Detailed Introduction
AgentField abstracts agent lifecycle, identity, and communication as cloud-native objects so multi-agent applications can run on a cluster with scalability, observability, and identity awareness. It combines scheduling, authentication, monitoring, and autoscaling so developers can deploy and operate agents similarly to microservices.
Main Features
- Kubernetes-native scheduling and runtime integration with native horizontal scaling.
- Identity-aware authentication for secure inter-agent communication and access control.
- Built-in observability: logs, metrics, and tracing for behavior analysis and troubleshooting.
- Microservice-style lifecycle management supporting rolling updates and rollbacks.
Use Cases
- Deploy multi-agent workflows as scalable backend services for task distribution, autonomous operations, and complex orchestration.
- Ensure secure agent-to-agent communication and auditing in multi-tenant or enterprise environments.
- Combine with RAG and external model services to provide long-running, domain-specific agent services.
Technical Features
- Implements Kubernetes extensions and controller patterns to reduce operational friction.
- Runtime design is language- and model-agnostic, enabling calls to external LLMs and inference services via APIs.
- Provides observability and authentication integration points for existing cloud-native monitoring and security toolchains.