Pelacakan Terdistribusi dengan Zipkin
Integrasikan Zipkin untuk pelacakan terdistribusi menyeluruh di seluruh layanan mikro guna men-debug interaksi kompleks.
Pelacakan Terdistribusi dengan Zipkin adalah pelajaran Spring Boot 4 Microservices & REST APIs gratis di CoddyKit. Ini adalah pelajaran 3 dari 3. 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 Spring Boot 4 Microservices & REST APIs, dan progresmu tersinkronisasi di web dan aplikasi CoddyKit. Kursus Spring Boot 4 Microservices & REST APIs mencakup 3 pelajaran total.
Bagian dari pelajaran ini belum diterjemahkan dan ditampilkan dalam bahasa Inggris.
The Microservice Debugging Maze
In a microservices architecture, a single user request might travel through many different services. When something goes wrong, it's like finding a needle in a haystack!
Traditional logging only shows what happened within one service. We need a way to see the entire journey.
What is Distributed Tracing?
Distributed tracing is a technique to monitor and observe requests as they flow through different components of a distributed system.
- It helps you understand how services interact.
- It pinpoints performance bottlenecks.
- It makes debugging across service boundaries much easier.
Introducing Zipkin
Zipkin is an open-source distributed tracing system.
It helps you gather timing data needed to troubleshoot latency problems in microservice architectures. It manages both the collection and lookup of this data.
Core Concepts: Trace & Span
Two fundamental concepts in distributed tracing are Traces and Spans:
- A Trace represents a single request or workflow as it flows through your entire system.
- A Span is a single operation within a trace. It has a name, a unique ID, and a parent ID (unless it's the root span).
Think of a Trace as a story, and Spans as the individual chapters.
How Zipkin Works
Zipkin works by collecting data from your instrumented services.
Here's the basic flow:
- Your services send tracing data (spans) to the Zipkin Collector.
- The Collector stores this data (e.g., in memory, MySQL, Elasticsearch).
- You use the Zipkin UI to visualize and analyze the traces.
Spring Cloud Sleuth Magic
For Spring Boot applications, Spring Cloud Sleuth makes integration with Zipkin incredibly easy.
Sleuth automatically adds tracing information to your logs and HTTP headers, and sends it to Zipkin without much manual coding from you.
Setting Up Zipkin Locally
The easiest way to run a Zipkin server locally is using Docker. If you have Docker installed, just run this command in your terminal:
docker run -p 9411:9411 openzipkin/zipkin
Once running, you can access the Zipkin UI at http://localhost:9411.
Simple Service Instrumentation
To enable tracing, add Sleuth and Zipkin dependencies (spring-cloud-starter-sleuth and spring-cloud-sleuth-zipkin). Then, configure your application.properties to point to the Zipkin server:
spring.application.name=my-traced-servicespring.zipkin.base-url=http://localhost:9411spring.sleuth.sampler.probability=1.0 (trace all requests)
Now, let's look at a simple service that sends traces!
Tracing an Endpoint Call
Here's a basic Spring Boot service. With the properties from the last scene and Sleuth dependencies, it will automatically send trace data to Zipkin when you hit its /hello endpoint.
Try running this and then visiting http://localhost:8080/hello. Check your Zipkin UI!
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 MyTracedServiceApplication {
public static void main(String[] args) {
SpringApplication.run(MyTracedServiceApplication.class, args);
}
@GetMapping("/hello")
public String hello() {
// Sleuth automatically adds tracing to this request
System.out.println("Processing /hello request...");
return "Hello from Traced Service!";
}
}Exploring the Zipkin UI
After making requests to your traced service, open http://localhost:9411 in your browser.
You can search for traces by service name or trace ID. The UI will show you a visual timeline of each trace, including its spans, duration, and dependencies between services.
Quick Check: Tracing Terms
Test your understanding of distributed tracing with Zipkin.
Recap: Debugging with Zipkin
Great job! You've learned how distributed tracing helps debug microservices, and how Zipkin and Spring Cloud Sleuth make it easy.
- Distributed tracing visualizes request flow.
- Zipkin collects and displays trace data.
- Sleuth automates instrumentation for Spring Boot.
This helps you quickly find issues and optimize performance across your services.
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Pertanyaan yang Sering Diajukan
Apakah pelajaran “Pelacakan Terdistribusi dengan Zipkin” gratis?
Ya — teks lengkap “Pelacakan Terdistribusi dengan Zipkin” gratis dibaca di sini di web. Untuk praktiknya secara interaktif (editor kode bawaan dan tutor AI 24/7) dan buka sisa kursus Spring Boot 4 Microservices & REST APIs, upgrade ke CoddyKit PRO. Kursus Spring Boot 4 Microservices & REST APIs mencakup 3 pelajaran total.
Apa yang akan aku pelajari di “Pelacakan Terdistribusi dengan Zipkin”?
Integrasikan Zipkin untuk pelacakan terdistribusi menyeluruh di seluruh layanan mikro guna men-debug interaksi kompleks. Kamu berlatih Spring Boot 4 Microservices & REST APIs 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 Spring Boot 4 Microservices & REST APIs?
Tidak diperlukan pengalaman sebelumnya. Spring Boot 4 Microservices & REST APIs 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 3 dari 3.
Berapa lama pelajaran “Pelacakan Terdistribusi dengan Zipkin” 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 Spring Boot 4 Microservices & REST APIs ini?
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