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

Spring Retryによるリトライ機構

一時的な障害が発生した際にメッセージ処理を自動で再試行するSpring Retryを統合し、アプリケーションの堅牢性を高めます。

「Spring Retryによるリトライ機構」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 Do We Need Retries?

In distributed systems like those using Kafka, operations can sometimes fail due to temporary issues. These are called transient failures.

  • Network glitches
  • Temporary service unavailability
  • Database connection timeouts

Retries help overcome these by automatically re-attempting failed operations, improving system resilience and reducing manual intervention.

Meet Spring Retry

Spring Retry is a powerful framework that simplifies implementing retry logic in your applications. It provides both declarative (using annotations) and programmatic (using RetryTemplate) ways to handle transient errors.

It integrates seamlessly with Spring Boot to make your applications more robust, especially when interacting with external services like Kafka.

RetryTemplate Basics

The RetryTemplate is Spring Retry's programmatic core. It allows you to wrap any code that might fail and define how it should be retried. Let's see a basic example:

import org.springframework.retry.RetryCallback;
import org.springframework.retry.RetryContext;
import org.springframework.retry.support.RetryTemplate;

public class BasicRetryDemo {
    private static int attemptCount = 0;

    public static void main(String[] args) {
        RetryTemplate retryTemplate = new RetryTemplate();

        try {
            String result = retryTemplate.execute(
                new RetryCallback<String, RuntimeException>() {
                    @Override
                    public String doWithRetry(RetryContext context) {
                        System.out.println("Executing task. Attempt: " + (++attemptCount));
                        if (attemptCount < 3) {
                            throw new RuntimeException("Simulated service failure!");
                        }
                        return "Task completed successfully!";
                    }
                });
            System.out.println(result);
        } catch (RuntimeException e) {
            System.out.println("Final failure: " + e.getMessage());
        }
    }
}

Limiting Retries: Max Attempts

By default, RetryTemplate retries 3 times (1 initial attempt + 2 retries). You can configure this using a SimpleRetryPolicy. Let's set it to 4 attempts:

import org.springframework.retry.RetryCallback;
import org.springframework.retry.RetryContext;
import org.springframework.retry.support.RetryTemplate;
import org.springframework.retry.policy.SimpleRetryPolicy;

import java.util.Collections;

public class MaxAttemptsDemo {
    private static int attemptCount = 0;

    public static void main(String[] args) {
        RetryTemplate retryTemplate = new RetryTemplate();
        
        // Configure max attempts (1 initial + 3 retries)
        SimpleRetryPolicy retryPolicy = new SimpleRetryPolicy(
            4, Collections.singletonMap(RuntimeException.class, true));
        retryTemplate.setRetryPolicy(retryPolicy);

        try {
            String result = retryTemplate.execute(
                new RetryCallback<String, RuntimeException>() {
                    @Override
                    public String doWithRetry(RetryContext context) {
                        System.out.println("Executing task. Attempt: " + (++attemptCount));
                        if (attemptCount < 4) { // Fails first 3 times
                            throw new RuntimeException("Transient error!");
                        }
                        return "Task completed!";
                    }
                });
            System.out.println(result);
        } catch (RuntimeException e) {
            System.out.println("Final failure: " + e.getMessage());
        }
    }
}

Smart Delays: Fixed Backoff

Retrying immediately might overwhelm a temporarily struggling service. A backoff policy introduces a delay between retries. FixedBackOffPolicy waits a set amount of time.

import org.springframework.retry.RetryCallback;
import org.springframework.retry.RetryContext;
import org.springframework.retry.support.RetryTemplate;
import org.springframework.retry.policy.SimpleRetryPolicy;
import org.springframework.retry.backoff.FixedBackOffPolicy;

import java.util.Collections;

public class FixedBackoffDemo {
    private static int attemptCount = 0;

    public static void main(String[] args) {
        RetryTemplate retryTemplate = new RetryTemplate();
        retryTemplate.setRetryPolicy(
            new SimpleRetryPolicy(3, Collections.singletonMap(RuntimeException.class, true)));
        
