Execution Envelopes: A Shared Admission Contract for Backend AI Execution Requests

• URL: http://arxiv.org/abs/2605.08267v1
• Date: Fri, 08 May 2026 03:02:38 GMT
• Title: Execution Envelopes: A Shared Admission Contract for Backend AI Execution Requests
• Abstract summary: This paper introduces the execution envelope, a normalized internal admission object.<n>It records what kind of execution, what resources were requested, what policy-relevant scope accompanied the request, and what the backend ultimately granted.<n>The central claim is that a shared execution-admission contract is a useful missing primitive for modern AI backends.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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