Execution Envelopes: A Shared Admission Contract for Backend AI Execution Requests
For developers of enterprise AI backends, this provides a missing primitive to attach governance and observability consistently across heterogeneous execution requests, though the contribution is incremental as it formalizes an existing practice.
The paper introduces the execution envelope, a normalized admission object for AI backends that records request metadata (who, what resources, policy scope) and granted resources, enabling shared governance and observability without replacing existing request models. The proposal is demonstrated on a model deployment endpoint.
Enterprise AI backends increasingly admit heterogeneous execution requests across model deployment, inference, evaluation, data movement, and agentic workflows. In many systems, those requests arrive in service-specific shapes, which makes it difficult to attach shared admission-time behavior such as logging, governance hints, resource accounting, authorization-aware policy hooks, and later runtime review without rebuilding the same contract in each subsystem. This paper introduces the execution envelope, a normalized internal admission object that records who is asking for what kind of execution, what resources were requested, what policy-relevant scope accompanied the request, and what the backend ultimately granted. The proposal is intentionally narrow. It does not replace service-specific request models, perform scheduling, or introduce a new authority token. Instead, it defines a descriptive admission seam that can be threaded through real backend paths before backend-specific resolution begins. I formalize the distinction between requested and granted resources, specify the field families, invariants, and lifecycle of the envelope, work through POST /serving/deploy_model as an initial proving ground, and position the design relative to usage control, analyzable authorization, admission control, and cluster scheduling. The central claim is that a shared execution-admission contract is a useful missing primitive for modern AI backends because it creates one place to attach governance and observability without pretending to solve placement, policy, and runtime execution in a single step.