AgentField

Overview

AgentField is a Go-based open source framework for building, running, and scaling AI agents with built-in observability, auditability, and identity-awareness. It treats agents as API-first microservices, enabling developers to debug and monitor agent behavior in production from day one.

Best for

Best for
Developers building production AI agents that need observable, auditable, and identity-aware behavior from the start

Use cases

• Debug and trace agent decision-making in production
• Scale agent deployments with identity-aware access controls
• Integrate agents into existing microservice observability stacks

Notes

AgentField is a Go-based open source framework for building, running, and scaling AI agents with built-in observability, auditability, and identity-awareness. It treats agents as API-first microservices, enabling developers to debug and monitor agent behavior in production from day one.

2,049 stars on GitHub. Last updated 2026-06-01. Licensed Apache-2.0.

Use cases

• Debug and trace agent decision-making in production
• Scale agent deployments with identity-aware access controls
• Integrate agents into existing microservice observability stacks

Pros

• Built-in observability and audit logging without extra tooling
• Lightweight Go runtime designed for production workloads
• Identity-aware by design, simplifying RBAC for agent systems

Cons

• Small community (2049 stars) means fewer shared plugins or examples
• Requires Go expertise to modify or extend the framework
• Still early-stage with limited production case studies

Indexed from awesome-llmops and enriched against its public facts.