New in Confluent Cloud: Making Data & Pipelines Accessible for AI-Ready Streaming | Learn More
Confluent announces the General Availability of Queues for Kafka on Confluent Cloud and Confluent Platform with Apache Kafka 4.2. This production-ready feature brings native queue semantics to Kafka through KIP-932, enabling organizations to consolidate streaming and queuing infrastructure while...
Confluent's AI developer tools are now GA: an open-source local MCP server, a managed MCP server, and Agent Skills. Together they give AI coding assistants direct access to your streaming platform — the tools to act on it and the domain knowledge to build correctly.
Explore new Confluent Intelligence features: enhanced querying with Real-Time Context Engine, PII detection, sentiment analysis, and support for TimesFM, Anthropic, and Fireworks AI models.
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.
Learn how to design and implement a real-time data monetization engine using streaming systems. Get architecture patterns, code examples, tradeoffs, and best practices for billing usage-based data products.
Learn how to build a real-time compliance and audit logging pipeline using Apache Kafka® or the Confluent data streaming platform with architecture details and best practices including schemas, immutability, retention, and more.
Tableflow on Confluent Cloud now supports Delta Lake, Unity Catalog, and Azure (EA) for secure, governed, real-time analytics from Apache Kafka data - no ETL or custom pipelines required.
Use Confluent’s open source Connect migration utility to discover, assess, map, validate, and cut over self-managed Kafka connectors to fully managed in minutes.
Learn how software engineer Akshatha has grown as a strategic thinker and added new technical skills since joining Confluent’s Developer Productivity team.
Discover how a data streaming platform helps you unlock the full potential of your AI—and translates it into measurable business value.
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.
Learn how to manage connectors in Confluent Cloud as code using the Confluent Terraform Provider—complete with the role bindings and access controls needed to integrate external systems with Apache Kafka.
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.
At Current 2025 in New Orleans (Oct 29–30), developers, data engineers, operators, architects & tech execs unlock real-time data + AI insights.
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.