Apache Kafka

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.

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.

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.

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.

Planning an Apache Kafka® migration? Learn how to estimate migration expenses, reduce costs, and compare self-managed vs managed real-time data platforms with expert insight.

Explore the hidden costs of real-time streaming—compare infrastructure, ops, and ROI between Confluent Cloud and self-managed Apache Kafka®. Learn how auto-scaling and governance lower TCO.

Confluent, powered by Kafka, is the real-time backbone for agentic systems built with Google Cloud. It enables agents to access fresh data (MCP) and communicate seamlessly (A2A) via a decoupled architecture. This ensures scalability, resilience, and observability for complex, intelligent workflows.

AWS Lambda's Kafka Event Source Mapping now supports Confluent Schema Registry. This update simplifies building event-driven applications by eliminating the need for custom code to deserialize Avro/Protobuf data. The integration makes it easier and more efficient to leverage Confluent Cloud.

Confluent’s Cluster Linking enables fully managed, offset-preserving Kafka replication across clouds. It supports public and private networking, enabling use cases like disaster recovery, data sharing, and analytics across AWS, Azure, Google Cloud, and on-premises clusters.

Confluent Cloud now offers native Kafka Streams health monitoring to simplify troubleshooting. The new UI provides at-a-glance application state, performance ratios to pinpoint bottlenecks (code vs. cluster), and state store metrics.

Learn how to scale Kafka Streams applications to handle massive throughput with partitioning, scaling strategies, tuning, and monitoring.

Learn how to choose the right Apache Kafka® multi-cluster replication pattern and run an audit-ready disaster recovery and high availability program with lag SLOs, drills, and drift control.

Learn how to handle data transformation, schema evolution, and security in Kafka Connect with best practices for consistency, enrichment, and format conversions.