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docs: center images in whitepaper
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initiatives/1675-ai-sustainability-papers/1675-ai-sustainability-framework/[WHITEPAPER] Foundations & Framework for Sustainable AI in Cloud-Native Environments.md

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# Foundations & Framework for Sustainable AI in Cloud Native Environments
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| TAG / Group Home: [https://tag-runtime.cncf.io/wgs/cnaiwg/](https://tag-runtime.cncf.io/wgs/cnaiwg/) Authors (listed alphabetically): Adel Zaalouk Andrew Block, Red Hat Marisol Palmero Nimisha Mehta Payam Mohajeri Prateek Kumar Viktor Lu Vincent Caldeira, Red Hat | GitHub Issues: [CNCF TOC Issue 1675](https://github.com/cncf/toc/issues/1675) |
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The impact is global. The International Energy Agency projects that data-center electricity demand will nearly double to around 945 TWh by 2030, approaching 3% of global electricity consumption, with significant growth across North America, Europe, and Asia-Pacific.3
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## CNCF’s Role in Sustainable Cloud Native AI {#cncf’s-role-in-sustainable-cloud-native-ai}
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As AI adoption accelerates, its energy, carbon, and water impacts are becoming operational sustainability challenges. The CNCF ecosystem provides widely used cloud native building blocks to deploy, observe, and optimize AI workloads across distributed environments, aligned with CNCF’s mission to make cloud native computing ubiquitous.[^6]
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6. Instrument and standardize telemetry
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The practical outcome of this approach is a measurable loop: telemetry reveals waste (idle accelerators, oversized services, inefficient placement), and platform controls convert those insights into action (autoscaling, scheduling, placement, and time shifting). This makes sustainability improvements repeatable across teams and workloads, while aligning operational behavior with the growing scale of AI and evolving governance expectations.3 5 21
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[^1]: [CNCF Environmental Sustainability TAG](https://tag-env-sustainability.cncf.io/)
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[^2]: [Green Software for Practitioners (LFC131)](https://training.linuxfoundation.org/training/green-software-for-practitioners-lfc131/)

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