Confluent launches Confluent Private Cloud, bringing cloud simplicity on-premises
Cloud simplicity meets on-premises security to quickly scale data streaming across even the most heavily regulated businesses.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
Keynote Day 2: Be Ready for What's Next
AI is driving change, and data streaming makes it possible for me to adapt.
Confluent launches Confluent Intelligence to solve the AI context gap
The unified platform to build and power contextual AI that scales seamlessly from pilot to production\
Demo: Streaming Agents for price matching, with RAG, observability, and Real-Time Context Engine
Streaming Agents enable you to build, deploy, and orchestrate event-driven agents on Apache Flink and Apache Kafka. Embedded in the stream, they can tap into the latest enriched data and be the eyes and ears of a business, continuously monitoring and acting on live operational events. In this demo, Brenner Heintz, Staff Technical Marketing Manager at Confluent, shows how to build price matching agents, do vector search for retrieval augmented generation (RAG), and leverage Confluent’s Real-Time Context Engine to process and serve fresh context the moment it’s needed for AI decision-making.
Keynote: Building Intelligent Systems on Real-time Data
Join Jay Kreps, Confluent leadership, our customers, and industry thought leaders to learn how you can build intelligent systems with real-time data. We’ll show you why streaming is becoming ubiquitous across the business—and how that unlocks a shift-left approach: process and govern at the source, then reuse everywhere. Expect live demos and candid customer stories that make it concrete. Whether you’re a data leader, architect, or builder, you’ll leave with practical playbooks for bringing real-time AI to production. The future is here-let's ignite it together!
Why Apache Kafka Migration Costs Are Often Underestimated
As a critical, stateful system, migrating Apache Kafka deployments is virtually always a complex engineering project where the most significant expenses are often hidden. Scoping and committing to a Kafka migration requires multiple layers of careful calculation involving infrastructure choices, data complexity, team expertise, and risk tolerance. Underestimating these variables leads to blown budgets and extended timelines.
Introducing Confluent Private Cloud: Cloud-Level Agility for Your Private Infrastructure
If you’re on a platform team running Apache Kafka, you know it’s rarely simple. You’re expected to keep it stable, performant, and secure while juggling requests from every direction. Supporting multiple teams and partners leads to operational complexity that never really goes away.
Tableflow is Production Ready: Delta Lake, Unity Catalog, Azure Early Availability (EA), and More Enterprise-Grade Features
Data-driven organizations know that unlocking real-time analytics from streaming data isn’t just about collecting and transmitting events. It’s about getting high-quality, governed, and query-ready tables into the hands of analysts and business users while ensuring enterprise-grade security and compliance. Traditionally, moving data from Apache Kafka into analytic tables required complex ETL pipelines, manual data wrangling, and custom governance processes.
Unified Stream Manager: Manage and Monitor Apache Kafka Across Environments
If you’re running Confluent Platform or our new offering, Confluent Private Cloud, on-premises, you have your reasons: data sovereignty, regulatory compliance, or maybe a phased cloud migration. Your on-prem Apache Kafka isn’t going anywhere. It’s a critical part of your infrastructure.
New in Confluent Cloud: Data in Motion for AI in Action
The most innovative companies know that artificial intelligence (AI) problems are fundamentally data problems. To produce the right results, AI applications, ranging from real-time fraud detection to autonomous agents, must share a common foundation: trustworthy data in motion.