Error Handling via Dead Letter Queue in Apache Kafka

Recognizing and handling errors is essential for any reliable data streaming pipeline. This blog post explores best practices for implementing error handling using a Dead Letter Queue in Apache Kafka infrastructure. The options include a custom implementation, Kafka Streams, Kafka Connect, the Spring framework, and the Parallel Consumer. Real-world case studies show how Uber, CrowdStrike, and Santander Bank build reliable real-time error handling at an extreme scale.

(Originally posted on Kai Waehner’s blog: “Error Handling via Dead Letter Queue in Apache Kafka”… Stay informed about new blog posts by subscribing to my newsletter)

Apache Kafka became the favorite integration middleware for many enterprise architectures. Even for a cloud-first strategy, enterprises leverage data streaming with Kafka as a cloud-native integration platform as a service (iPaaS).

Message Queue Patterns in Data Streaming with Apache Kafka

Before I go into this post, I want to make you aware that this content is part of a blog series about “JMS, Message Queues, and Apache Kafka”:

• 10 Comparison Criteria for JMS Message Broker vs. Apache Kafka Data Streaming
• THIS POST — Alternatives for Error Handling via a Dead…