Error handling in clients in Kafka - Commands & Configuration

Introduction

When clients communicate with Kafka, errors can happen like network issues or wrong data. Handling these errors properly helps keep your app running smoothly and avoids losing messages.

When your app sends messages to Kafka and you want to retry if sending fails

When your app reads messages and needs to skip or log bad data without crashing

When network problems cause temporary disconnects and you want to reconnect automatically

When you want to log errors for later debugging without stopping your app

When you want to handle specific Kafka errors differently, like authorization failures

Commands

Starts a simple Kafka producer to send messages to the topic 'example-topic'. This helps test sending messages and observe error handling.

Terminal

kafka-console-producer --broker-list localhost:9092 --topic example-topic

Expected Output

No output (command runs silently)

→

--broker-list - Specifies the Kafka broker addresses to connect to

→

--topic - Specifies the topic to send messages to

Starts a simple Kafka consumer to read messages from 'example-topic' from the start. Useful to see messages and test error handling when consuming.

Terminal

kafka-console-consumer --bootstrap-server localhost:9092 --topic example-topic --from-beginning

Expected Output

No output (command runs silently)

→

--bootstrap-server - Specifies the Kafka broker addresses to connect to

→

--topic - Specifies the topic to read messages from

→

--from-beginning - Reads all messages from the start of the topic

Runs a Java Kafka producer client that includes error handling code to retry sending messages on failure.

Terminal

java -cp kafka-clients.jar:. ExampleKafkaProducer

Expected Output

Message sent successfully

Retrying to send message due to error: NetworkException

Message sent successfully

Runs a Java Kafka consumer client that handles errors like deserialization failures by logging and skipping bad messages.

Terminal

java -cp kafka-clients.jar:. ExampleKafkaConsumer

Expected Output

Consumed message: Hello

Error deserializing message, skipping

Consumed message: World

Key Concept

If you remember nothing else from this pattern, remember: always catch and handle errors in Kafka clients to keep your app stable and avoid losing messages.

Common Mistakes

Not catching exceptions in the Kafka client code

Uncaught exceptions crash the app and stop message processing

Wrap send and receive calls in try-catch blocks and handle errors gracefully

Ignoring retry logic on transient errors

Temporary network glitches cause message loss without retries

Implement retries with backoff for sending messages

Failing to log errors for later debugging

Without logs, it's hard to find and fix issues

Log all errors with clear messages and context

Summary

Use kafka-console-producer and kafka-console-consumer to test sending and receiving messages.

Write client code that catches exceptions when sending or receiving messages.

Implement retry logic and error logging to handle temporary failures and bad data.

Practice

1. What is the main purpose of error handling in Kafka clients?

easy

A. To increase the speed of message processing

B. To keep the client stable and responsive during failures

C. To reduce the size of messages sent

D. To automatically create Kafka topics

Solution

1. Step 1: Understand error handling role

   Error handling helps the client manage unexpected problems without crashing.

2. Step 2: Identify the main goal in Kafka clients

   Keeping the client stable and responsive ensures smooth operation even if errors occur.

3. Final Answer:

   To keep the client stable and responsive during failures -> Option B

4. Quick Check:

   Error handling = stability and responsiveness [OK]

Hint: Error handling keeps your client stable and responsive [OK]

Common Mistakes:

• Thinking error handling speeds up processing
• Confusing error handling with message size control
• Assuming error handling creates topics automatically

2. Which syntax correctly wraps a Kafka producer send call to catch exceptions in Java?

easy

A. producer.send(record).catch(e => console.log(e));

B. if (producer.send(record)) { } else { handleError(); }

C. try { producer.send(record); } catch (Exception e) { e.printStackTrace(); }

D. try catch producer.send(record);

Solution

1. Step 1: Identify correct Java try-catch syntax

   Java requires try { ... } catch (Exception e) { ... } to handle exceptions.

2. Step 2: Match syntax with Kafka producer send call

   try { producer.send(record); } catch (Exception e) { e.printStackTrace(); } correctly wraps the send call in try-catch block.

3. Final Answer:

   try { producer.send(record); } catch (Exception e) { e.printStackTrace(); } -> Option C

4. Quick Check:

   Java try-catch syntax = try { producer.send(record); } catch (Exception e) { e.printStackTrace(); } [OK]

Hint: Use try-catch blocks in Java to catch Kafka errors [OK]

Common Mistakes:

• Using if-else instead of try-catch for exceptions
• Using JavaScript syntax in Java code
• Missing braces in try-catch block

3. Given this Java Kafka consumer code snippet, what will be printed if a network error occurs during poll?

try {
  ConsumerRecords records = consumer.poll(Duration.ofMillis(100));
  for (var record : records) {
    System.out.println(record.value());
  }
} catch (WakeupException e) {
  System.out.println("Consumer interrupted");
} catch (Exception e) {
  System.out.println("Error during poll");
}

medium

A. Error during poll

B. Consumer interrupted

C. No output

D. Exception stack trace

Solution

1. Step 1: Identify exception types caught

   WakeupException prints "Consumer interrupted"; all other exceptions print "Error during poll".

2. Step 2: Determine exception for network error

   Network errors throw general exceptions, not WakeupException.

3. Final Answer:

   Error during poll -> Option A

4. Quick Check:

   Network error triggers general Exception = Error during poll [OK]

Hint: General exceptions print "Error during poll" [OK]

Common Mistakes:

• Confusing WakeupException with network errors
• Expecting no output on error
• Assuming stack trace prints automatically

4. Identify the error in this Kafka producer error handling code snippet:

try {
  producer.send(record);
} catch (KafkaException e) {
  System.out.println("Error sending message");
}
producer.close();

medium

A. producer.send() does not throw exceptions

B. Catch block should catch Exception, not KafkaException

C. Missing return statement after catch

D. producer.close() should be inside finally block

Solution

1. Step 1: Check resource cleanup

   producer.close() must run regardless of exceptions to free resources.

2. Step 2: Use finally block for cleanup

   Placing close() inside finally ensures it always executes.

3. Final Answer:

   producer.close() should be inside finally block -> Option D

4. Quick Check:

   Always close resources in finally block [OK]

Hint: Put cleanup code in finally block to always run [OK]

Common Mistakes:

• Closing producer only on success
• Catching too broad or wrong exceptions
• Assuming send() never throws exceptions

5. You want to build a Kafka consumer that retries polling up to 3 times on recoverable errors, then logs and stops. Which approach correctly implements this error handling?

hard

A. Use a loop with try-catch around poll; on exception increment retry count; break after 3 retries; finally close consumer

B. Call consumer.poll() once; if exception, immediately close consumer without retry

C. Wrap poll in try-catch but ignore exceptions and continue polling forever

D. Use multiple nested try-catch blocks without retry logic

Solution

1. Step 1: Understand retry logic requirements

   Retry polling up to 3 times on recoverable errors, then stop and log.

2. Step 2: Identify correct control flow

   Loop with try-catch, count retries, break after 3 attempts, and close consumer in finally block is correct.

3. Final Answer:

   Use a loop with try-catch around poll; on exception increment retry count; break after 3 retries; finally close consumer -> Option A

4. Quick Check:

   Retry with loop and try-catch = Use a loop with try-catch around poll; on exception increment retry count; break after 3 retries; finally close consumer [OK]

Hint: Use loop with try-catch and retry count for controlled retries [OK]

Common Mistakes:

• Not retrying on recoverable errors
• Ignoring exceptions and continuing endlessly
• Closing consumer too early without retries