FailureAtlas: A Taxonomy of Failure Modes in Multi-Provider LLM Serving Infrastructure

Abstract:Multi-provider LLM gateways reverse proxies that route, load-balance, and rate-limit requests across foundation-model APIs have become critical production infrastructure. Yet the failure modes specific to this architectural layer remain undocumented, scattered across issue trackers and post-mortems with no unifying framework. We introduce \fa{}, a two-axis taxonomy that classifies failures by their \emph{origin layer} (Network/Transport, Streaming/Protocol, State/Session, Model~Behavior, Governance/Cost) and their \emph{detectability} (Loud vs.\ Silent). We populate this taxonomy with five verified catalog entries sourced from public bug reports and first-hand stress testing, each accompanied by a mechanistic root-cause analysis. Three entries include standalone reproduction scripts. Our principal finding is that the most operationally severe failures are \emph{silent}: they return HTTP~200, pass every standard health check, and corrupt application state in ways that require semantic-level observability to detect. Two such silent failures a concurrency race condition causing history loss and a streaming index collision corrupting tool-call payloads were discovered first-hand during \cb{} evaluation campaigns.

Machine Learning (cs.LG); Software Engineering (cs.SE)

arXiv:2607.17525 [cs.LG]

(or arXiv:2607.17525v1 [cs.LG] for this version)

https://doi.org/10.48550/arXiv.2607.17525 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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