Agentic AI Meets Kafka + Flink: Event-Driven Orchestration for Multi-Agent Systems

The rise of agentic AI systems is reshaping how intelligent applications are architected—introducing new levels of autonomy, collaboration, and complexity. As protocols like Agent-to-Agent (A2A) and Model Context Protocol (MCP) become foundational for multi-agent orchestration, the need for robust, scalable, and event-driven infrastructure becomes mission-critical.

In this session, we’ll explore how Apache Kafka and Apache Flink serve as the backbone for enabling multi-agent systems to operate reliably and responsively in high-throughput environments. From maintaining contextual memory to routing asynchronous and synchronous requests, we’ll break down the architectural patterns that support real-time, protocol-compliant agent communication at scale.

You’ll learn how to stream and process multimodal data - from gRPC to REST to JSON payloads - across distributed agent workflows while enforcing data integrity, managing quotas, and maintaining full observability. We’ll also cover how to apply stateful stream processing and fine-grained filtering to ensure agents always act on timely, relevant, and high-quality information.

Key Takeaways:

- How to integrate Kafka and Flink with agentic AI frameworks using A2A and MCP

- Designing asynchronous/synchronous agent workflows with low-latency pipelines

- Techniques for streaming multimodal data between AI agents and services

- Enabling quota enforcement, usage tracking, and cost visibility with Kafka/Flink

- Real-world lessons from building distributed, multi-agent AI systems in production

If you're working on next-gen AI systems that require context awareness, memory, coordination, and streaming intelligence - this session will show you how to make it real.