Technology

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.

Confluent is providing our customers and prospects with a full package to build trust and innovate securely with Confluent. With our technical documentation, foundational principles and a new level of transparency.

Powering analytics and AI requires reliable, consistent, and easily discoverable data to reach the data lake. To enforce these needs, strong and holistic governance is an important of building better platforms for getting from raw data to valuable insights and actions.

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.

Learn best practices for validating your Apache Kafka® disaster recovery and high availability strategies, using techniques like chaos testing, monitoring, and documented recovery playbooks.

Learn best practices for running Kafka Connect in production—covering scaling, security, error handling, and monitoring to build resilient data integration pipelines.

Learn how to automate BI with real-time streaming. Explore event-driven workflows that deliver instant insights and close the gap between data and action.

Discover how banks and payment providers use Apache Kafka® streaming to detect and block fraud in real time. Learn patterns for anomaly detection, risk mitigation, and trusted automation.

Discover why microservices architectures thrive with event-driven design and how streaming powers applications that are agile, resilient, and responsive in real time.