Technology Blog

Learn how to interact with the librdkafka library when sending and how to handle errors correctly. Take a deepdive into the internal mechanics of the library.

Stepping into the world of Apache Kafka® can feel a bit daunting at first. Get started with the top resources for beginners to start building your first Kafka application!

In this blog post, we will provide an overview of Confluent's new SQL Workspaces for Flink, which offer the same functionality for streaming data that SQL users have come to expect for batch-based systems.

The Apache Flink PMC is pleased to announce the release of Apache Flink 1.18.0. As usual, we are looking at a packed release with a wide variety of improvements and new features. Overall, 174 people contributed to this release completing 18 FLIPS and 700+ issues.

This series of blog posts will take you on a journey from absolute beginner (where I was a few months ago) to building a fully functioning, scalable application. Our example Gen AI application will use the Kappa Architecture as the architectural foundation.

Confluent Schema Registry, both in Confluent Platform Enterprise and Confluent Cloud, now supports the use of data contracts. In this article, we'll walk through an example of enhancing a schema to be a full-fledged data contract.

Apache Kafka 3.6 is here! This release includes Tiered Storage (Early Access), the ability to migrate clusters from ZooKeeper to KRaft with no downtime, the addition of a grace period to stream-table joins, & more!

Ever dealt with a misbehaving consumer group? Imbalanced broker load? This could be due to your consumer group and partitioning strategy!

Today, we’re introducing Confluent Cloud’s fully managed service for Apache Flink®, improvements to Kora Engine, how AI and streaming work together, and much more.

As of today, Confluent Cloud for Apache Flink® is available for preview in select regions on AWS. In this post, learn how we’ve re-architected Flink as a cloud-native service on Confluent Cloud.

Learn the best practices for integrating Confluent with AWS Lambda to build event-driven architectures.

Learn about the role of batch.size and linger.ms in data compression.

Learn how to build a Java pipeline that consumes clickstream data from Apache Kafka®. Consuming clickstreams is something that many businesses have a use for and it can also be generalized to consuming other types of streaming data.

Dive into Flink SQL, a powerful data processing engine that allows you to process and analyze large volumes of data in real time. We’ll cover how Flink SQL relates to the other Flink APIs and showcase some of its built-in functions and operations with syntax examples.