Best practices for deploying multi-agent AI systems with distributed execution?

So I've been experimenting with building multi-agent systems using tools like CrewAI, LangGraph and Azure AI Foundry, but it seems like most of them run agents sequentially.

I'm just curious what's the best way to deploy AI agents in a distributed setup, with cost tracking per agent and robust debugging (I want to trace what data was passed between agents, which agent triggered which, even across machines)

What tools, frameworks or platforms for this? And has anyone here tried building or deploying something like this at scale?