Methodology: Every two weeks we collect most relevant posts on LinkedIn for selected topics and create an overall summary only based on these posts. If you´re interested in the single posts behind, you can find them here: https://linktr.ee/thomasallgeyer. Have a great read!

AI Transparency and Efficiency Metrics

  • Google’s energy breakdown for Gemini apps highlighted rapid prompt-level efficiency gains and a sharper view on training versus inference impacts

  • Experts stressed standardized disclosure, pointing to comparable metrics and an emerging AI Energy Score to align reporting

  • Salesforce’s AI Sustainability Outlook emphasized trusted, reliable, sustainable AI practices as a prerequisite for scaled adoption

  • Guidance focused on right-sizing models, minimizing unnecessary compute, and aligning performance with footprint

Data Centers, Water, and Thermal impacts

  • Water use surfaced as a key variable, with calls to clarify WUE and to distinguish training from inference consumption

  • Cooling choices and siting were underlined, including the need to manage local externalities such as noise near residential areas

  • Investment momentum appeared with Vesper Infrastructure Partners backing Terakraft to develop a green AI data center

  • Workload placement in facilities with strong renewable supply and advanced cooling was reinforced as a near-term lever

Green Software and DevOps in Practice

  • DevOps was framed as a driver of sustainable IT through waste reduction, resource optimization, and automation discipline

  • Green software practices were tied to tangible business benefits via lower energy use and operational efficiency

  • Carbon-aware design patterns were promoted, including efficient code paths and demand shaping for lower-carbon execution windows

  • Frugal AI training initiatives supported a culture shift toward responsible compute consumption

Measurement, Tooling, and Observability

  • The tool stack featured AWS Compute Optimizer, AWS Customer Carbon Footprint Tool, Google Carbon Sense, Microsoft Cloud for Sustainability, Scaphandre, and Kubernetes Vertical Pod Autoscaler

  • Carbon observability was positioned as first-class, tracking energy per request and enabling footprint-informed SRE decisions

  • Practical checklists emphasized monitoring, eliminating idle capacity, and continuously tuning workload-to-infrastructure fit

Hardware Footprint and Lifecycle Insights

  • A comprehensive LCA of the NVIDIA A100 accelerated the conversation on hardware-level impacts and data collection rigor

  • Collaboration with lifecycle experts reinforced the need for component-level transparency to inform procurement and design choices

Enterprise Moves and Reference Cases

  • Port de Barcelona modernized on IBM LinuxONE to consolidate workloads, cut energy use, and harden security while scaling open, containerized platforms

  • An AI plus Energy startup cohort was announced to drive grid modernization and clean energy innovation across emerging use cases

Community, Governance, and Knowledge Sharing

  • The Jisc Digital Sustainability newsletter curated global signals, helping teams track policy, practice, and technology shifts

  • Accenture introduced the SAIQ metric to quantify AI’s return on sustainability and guide investment decisions

  • ASML hosted a meetup on embedding sustainability into software engineering, linking practitioners across disciplines

  • Green IO London announced a program on responsible technology with hands-on use cases and sector-specific GreenOps insights

Want to see the posts voices behind this summary?

This week’s roundup (CW 34/ 35) brings you the Best of LinkedIn on Sustainability & Green ICT:

→ 60 handpicked posts that cut through the noise

→ 32 fresh voices worth following

→ 1 deep dive you don’t want to miss

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