Building Resilient Multi‑Agent Systems with Distributed LLM Orchestration and Event‑Driven Architecture
Introduction Large language models (LLMs) have moved from isolated “chat‑bot” prototypes to core components of real‑world software. When several LLM‑powered agents cooperate, they can solve problems that are too complex for a single model—think autonomous workflow automation, dynamic knowledge extraction, or coordinated decision‑making in logistics. However, scaling such multi‑agent systems introduces new challenges: Reliability – agents must continue operating despite network partitions, model latency spikes, or hardware failures. Scalability – workloads often fluctuate wildly; the architecture must elastically add or remove compute resources. Observability – debugging a conversation across dozens of agents requires transparent logging and tracing. Coordination – agents need a shared protocol for exchanging intent, state, and results without deadlocking. Two architectural patterns have emerged as particularly effective for addressing these concerns: ...