Hi, I'm a Dapr CNCF project maintainer. We've recently released Dapr Agents which provides agentic AI features together with built-in durable execution to guarantee statefulness and reliable agentic workflows that run to completion and retry upon failure. It runs natively on Kubernetes, has built-in OTEL integration and uses a lightweight architecture where agents scale to zero, allowing you to run thousands of agents on commodity hardware. It'd be great if you can test it out and give us feedback.
And benchmarks. Well thought out, structured, non-cherry-picked benchmarks to highlight which framework does well in what area.
Assuming you knew there are lots of alternatives, what led you to create it?
We wanted to create a vendor neutral framework that doesn't over pivot on features that are tied to the backing of a commercial product. The other and no less important point is the ecosystem that Dapr has around messaging and state integrations. A lot of the Agentic AI frameworks you see today will not withstand a restart of the process,let alone complete cluster shutdown. Dapr has durability built-in to handle these catastrophic failures
So I might have titled this submission "A durable, streaming agent framework".