger.info({ orderId: order.id }, 'order saved');
}

module.exports = { logger, saveOrder };

Propagating the ID to Downstream Calls

Correlation only spans services if you forward the ID on outbound requests. When your service calls another HTTP API, read the ID from context and set it as a header. The downstream service's middleware will reuse it, so both services' logs share one ID.

The same principle applies to message queues (put the ID in message metadata) and background jobs (store it on the job payload).

const { context } = require('./context');

async function callInventoryService(sku) {
  const { correlationId } = context();
  const res = await fetch('https://inventory.internal/check', {
    method: 'POST',
    headers: {
      'content-type': 'application/json',
      'x-correlation-id': correlationId,
    },
    body: JSON.stringify({ sku }),
  });
  return res.json();
}

module.exports = { callInventoryService };

Production Hygiene

A few rules keep your structured logs clean and safe:

Never log secrets or PII — passwords, tokens, full card numbers. Configure pino redact paths (e.g. ['req.headers.authorization', '*.password']).
Log at the right level — info for business events, warn for recoverable issues, error with the serialized error object for failures.
Keep field names stable — correlationId always means the same thing; dashboards and alerts depend on it.
One JSON object per line — do not pretty-print in production; it breaks NDJSON parsing.

const pino = require('pino');

const logger = pino({
  level: process.env.LOG_LEVEL || 'info',
  redact: ['req.headers.authorization', 'password', '*.password', 'creditCard'],
});

logger.info({ user: { id: 7, password: 'hunter2' } }, 'login');
// -> password is replaced with [Redacted] in the output

Quick Check

You need the correlation ID available to every function in a deep call stack during a request, without passing it as an argument and without leaking it between concurrent requests. What is the correct mechanism in Node.js?

Recap

You learned how to make logs both machine-parseable and traceable:

Structured logging emits one JSON object per line (NDJSON) so aggregators can index and query fields.
pino is the standard fast Node.js logger; the field object comes first, the message second.
A correlation ID is generated or reused from an inbound header once per request and echoed in the response.
AsyncLocalStorage threads that ID through the whole async call stack without changing function signatures, and isolates concurrent requests.
Pino's mixin auto-injects the ID into every log; forwarding it as an outbound header extends tracing across services.
Practice good hygiene: redact secrets, use correct levels, keep field names stable, never pretty-print in production.

よくある質問

「相関IDを使った構造化ロギング」レッスンは無料ですか？

はい。「相関IDを使った構造化ロギング」の完全なテキストはこのウェブで無料で読めます。インタラクティブに演習し（組み込みコードエディタと24時間対応のAIチューター）、Node.js Backend Development Bootcampコースの残りをアンロックするには、CoddyKit PROにアップグレードしてください。 Node.js Backend Development Bootcampコースには全4レッスンが含まれています。

「相関IDを使った構造化ロギング」で何を学びますか？

機械で解析可能なJSONログを出力し、非同期コンテキストを通じて相関IDを引き継ぎ、リクエストを追跡します。ブラウザで直接実行するハンズオンコードでNode.js Backend Development Bootcampを演習し、24時間対応のAIチューターがレッスンを進める中での質問に答えます。

Node.js Backend Development Bootcampを始めるのに経験は必要ですか？

事前経験は必要ありません。CoddyKitのNode.js Backend Development Bootcampは初級者から上級者向けに構成されているため、ここから始めるか最初から始めて、自分のペースで進むことができます。これはレッスン1/4です。

「相関IDを使った構造化ロギング」レッスンにはどのくらい時間がかかりますか？

ほとんどのCoddyKitレッスンは約5～10分かかります。各レッスンはコンパクトでインタラクティブなので、着実に進歩し、ウェブとアプリ全体で正確に前回の場所から再開できます。

このNode.js Backend Development Bootcampレッスンでコードを書いて実行できますか？

はい。すべてのNode.js Backend Development Bootcampレッスンに組み込みコードエディタが含まれているため、ブラウザでリアルコードを書いて実行し、即座のAIフィードバックを取得できます。ローカル設定は不要です。

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