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.

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).

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