        // Configure fixed delay of 1000ms (1 second)
        retryTemplate.setBackOffPolicy(new FixedBackOffPolicy(1000L));

        try {
            String result = retryTemplate.execute(
                new RetryCallback<String, RuntimeException>() {
                    @Override
                    public String doWithRetry(RetryContext context) {
                        System.out.println("Attempt: " + (++attemptCount));
                        if (attemptCount < 3) {
                            throw new RuntimeException("Service busy!");
                        }
                        return "Success after retries!";
                    }
                });
            System.out.println(result);
        } catch (RuntimeException e) {
            System.out.println("Final failure: " + e.getMessage());
        }
    }
}

Exponential Backoff

For services that need more time to recover, exponential backoff increases the delay after each retry. This is often more effective than a fixed delay.

ExponentialBackOffPolicy lets you set initial delay, multiplier, and max delay.

import org.springframework.retry.RetryCallback;
import org.springframework.retry.RetryContext;
import org.springframework.retry.support.RetryTemplate;
import org.springframework.retry.policy.SimpleRetryPolicy;
import org.springframework.retry.backoff.ExponentialBackOffPolicy;

import java.util.Collections;

public class ExponentialBackoffDemo {
    private static int attemptCount = 0;

    public static void main(String[] args) {
        RetryTemplate retryTemplate = new RetryTemplate();
        retryTemplate.setRetryPolicy(
            new SimpleRetryPolicy(4, Collections.singletonMap(RuntimeException.class, true)));
        
        // Configure exponential backoff
        ExponentialBackOffPolicy backOffPolicy = new ExponentialBackOffPolicy();
        backOffPolicy.setInitialInterval(100L); // 100ms
        backOffPolicy.setMultiplier(2.0);      // Doubles each time
        backOffPolicy.setMaxInterval(2000L);   // Max 2 seconds
        retryTemplate.setBackOffPolicy(backOffPolicy);

        try {
            String result = retryTemplate.execute(
                new RetryCallback<String, RuntimeException>() {
                    @Override
                    public String doWithRetry(RetryContext context) {
                        System.out.println("Attempt: " + (++attemptCount));
                        if (attemptCount < 4) {
                            throw new RuntimeException("Resource contention!");
                        }
                        return "Success after exponential backoff!";
                    }
                });
            System.out.println(result);
        } catch (RuntimeException e) {
            System.out.println("Final failure: " + e.getMessage());
        }
    }
}

Retry on Specific Errors

You might only want to retry on certain types of exceptions, not all. SimpleRetryPolicy allows you to specify which exceptions should trigger a retry.

Exceptions not in the list will cause immediate failure.

import org.springframework.retry.RetryCallback;
import org.springframework.retry.RetryContext;
import org.springframework.retry.support.RetryTemplate;
import org.springframework.retry.policy.SimpleRetryPolicy;

import java.io.IOException;
import java.util.HashMap;
import java.util.Map;

public class SpecificExceptionDemo {
    private static int attemptCount = 0;

    public static void main(String[] args) {
        RetryTemplate retryTemplate = new RetryTemplate();
        
        Map<Class<? extends Throwable>, Boolean> retryableExceptions = new HashMap<>();
        retryableExceptions.put(IOException.class, true); // Only retry IOException
        retryableExceptions.put(MyCustomTransientException.class, true); 

