Menerapkan Pengalihan Cadangan dan Batas Waktu
Konfigurasikan pengalihan cadangan dan batas waktu yang terkendali untuk panggilan layanan yang tidak andal.
Menerapkan Pengalihan Cadangan dan Batas Waktu adalah pelajaran Spring Boot 4 Microservices & REST APIs gratis di CoddyKit. Ini adalah pelajaran 2 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.
Building Resilient Services
In microservices, services often depend on each other. What happens if one service is slow or fails?
This lesson explores timeouts and fallbacks, crucial patterns to make your applications resilient to such issues.
Dealing with Unreliable Calls
Imagine your user service calls a product service. If the product service hangs, your user service might wait indefinitely.
- Resource Drain: Threads get stuck, consuming memory and CPU.
- Poor User Experience: Users face long waits or unresponsive apps.
- Cascading Failures: One slow service can bring down others.
Understanding Call Timeouts
A timeout is a maximum duration an operation is allowed to take. If the operation doesn't complete within this time, it's aborted.
- Connection Timeout: How long to wait to establish a connection.
- Read Timeout: How long to wait for data after a connection is established.
Timeouts prevent your application from waiting forever for an unresponsive service.
Configuring Basic Timeouts
You can configure timeouts for HTTP clients like Spring's RestTemplate or WebClient. This example shows a simple RestTemplate setup.
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.context.annotation.Bean;
import org.springframework.web.client.RestTemplate;
import org.springframework.boot.web.client.RestTemplateBuilder;
import java.time.Duration;
@SpringBootApplication
public class TimeoutApp {
public static void main(String[] args) {
SpringApplication.run(TimeoutApp.class, args);
}
@Bean
public RestTemplate restTemplate(RestTemplateBuilder builder) {
return builder
.setConnectTimeout(Duration.ofSeconds(1)) // 1 second to connect
.setReadTimeout(Duration.ofSeconds(2)) // 2 seconds to read data
.build();
}
// In a real app, you'd inject and use this RestTemplate
// e.g., restTemplate.getForObject("http://localhost:8081/slow-service", String.class);
}Graceful Degradation with Fallbacks
Even with timeouts, a service call might still fail (e.g., due to network issues or service unavailability). A fallback provides an alternative action or default value when the primary operation fails.
This ensures your application can still respond gracefully, even if with limited functionality.
Simple Fallback Logic
You can implement fallbacks manually using try-catch blocks. This allows you to handle exceptions and return a default response.
Consider a simple method that fetches user details:
public class UserService {
public String getUserName(int userId) {
try {
// Simulate a network call that might fail
if (userId == 101) {
throw new RuntimeException("Service unavailable!");
}
return "User " + userId + " Details";
} catch (Exception e) {
// This is our fallback logic!
System.out.println("Error fetching user " + userId + ". Returning default.");
return "Guest User"; // Fallback value
}
}
public static void main(String[] args) {
UserService service = new UserService();
System.out.println(service.getUserName(100)); // Works
System.out.println(service.getUserName(101)); // Fails, returns fallback
}
}Resilience4j for Fallbacks
Manually managing fallbacks can become complex. Libraries like Resilience4j provide declarative ways to implement resilience patterns, including fallbacks.
Resilience4j integrates well with Spring Boot and allows you to specify a fallbackMethod that gets called when the primary method fails.
Declarative Fallbacks with Resilience4j
Using Resilience4j's @CircuitBreaker annotation, you can define a fallbackMethod. This method will be invoked if the main method fails or the circuit breaker is open.
First, you'd need the Resilience4j dependency. Then, you can apply it:
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;
import org.springframework.stereotype.Service;
import org.springframework.beans.factory.annotation.Autowired;
import io.github.resilience4j.circuitbreaker.annotation.CircuitBreaker;
@SpringBootApplication
@RestController
public class ResilienceApp {
@Autowired
private ProductService productService;
public static void main(String[] args) {
SpringApplication.run(ResilienceApp.class, args);
}
@GetMapping("/product-info")
public String getProductDetails() {
return productService.getProduct();
}
}
@Service
class ProductService {
private int callCount = 0;
@CircuitBreaker(name = "productService", fallbackMethod = "fallbackGetProduct")
public String getProduct() {
callCount++;
if (callCount % 3 != 0) { // Simulate failure 2 out of 3 times
throw new RuntimeException("Product service is down!");
}
return "Product A Details";
}
// This is the fallback method
public String fallbackGetProduct(Throwable t) {
System.out.println("Fallback activated: " + t.getMessage());
return "Default Product (Fallback)";
}
}Apply Your Knowledge
You have a microservice that calls an external payment gateway. This gateway is sometimes slow or fails.
Which combination of resilience patterns would best ensure your service remains responsive and provides a user-friendly experience, even if the payment gateway is unreliable?
Lesson Summary
We've learned how timeouts and fallbacks are essential for building robust microservices:
- Timeouts prevent service calls from hanging indefinitely, saving resources.
- Fallbacks provide alternative responses when primary operations fail, ensuring graceful degradation.
These patterns improve user experience and prevent cascading failures in distributed systems. Keep practicing to build even more resilient applications!
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Pertanyaan yang Sering Diajukan
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Semua pelajaran dalam kursus ini
- Pemutus Sirkuit dengan Resilience4j
- Menerapkan Pengalihan Cadangan dan Batas Waktu
- Pelacakan Terdistribusi dengan Zipkin