Confluent Blog

Find out what’s next for Current 2026—including the role of the event in the growing data streaming community and updates to plans for Asia-Pacific and United States events.

Learn how to build a custom Kafka connector, which is an essential skill for anyone working with Apache Kafka® in real-time data streaming environments with a wide variety of data sources and sinks.

Manual schema management in Apache Kafka® leads to rising costs, compatibility risks, and engineering overhead. See how Confluent lowers your total cost of ownership for Kafka with Schema Registry and more.

Confluent is recognized in the 2025 Gartner Data Integration Tools MQ. While valued for execution, we are running a different race. Learn how we are defining the data streaming platform category with our Apache Flink® service and Tableflow to power the modern real-time enterprise.

Apache Kafka® cluster rebalancing seems routine, but it drives hidden costs in time, resources, and cloud spend. Learn how Confluent helps reduce your Kafka total cost of ownership.

Audit logging in Confluent Cloud can seem boring—until you need precise insights in a crisis. Learn how to easily filter audit logs for your serverless Apache Kafka® environment and improve your data security.

Manual Apache Kafka® monitoring and tool sprawl drive hidden costs in time, complexity, and cloud spend. Learn how Confluent lowers total cost of ownership for Kafka with integrated monitoring.

Explore the latest Confluent client updates, featuring KIP-848 general availability for improved consumer stability and native Asyncio support for Python. We’ve also added simplified OAuth metadata authentication for cloud security and new observability metrics for Node.js consumers.

Discover the real cost of building a data streaming platform in-house. Learn what drives expenses, compare to managed solutions, and see how to optimize total cost of ownership for platforms powered by Apache Kafka®.

Discover how Confluent is improving Kafka Connect with better observability, security, migrations, and connector flexibility—making data integration easier to scale.

Power Snowflake Cortex agents with real-time, trustworthy context using Confluent Intelligence, Streaming Agents, and the Real-Time Context Engine.

We are excited to announce that Confluent has entered into a definitive agreement to be acquired by IBM.

Confluent Hub has evolved into the new Confluent Marketplace—a curated catalog when you can discover, purchase, and deploy community and partner-built integrations and streaming solutions.

This blog introduces the concept of API chaining — a method where data is collected by sequentially calling multiple related APIs. The response from one API is used to construct the request for the next, creating a chain that enables richer, more contextual data collection.