P322：カーボンアウェア・スケジューリング：Microsoft Azure事例研究
P322: Carbon-aware scheduling: Microsoft Azure study (原題)
Sonu Kumar Singh
🤖 gxceed AI 要約
日本語
本稿はMicrosoft Azureにおけるカーボンアウェア・スケジューリングを、設計・ガバナンス・実証評価の観点から検討する。クラウド効率をコストと資源消費の両面で測定すべきと主張し、アーキテクチャ比較分析を通じて設計選択とセキュリティ統制・経済性・再現性を結びつける。合成ベンチマーク数値ではなく、仮説を実証結果に変えるために必要な実験設計を定義することを主眼とする。
English
This monograph examines carbon-aware scheduling in Microsoft Azure as a set of engineering obligations spanning design, governance, and empirical evaluation. It argues cloud efficiency should be measured as cost and resource consumption per successful workload under service-level constraints, linking architectural choices to security controls, economics, and reproducibility. Rather than supplying synthetic benchmarks, it defines the experiments needed to convert design hypotheses into supported results.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本企業のクラウド利用拡大とデータセンター電力消費の増大を背景に、Scope 2・Scope 3排出量の削減とクラウド調達の脱炭素化に関わる論点を提供する。SSBJ・有報でのGHG開示や再エネ調達戦略を検討する実務家にとって、炭素考慮型ワークロード運用の設計指針となり得る。
In the global GX context
As cloud workloads grow, carbon-aware scheduling connects operational efficiency to Scope 2/3 accounting and CSRD/ISSB disclosure of energy and emissions. This work contributes a governance and evaluation framework for turning vendor carbon claims into auditable evidence, relevant to global cloud decarbonization and FinOps practice.
👥 読者別の含意
🔬研究者:Provides a structured framework for evaluating carbon-aware scheduling claims and designing reproducible experiments.
🏢実務担当者:Offers guidance on integrating carbon-aware scheduling into Azure workloads and measuring cost and emissions per outcome.
🏛政策担当者:Highlights the need for verifiable metrics and governance around cloud carbon accounting claims.
📄 Abstract（原文）
Carbon-aware scheduling: Microsoft Azure study Author: Sonu Kumar Singh (Senior Consultant — Cloud & AI Solutions Architecture, Capgemini US LLC) Professional Credential: Member, IEEE (Membership # 102728576) | ORCID: 0009-0002-9180-4946 Abstract Cloud efficiency must be measured as cost and resource consumption per successful workload outcome under explicit service-level constraints rather than as isolated list prices or peak benchmark scores. Against this backdrop, the paper examines carbon-aware scheduling in Microsoft Azure. It asks a focused question: How should carbon-aware scheduling be designed, governed, and empirically evaluated for Microsoft Azure? Here, the topic is treated as a set of engineering obligations, not a slogan. The important questions are what must remain correct under scale and failure, which controls must follow the workload across services, and which measurements would be needed to support a claim. Framing the topic this way prevents the analysis from reducing to a list of vendor capabilities. The main contribution is a structured way to move from architectural claims to evidence. Using comparative architecture analysis, the paper links design choices with security controls, operating assumptions, economics, and reproducibility. It does not fill gaps with synthetic benchmark numbers; instead, it defines the experiment that would be required to turn a design hypothesis into a supported result. Architectural Research Scope Research Domain / Theme: FinOps, Performance & Sustainability Architectural Scope: Microsoft Azure Core Research Question: How should carbon-aware scheduling be designed, governed, and empirically evaluated for Microsoft Azure? Specification Standard: Full 20-page peer-level monograph featuring system topology diagrams, 7 empirical benchmark tables, and failure-mode analyses. Published as part of the Cloud, AI, and Distributed Data Systems: 500-Monograph Engineering Corpus.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.5281/zenodo.23109858first seen 2026-10-04 04:48:16 · last seen 2026-10-04 04:48:20
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