Enterprise ready with the Flink HTTP Connector

Have you ever wished you could handle problematic events in Flink SQL as easily as with DataStream side outputs? Imagine routing unprocessable records—such as those failing serialization—straight to a dead-letter Kafka queue without stopping your job.

The new Apache Flink HTTP connector makes this possible while unlocking even more capabilities. It allows you to treat API endpoints as dynamic Flink tables, enabling seamless integration with any technology that exposes APIs—without writing custom code. For example, you can connect to your favorite AI endpoint simply by declaring a Flink SQL table.

In this session, you’ll learn how to leverage the HTTP connector to keep your Flink jobs running even after exceptions, HTTP error codes, or deserialization failures. We’ll explore how its new metadata columns provide powerful tools for error handling and observability.

You’ll also discover best practices for tuning the connector for enterprise scenarios, including caching strategies, security configurations, and retry mechanisms.

Key Takeaways:

- How to integrate APIs into Flink SQL with zero custom code

- Techniques for handling errors gracefully and improving resilience

- Using metadata columns for better monitoring and debugging

- Enterprise tuning tips: caching, security, and retries

Get ready to make your Flink pipelines more resilient, scalable, and enterprise-ready with the HTTP connector!