Datacenter Metrics and Key Performance Indicators: Thematic taxonomy with verification status, formulas and proposed indicators

This document is a thematic taxonomy of the metrics and key performance indicators (KPIs) used, or proposed, to describe datacenters from chip to site and beyond the site boundary. It lists 619 metrics and measurements and 266 candidate KPIs in 28 families, grouped into seven sections: energy and electrical systems; thermal management, water and environment; IT systems and workloads; sustainability, lifecycle and integrated performance; reliability, resilience and service; capacity, operations and economics; and safety, security and governance. Each entry has a stable identifier and a definition; metrics carry a unit, KPIs a formula written with metric identifiers and a direction. Every entry also records its origin, a verification status against primary or secondary sources, a maturity class (117 standardized, 647 in use, 121 proposed), its measurement level from chip to organisation, and dimension flags for sustainability, efficiency, security, health and safety, and economics. A listed KPI is a candidate: it becomes a KPI only with an objective, a target and an owner. Cooling is split into the facility plant, the air path and direct liquid cooling, with KPIs that compare the liquid path with the whole site. calculation pipelines and a gaming-risk checklist, and draws the catalogue as hypergraphs in which families, sections, dimension flags and measurement levels are hyperedges and identifier references are directed edges; hovering a node shows the definition of the entry. Abbreviations are defined under every table. The L A T E X source and the figures are generated by Python scripts distributed with the document.

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Publication Details

Journal
Infoscience (Ecole Polytechnique Fédérale de Lausanne)
Published
2026-10-29
Primary Topic
Cloud Computing and Resource Management
Type
preprint
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preprint

Datacenter Metrics and Key Performance Indicators: Thematic taxonomy with verification status, formulas and proposed indicators

Xavier Ouvrard
Infoscience (Ecole Polytechnique Fédérale de Lausanne)
Cloud Computing and Resource Management
preprint

Datacenter Metrics and Key Performance Indicators: Thematic taxonomy with verification status, formulas and proposed indicators

Xavier Ouvrard
preprint en

Abstract

This document is a thematic taxonomy of the metrics and key performance indicators (KPIs) used, or proposed, to describe datacenters from chip to site and beyond the site boundary. It lists 619 metrics and measurements and 266 candidate KPIs in 28 families, grouped into seven sections: energy and electrical systems; thermal management, water and environment; IT systems and workloads; sustainability, lifecycle and integrated performance; reliability, resilience and service; capacity, operations and economics; and safety, security and governance. Each entry has a stable identifier and a definition; metrics carry a unit, KPIs a formula written with metric identifiers and a direction. Every entry also records its origin, a verification status against primary or secondary sources, a maturity class (117 standardized, 647 in use, 121 proposed), its measurement level from chip to organisation, and dimension flags for sustainability, efficiency, security, health and safety, and economics. A listed KPI is a candidate: it becomes a KPI only with an objective, a target and an owner. Cooling is split into the facility plant, the air path and direct liquid cooling, with KPIs that compare the liquid path with the whole site. calculation pipelines and a gaming-risk checklist, and draws the catalogue as hypergraphs in which families, sections, dimension flags and measurement levels are hyperedges and identifier references are directed edges; hovering a node shows the definition of the entry. Abbreviations are defined under every table. The L A T E X source and the figures are generated by Python scripts distributed with the document.

Infoscience (Ecole Polytechnique Fédérale de Lausanne)
Cloud Computing and Resource Management
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