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Advanced Spring Boot 4: Event-Driven Architecture (Kafka) · Pelajaran

Integrasi dengan Prometheus & Grafana

Siapkan Prometheus untuk mengambil metrik dari Kafka dan aplikasi Spring Boot, lalu tampilkan secara visual menggunakan dasbor Grafana.

Integrasi dengan Prometheus & Grafana adalah pelajaran Advanced Spring Boot 4: Event-Driven Architecture (Kafka) gratis di CoddyKit. Ini adalah pelajaran 2 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 Advanced Spring Boot 4: Event-Driven Architecture (Kafka), dan progresmu tersinkronisasi di web dan aplikasi CoddyKit. Kursus Advanced Spring Boot 4: Event-Driven Architecture (Kafka) mencakup 4 pelajaran total.

Bagian dari pelajaran ini belum diterjemahkan dan ditampilkan dalam bahasa Inggris.

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!

Pertanyaan yang Sering Diajukan

Apakah pelajaran “Integrasi dengan Prometheus & Grafana” gratis?

Ya — teks lengkap “Integrasi dengan Prometheus & Grafana” gratis dibaca di sini di web. Untuk praktiknya secara interaktif (editor kode bawaan dan tutor AI 24/7) dan buka sisa kursus Advanced Spring Boot 4: Event-Driven Architecture (Kafka), upgrade ke CoddyKit PRO. Kursus Advanced Spring Boot 4: Event-Driven Architecture (Kafka) mencakup 4 pelajaran total.

Apa yang akan aku pelajari di “Integrasi dengan Prometheus & Grafana”?

Siapkan Prometheus untuk mengambil metrik dari Kafka dan aplikasi Spring Boot, lalu tampilkan secara visual menggunakan dasbor Grafana. Kamu berlatih Advanced Spring Boot 4: Event-Driven Architecture (Kafka) 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 Advanced Spring Boot 4: Event-Driven Architecture (Kafka)?

Tidak diperlukan pengalaman sebelumnya. Advanced Spring Boot 4: Event-Driven Architecture (Kafka) 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 2 dari 4.

Berapa lama pelajaran “Integrasi dengan Prometheus & Grafana” 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 Advanced Spring Boot 4: Event-Driven Architecture (Kafka) ini?

Ya. Setiap pelajaran Advanced Spring Boot 4: Event-Driven Architecture (Kafka) menyertakan editor kode bawaan, jadi kamu menulis dan menjalankan kode nyata langsung di browser dan mendapatkan umpan balik AI instan — tidak diperlukan penyiapan lokal.

Semua pelajaran dalam kursus ini

  1. Metrik Kafka (JMX) dan Pemeriksaan Kesehatan
  2. Integrasi dengan Prometheus & Grafana
  3. Pelacakan Terdistribusi dengan Sleuth/Zipkin
  4. Memantau Kesenjangan Konsumen dan Menetapkan Peringatan
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