[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-81806-en":3,"doc-seo-81806-105":30,"detail-sidebar-cat-0-en-105":83},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":13,"seo_description":14,"update_tm":28,"read_time":29},81806,137441390410,"Hazel","https://ap-avatar.wpscdn.com/avatar/2000252f4ab5702993?_k=1776741390130283984",8,"Research & Report","Measure Once, Model Everywhere Model-Based Per-Request Resource Consumption for HTTP","Recent proposals on HTTP-based sustainability disclosure specify what environmental information should be transmitted at the protocol boundary, such as via response headers, yet leave the practical challenge of generating per-request values in real deployments. This paper proposes a model-based method to estimate resource consumption per HTTP request without fine-grained power telemetry. It benchmarks endpoints offline, derives compact energy models from observable request features, and evaluates them online at the HTTP server boundary via an nginx extension that emits request-level sustainability metadata.","Measure Once, Model Everywhere:  \nModel-Based Per-Request Resource Consumption for [HTTP](HTTP)  \nGeerd-Dietger Hoffmann  \nGreen Coding Solutions,  \nUniversity of Potsdam, HTW Berlin  \nPotsdam, Germany [didi@green-coding.io](didi@green-coding.io)  \nVerena Majuntke  \nHTW Berlin Berlin, Germany [verena.majuntke@htw-berlin.de](verena.majuntke@htw-berlin.de)  \narXiv :2607 .0 1246v 1 [ cs .CY] 1 Jun 2026  \nAbstract  \nRecent proposals for [HTTP-based sustainability disclosure focus on](HTTP-based sustainability disclosure focus on)[ ](HTTP-based sustainability disclosure focus on)what environmental information should be transmitted at the protocol boundary, for example through response headers, but leave open the practical question of how such per-request values can be generated in realistic deployments. This paper addresses that implementation gap. We present a model-based approach for estimating resource consumption and 􀀘􀀤2 􀀴 per HTTP request without requiring fine-grained production power telemetry. The approach benchmarks endpoints offline under controlled conditions, derives compact endpoint-specific energy models from observable request features, and evaluates these models online at the [HTTP](HTTP) server boundary. We implement this mechanism as an nginx extension that loads aJSON model registry and emits per-request metadata for energy, grid intensity, embodied emissions, and total request-level impact. We show that heterogeneous request classes can be represented with constant, linear, and piecewise models, and that the same approach extends to endpoints whose dominant cost driver is only visible at the application layer through inputs such as token counts. Our evaluation indicates that the approach is operationally feasible and introduces only low runtime overhead.  \n1 Introduction  \nSoftware is increasingly delivered through [HTTP interfaces built on](HTTP interfaces built on)[ ](HTTP interfaces built on)opaque stacks of virtualised infrastructure, managed platforms, and third-party services. The dominant cloud-native model presents these resources as elastic and available on demand: compute, storage, and bandwidth can be acquired through a single API call or a dashboard click, with billing and quotas as the primary feedback channels. The same abstractions that make this delivery scalable also conceal the physical and ecological costs of operating the underlying infrastructure [10, 20, 25], so that at the interface where requests are issued the system appears practically limitless. Users can observe latency and price, but not the energy use or emissions of a single request. Providers face a similar challenge: even when disclosure is desired, request execution spans multiple systems, and fine-grained power telemetry is typically unavailable.  \nA recurring principle in sustainable computing is to expose information at the interface where decisions are made. The Software Carbon Intensity (SCI) specification expresses emissions relative to a functional unit 􀀧 [8] . For web systems, the natural functional unit is the [HTTP request. If](HTTP request. If) request-level impact were available atthe protocol boundary, clients could incorporate it into decisions such as retry behaviour, batching, or prompt design.  \nLIMITS ’26, Online 2026.  \n[HTTP is a natural disclosure](HTTP is a natural disclosure) surface, and prior work has proposed response headers for communicating carbon information [2, 19, 22, 23] . However, these efforts focus on what to disclose, not on how to derive per-request values in practice.  \nPer-request disclosure does not by itself reduce demand, but it is a precondition for the design strategies that do. Sufficiency-and sobriety-oriented approaches [21, 24], critiques of growth-oriented computing infrastructure [1], and low-impact server designs such as the solar website [4] all require the marginal environmental cost of an interaction to be legible at the boundary where the request is issued. Without that leg","cbCaifPPenABbSzV","https://ap.wps.com/l/cbCaifPPenABbSzV","pdf",656136,3,1,10,"English","en",105,"# Abstract\n# Introduction\n# Related Work","[{\"question\":\"How is the approach implemented and what metadata does it expose?\",\"answer\":\"The method is implemented as an nginx extension that loads a JSON model registry and emits per-request metadata. 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