By Xintong Song, Staff Software Engineer, Alibaba Cloud
At Flink Forward Barcelona 2025, we announced a major collaboration between Alibaba Cloud, Ververica, Confluent, and LinkedIn—four influential companies in the $100 billion data streaming industry—to jointly develop and contribute to Apache Flink Agents, a new open-source sub-project from the Apache Flink community designed to bring AI agents into the world of real-time, event-driven systems. This initiative marks a pivotal step toward industrial-scale AI applications that react instantly and autonomously to live data streams.

While AI agents have made rapid progress in interactive applications like chatbots, most still operate outside the high-throughput, low-latency world of real-time data processing. Yet in industrial settings—from e-commerce and finance to IoT and logistics—critical decisions must be made instantly in response to live events: a payment failure, a sensor anomaly, a user click.
These workloads demand more than just intelligence—they require massive scale, millisecond latency, fault tolerance, and stateful coordination, all of which are strengths of Apache Flink. But until now, there’s been no unified framework to bring agentic AI patterns into this proven streaming ecosystem. Apache Flink Agents bridges this gap.
Apache Flink Agents, a brand-new sub-project from the Apache Flink community, is an open-source framework for building event-driven agents. Building on Flink's battle-tested streaming engine, Apache Flink Agents inherits distributed, at-scale, fault-tolerant structured data processing and mature state management, and adds first-class abstractions for Agentic AI building blocks and functionalities - large language models (LLMs), prompts, tools memory, dynamic orchestration, observability, and more.
This initiative is the result of a community-based joint effort by developers from Alibaba Cloud, Ververica, Confluent, and LinkedIn, a group of engineers with deep expertise in large-scale stream processing and real-time AI. By combining our experience in production-grade data infrastructure and intelligent systems, we are aligning on a shared vision: bringing agentic AI into the streaming data ecosystem, where it can operate with scalability, reliability, and real-time responsiveness.
The key features of Apache Flink Agents include:
The first public release of Apache Flink Agents, version 0.1.0 is available today. This initial version provides core agent abstractions, integrates Flink's DataStream and Table APIs, supports Kafka-based action consistency, integrates with selected LLMs and vector stores, includes MCP support, and offers observability through event logs.
This milestone marks the beginning of a powerful new framework for building scalable, event-driven AI agents on top of Apache Flink. For more information, visit the Apache Flink Agents GitHub repository.
Detailed timelines, design discussions, and community input can be found in the GitHub Discussions section—your go-to place to follow and contribute to the project’s evolution.
If you're passionate about building intelligent, autonomous systems that react in real time to streaming events, Flink Agents is a project worth watching—and joining.
We warmly invite developers, contributors, and AI enthusiasts to get involved and help shape the future of event-driven AI with Apache Flink.
Read our in-depth blog: Flink Agents: An Event-Driven AI Agent Framework Based on Apache Flink
Watch the presentation from Flink Forward Asia Singapore 2025: Flink Agents – The Agentic AI Framework based on Apache Flink
Explore the original proposal: FLIP-531: Initiate Flink Agents as a new Sub-Project
The future of AI isn’t just smarter models—it’s smarter systems that act continuously, reliably, and at scale.
With Apache Flink Agents, we’re building that future—together.
Apache®, Apache Flink®, Flink®, and the Flink logo are trademarks are Foundation in the United States and/or other countries. No endorsement by the Apache Software Foundation is implied by using these marks. All other trademarks are the property of their respective owners.
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