Advanced Spring Boot 4: Event-Driven Architecture (Kafka) · レッスン

PrometheusとGrafanaの統合

KafkaとSpring BootアプリケーションからPrometheusでメトリクスを収集し、Grafanaのダッシュボードで可視化する方法を学習します。

「PrometheusとGrafanaの統合」はCoddyKit上の無料Advanced Spring Boot 4: Event-Driven Architecture (Kafka)レッスンです。これはレッスン2/4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Advanced Spring Boot 4: Event-Driven Architecture (Kafka)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。 Advanced Spring Boot 4: Event-Driven Architecture (Kafka)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 Monitor with P&G?

In modern systems, understanding what your applications and infrastructure are doing is critical. This is where monitoring comes in!

We'll explore how Prometheus and Grafana form a powerful duo for observing your Spring Boot Kafka applications and the Kafka cluster itself.

Introducing Prometheus

Prometheus is an open-source monitoring system that collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts.

It uses a pull model: Prometheus scrapes (pulls) metrics from your services.
It stores data as time-series data, making it excellent for tracking changes over time.

Spring Boot & Micrometer

Spring Boot applications can expose metrics using Actuator, Spring's production-ready features. Micrometer is an instrumentation library that Actuator uses to provide a vendor-neutral metrics facade.

This allows you to export metrics to various monitoring systems, including Prometheus, with minimal code changes.

Enabling Prometheus Endpoint

To make your Spring Boot app's metrics available for Prometheus, you need to add dependencies and configure Actuator.

First, add spring-boot-starter-actuator and micrometer-registry-prometheus to your pom.xml.

Then, enable the Prometheus endpoint in application.properties:

management.endpoints.web.exposure.include=health,info,prometheus

This exposes metrics at /actuator/prometheus.

management.endpoints.web.exposure.include=health,info,prometheus

Your First Metric

This minimal Spring Boot application demonstrates how to expose a custom counter. When you hit the /hello endpoint, the app.hello.requests counter increments, which Prometheus can then scrape.

import io.micrometer.core.instrument.Counter;
import io.micrometer.core.instrument.Metrics;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RestController;

@SpringBootApplication
@RestController
public class MetricsApp {

  private final Counter helloCounter =
      Metrics.counter("app.hello.requests");

  public static void main(String[] args) {
    SpringApplication.run(MetricsApp.class, args);
  }

  @GetMapping("/hello")
  public String hello() {
    helloCounter.increment();
    return "Hello CoddyKit!";
  }
}

Kafka Metrics with Exporter

Kafka brokers don't natively expose metrics in a Prometheus-friendly format. We use a separate component called Kafka Exporter.

Kafka Exporter is a lightweight service that scrapes JMX metrics from Kafka brokers and re-exposes them in a format that Prometheus can easily consume.

Prometheus Scrape Config

Prometheus needs to know where to find your metrics. You configure scrape targets in its prometheus.yml file. Here's an example:

scrape_configs:
  - job_name: 'spring-boot-app'
    metrics_path: '/actuator/prometheus'
    static_configs:
      - targets: ['localhost:8080']

  - job_name: 'kafka-exporter'
    static_configs:
      - targets: ['localhost:9308'] # Kafka Exporter port

Introducing Grafana

Grafana is an open-source platform for monitoring and observability. It allows you to query, visualize, alert on, and understand your metrics no matter where they are stored.

Think of it as the display panel for all the data Prometheus collects. It uses dashboards with various panels to present metrics in an easy-to-understand way.

Grafana Data Sources

Before visualizing, Grafana needs to connect to a data source. Here, Prometheus will be our data source.

In Grafana's UI, navigate to "Connections" -> "Data sources" -> "Add new data source". Select "Prometheus" and configure its URL (e.g., http://localhost:9090, Prometheus' default port).

Creating a Dashboard

With Prometheus connected, you can start building dashboards.

Create a new dashboard and add a panel.
Select Prometheus as the data source.
Write a PromQL query (Prometheus Query Language) to select your metric, e.g., app_hello_requests_total for our Spring Boot app.
Choose a visualization type like "Graph" or "Stat".

This brings your metrics to life!

Prometheus & Grafana Check

You've learned how Prometheus scrapes metrics and Grafana visualizes them. What is the primary role of Kafka Exporter in this monitoring setup?

Recap: P&G Power

Great job! You've learned how to integrate Prometheus and Grafana into your monitoring strategy for Spring Boot Kafka applications and Kafka itself.

Prometheus scrapes metrics from endpoints.
Micrometer/Actuator expose Spring Boot metrics.
Kafka Exporter makes Kafka broker metrics available.
Grafana visualizes these collected metrics.

This powerful combination provides deep insights into your system's health and performance!

よくある質問

「PrometheusとGrafanaの統合」レッスンは無料ですか？

はい。「PrometheusとGrafanaの統合」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）、Advanced Spring Boot 4: Event-Driven Architecture (Kafka)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。 Advanced Spring Boot 4: Event-Driven Architecture (Kafka)コースには全4レッスンが含まれています。

「PrometheusとGrafanaの統合」で何を学びますか？

KafkaとSpring BootアプリケーションからPrometheusでメトリクスを収集し、Grafanaのダッシュボードで可視化する方法を学習します。ブラウザで直接実行するハンズオンコードでAdvanced Spring Boot 4: Event-Driven Architecture (Kafka)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。

Advanced Spring Boot 4: Event-Driven Architecture (Kafka)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Advanced Spring Boot 4: Event-Driven Architecture (Kafka)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2/4です。

「PrometheusとGrafanaの統合」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Advanced Spring Boot 4: Event-Driven Architecture (Kafka)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Advanced Spring Boot 4: Event-Driven Architecture (Kafka)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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