AgentField is an open-source control plane designed to run AI agents as production-grade backend services, applying cloud-native principles similar to Kubernetes to the world of autonomous software. Instead of treating agents as isolated scripts or prototypes, the system elevates them to first-class infrastructure components that can be deployed, orchestrated, and managed at scale across distributed environments. Developers define agents as typed functions, and the platform automatically handles orchestration, communication, identity, and execution, allowing agents to behave like APIs within a broader system architecture. The framework includes built-in support for asynchronous execution, long-running processes, and multi-agent coordination, enabling complex workflows that go far beyond simple prompt-response interactions. It also introduces strong identity and governance mechanisms, such as cryptographic identities and policy enforcement, ensuring that agents can operate securely.
Features
- Kubernetes-style control plane for deploying and managing AI agents
- Agents exposed as APIs that integrate with backend systems
- Asynchronous execution and long-running task support
- Built-in identity, authentication, and policy enforcement
- Real-time observability with logs, metrics, and health checks
- Scalable multi-agent orchestration with queues and workflows