NestJS Enterprise Backend APIs · レッスン

Prometheusによるモニタリング

Prometheusを統合してメトリクスを収集し、ダッシュボードを構築してNestJSアプリケーションのパフォーマンスと健全性を監視します。

「Prometheusによるモニタリング」はCoddyKit上の無料NestJS Enterprise Backend APIsレッスンです。これはレッスン3/3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NestJS Enterprise Backend APIs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。 NestJS Enterprise Backend APIsコースには全3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 Monitor Your App?

Monitoring is crucial for understanding your application's health and performance. It helps you catch issues early, debug problems, and ensure a smooth user experience.

Performance: Is your API fast enough?
Availability: Is your service online and responding?
Errors: Are there unexpected failures?
Resource Usage: How much CPU, memory, or disk space is being used?

Without monitoring, you're flying blind!

Meet Prometheus

Prometheus is an open-source monitoring system designed for reliability and scalability. It collects metrics from your applications and infrastructure, storing them as time-series data.

Think of it as a vigilant observer, constantly gathering data points about your system's behavior over time.

Prometheus Architecture

Prometheus works by scraping (pulling) metrics from configured targets. Key components:

Prometheus Server: The core component that scrapes, stores, and queries metrics.
Exporters: Specialized agents that expose existing metrics from third-party systems (like databases, OS) in a Prometheus-compatible format.
Client Libraries: Integrate directly into application code to expose custom metrics (what we'll use in NestJS).
Grafana: A popular dashboard tool for visualizing Prometheus data.

NestJS & `nestjs-prometheus`

To integrate Prometheus with a NestJS application, we use the nestjs-prometheus library. It simplifies exposing metrics and creating custom ones.

This library acts as a bridge, allowing your NestJS app to generate and expose metrics that the Prometheus server can then scrape.

Setting Up `nestjs-prometheus`

First, install the package:

npm install --save @willsoto/nestjs-prometheus prom-client

Then, import PrometheusModule into your root module (e.g., AppModule) and configure it:

import { Module } from '@nestjs/common';
import { PrometheusModule } from '@willsoto/nestjs-prometheus';
import { AppController } from './app.controller';

@Module({
  imports: [
    PrometheusModule.register({
      path: '/metrics',
      collectDefaultMetrics: true
    })
  ],
  controllers: [AppController],
  providers: [],
})
export class AppModule {}

Exposing Default HTTP Metrics

With collectDefaultMetrics: true, nestjs-prometheus automatically exposes basic Node.js process metrics. To also expose HTTP request metrics, you need to add an interceptor.

Update your main.ts to enable this:

import { NestFactory } from '@nestjs/core';
import { AppModule } from './app.module';
import { PrometheusInterceptor } from '@willsoto/nestjs-prometheus';

async function bootstrap() {
  const app = await NestFactory.create(AppModule);
  app.useGlobalInterceptors(new PrometheusInterceptor());
  await app.listen(3000);
  console.log('App is running on port 3000');
  // Access metrics at http://localhost:3000/metrics
}
bootstrap();

Custom Metrics: Counter

A Counter is a cumulative metric that represents a single monotonically increasing value. It can only go up or be reset to zero on restart. Use it for things like the total number of requests served, errors encountered, or items processed.

Here's how to inject and use a custom counter in a service:

import { Injectable } from '@nestjs/common';
import { InjectMetric } from '@willsoto/nestjs-prometheus';
import { Counter } from 'prom-client';

@Injectable()
export class UserService {
  constructor(
    @InjectMetric('users_created_total') public usersCreatedCounter: Counter,
  ) {}

  createUser(name: string): string {
    // Logic to create a user...
    this.usersCreatedCounter.inc(); // Increment the counter
    return `User ${name} created`;
  }
}

Custom Metrics: Gauge

A Gauge is a metric that represents a single numerical value that can arbitrarily go up and down. Use it for things like current memory usage, number of concurrent requests, or the current queue size.

Let's track active connections with a Gauge:

import { Injectable } from '@nestjs/common';
import { InjectMetric } from '@willsoto/nestjs-prometheus';
import { Gauge } from 'prom-client';

@Injectable()
export class ConnectionService {
  constructor(
    @InjectMetric('active_connections_count') public activeConnectionsGauge: Gauge,
  ) {}

  connectUser(): void {
    // User connects logic...
    this.activeConnectionsGauge.inc(); // Increment active connections
  }

  disconnectUser(): void {
    // User disconnects logic...
    this.activeConnectionsGauge.dec(); // Decrement active connections
  }
}

Other Metric Types

Prometheus also offers other metric types for more specific use cases:

Histogram: Samples observations (e.g., request durations) and counts them in configurable buckets. Useful for understanding distributions and percentiles.
Summary: Similar to Histogram but calculates configurable quantiles over a sliding time window. Good for latency.

For most common scenarios, Counters and Gauges are often sufficient.

Visualizing with Grafana

While Prometheus collects metrics, Grafana is typically used to visualize them. Grafana connects to Prometheus as a data source and allows you to build powerful, customizable dashboards.

You can create graphs, charts, and alerts based on the metrics exposed by your NestJS application, giving you real-time insights into its performance and health.

Quick Check

You've learned about setting up Prometheus monitoring in NestJS.

Recap: Monitoring with Prometheus

In this lesson, you learned the importance of monitoring and how Prometheus helps collect time-series metrics from your NestJS application.

We explored the Prometheus architecture and its components.
You saw how to integrate nestjs-prometheus to expose default and custom metrics.
We distinguished between Counter and Gauge metric types.
Finally, we touched on how Grafana is used for powerful visualization.

Monitoring is a vital practice for maintaining robust and performant applications!

よくある質問

「Prometheusによるモニタリング」レッスンは無料ですか？

はい。「Prometheusによるモニタリング」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）、NestJS Enterprise Backend APIs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。 NestJS Enterprise Backend APIsコースには全3レッスンが含まれています。

「Prometheusによるモニタリング」で何を学びますか？

Prometheusを統合してメトリクスを収集し、ダッシュボードを構築してNestJSアプリケーションのパフォーマンスと健全性を監視します。ブラウザで直接実行するハンズオンコードでNestJS Enterprise Backend APIs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。

NestJS Enterprise Backend APIs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NestJS Enterprise Backend APIs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3/3です。

「Prometheusによるモニタリング」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NestJS Enterprise Backend APIs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NestJS Enterprise Backend APIs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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