        SimpleRetryPolicy retryPolicy = new SimpleRetryPolicy(3, retryableExceptions);
        retryTemplate.setRetryPolicy(retryPolicy);

        try {
            String result = retryTemplate.execute(
                new RetryCallback<String, Exception>() { // Note: now throws Exception
                    @Override
                    public String doWithRetry(RetryContext context) throws Exception {
                        System.out.println("Attempt: " + (++attemptCount));
                        if (attemptCount == 1) {
                            throw new IOException("Network issue!"); // Will retry
                        } else if (attemptCount == 2) {
                            throw new MyCustomTransientException("DB lock!"); // Will retry
                        } else if (attemptCount == 3) {
                            throw new IllegalArgumentException("Bad data!"); // Will NOT retry
                        }
                        return "Success!";
                    }
                });
            System.out.println(result);
        } catch (Exception e) {
            System.out.println("Final failure: " + e.getClass().getSimpleName() + " - " + e.getMessage());
        }
    }
    
    static class MyCustomTransientException extends RuntimeException {
        public MyCustomTransientException(String message) { super(message); }
    }
}

Handling Final Failures: @Recover

What happens if all retries are exhausted and the operation still fails? You need a fallback!

In a Spring context, the @Recover annotation marks a method to be called when a @Retryable method permanently fails. It lets you provide alternative logic or gracefully log the error.

For RetryTemplate, you can provide a RecoveryCallback to achieve similar fallback behavior.

Spring Kafka Listener Retries

For Spring Boot Kafka consumers, you can apply the @Retryable annotation directly to your @KafkaListener methods. This ensures that if message processing fails, the listener will retry before the message is potentially sent to a Dead Letter Topic (DLT).

Remember to enable Spring Retry with @EnableRetry on your application class!

import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.retry.annotation.Retryable;
import org.springframework.stereotype.Component;
import org.springframework.retry.backoff.Backoff;

// This is a conceptual example for a Kafka Listener.
// It requires a running Kafka broker and Spring Boot app.
@Component
public class MyKafkaListener {
    private int processAttempts = 0;

    @KafkaListener(topics = "myTopic", groupId = "myGroup")
    @Retryable(
        value = {RuntimeException.class}, // Retry on RuntimeException
        maxAttempts = 5,
        backoff = @Backoff(delay = 1000) // Initial 1s delay
    )
    public void listen(String message) {
        processAttempts++;
        System.out.println("Processing message: '" + message + "' (Attempt " + processAttempts + ")");
        if (processAttempts < 3) { // Simulate failure for first 2 processing attempts
            throw new RuntimeException("Failed to process: " + message);
        }
        processAttempts = 0; // Reset for next message
        System.out.println("Successfully processed: " + message);
    }
}

public class Main {
    public static void main(String[] args) {
        System.out.println("This code demonstrates @Retryable on a @KafkaListener method.");
        System.out.println("It would run within a Spring Boot application connected to Kafka.");
    }
}

Retry Configuration Check

You are building a Kafka consumer that processes orders. Sometimes, the external payment service is temporarily unavailable. You want to retry processing an order up to 5 times, with an initial delay of 500ms, doubling each time, but not exceeding 5 seconds. Which configuration for @Retryable is correct?

Recap: Spring Retry

In this lesson, you learned how to make your Kafka consumers more resilient using Spring Retry:

  • Understood the need for retries for transient failures in distributed systems.
  • Explored RetryTemplate for programmatic retry logic, demonstrating its core features.
  • Learned how to configure maxAttempts and different BackOffPolicy strategies (fixed and exponential).
  • Understood the role of @Retryable and @Recover annotations for declarative retries in a Spring context, particularly for @KafkaListener methods.

Next, we'll explore Dead Letter Topics (DLT) for handling messages that permanently fail after all retries, ensuring no data is lost.

よくある質問

「Spring Retryによるリトライ機構」レッスンは無料ですか？

はい。「Spring Retryによるリトライ機構」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。

「Spring Retryによるリトライ機構」で何を学びますか？

一時的な障害が発生した際にメッセージ処理を自動で再試行するSpring Retryを統合し、アプリケーションの堅牢性を高めます。 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。

「Spring Retryによるリトライ機構」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。

このコースのすべてのレッスン

  1. コンシューマー例外の処理
  2. Spring Retryによるリトライ機構
  3. デッドレタートピック（DLT）の実装
  4. Retry Topicsによるノンブロッキング再試行
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