New industry initiative establishes an open category for data architectures that power real-time applications and AI agents
Learn how to migrate to Confluent Cloud in hours using Confluent’s open source Kafka Copy Paste tool. Get an in-depth introduction to the KCP tool and a walk-through of the four steps of migrating from MSK to Confluent Cloud using the tool.
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 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 how Confluent is improving Kafka Connect with better observability, security, migrations, and connector flexibility—making data integration easier to scale.
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.
Discover how a data streaming platform helps you unlock the full potential of your AI—and translates it into measurable business value.
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 the built-in anomaly detection ML function in Confluent Cloud for Apache Flink® enables event-driven AI agents to detect and act on outlier system events faster.
Unlock real-time context for AI with Confluent’s Real-Time Context Engine. Evaluate, process, and serve trustworthy context continuously in Confluent Cloud.
Explore new Streaming Agents features — Agent Definition, Observability & Debugging, and access to Real-Time Context Engine — to build intelligent, context-aware AI on Confluent.
Transform real-time Kafka data into governed, AI-ready Delta Lake tables with Confluent Tableflow and Databricks Unity Catalog. Simplify pipelines, ensure governance, and unlock real-time analytics and AI.
Explore updates from Confluent Cloud’s Q4 2025 release, including new capabilities and availability for Streaming Agents, new Real-Time Context Engine, and more.
Unified Stream Manager is now GA! Bridge the gap between Confluent Platform and Confluent Cloud with a single pane of glass for hybrid data governance, end-to-end lineage, and observability.
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.
Confluent Private Cloud (CPC) is a new software package that extends Confluent’s cloud-native innovations to your private infrastructure. CPC offers an enhanced broker with up to 10x higher throughput and a new Gateway that provides network isolation and central policy enforcement without client...
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.