What is AgentOps?

AgentOps serves as an operational layer for AI agents in production, offering visibility and control over the autonomous systems that utilize large language models (LLMs) for planning and decision-making. Unlike traditional request-scoped infrastructures, which handle a single request-response cycle, AgentOps addresses the complexities of multi-step, dynamic agent behavior by monitoring every LLM call and tool invocation, tracking token usage, latency, and expenditure, and enforcing guardrails and policy controls. This operational layer is crucial for managing reasoning errors, silent tool call failures, and cumulative cost and latency issues that arise from the complex interactions of agents. Portkey's AI Gateway exemplifies a shared control infrastructure that centralizes agent registration, model access, and compliance checks, enabling consistent governance across diverse agent frameworks and configurations. By enforcing controls at the infrastructure level rather than per-agent configurations, AgentOps ensures that agent behavior remains visible, bounded, and compliant with organizational policies, thus preventing issues like runaway loops and policy violations.

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