AIOps for LLM systems addresses the gap between traditional infrastructure monitoring and the operational needs of production AI. Standard monitoring confirms systems are running but misses output drift, cost spikes, and request-level failures. AIOps introduces a control layer between applications and model providers that enables end-to-end request tracing, runtime routing and policy enforcement, proactive cost controls, and governance with full auditability. Practical implementation involves a gateway that intercepts every request, applies routing rules, enforces usage limits, and logs full execution context. Teams benefit from faster debugging, predictable costs, and consistent model behavior.

6m read timeFrom portkey.ai
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Why traditional MLOps falls shortHow AIOps solves these problemsWhat this looks like in practiceFAQs
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