Smart Infrastructure and Sustainable AI Data Centres Carbon-Native DCIM Big Data Storage Observability and Cloud Resource Optimization

Authors

  • Bernhard Plattner Professor of Computer Engineering, ETH Zurich, Switzerland Author

DOI:

https://doi.org/10.15680/IJCTECE.2024.0704010

Keywords:

Sustainable AI Data Centres, Smart Infrastructure, Carbon-Native DCIM, Green Computing, Cloud Optimization, Big Data Storage, Observability, Energy Efficiency, Carbon Footprint Reduction, Edge Computing, Renewable Energy Integration, AIOps

Abstract

The exponential growth of artificial intelligence (AI), big data analytics, and cloud computing has significantly increased global data centre energy consumption, raising concerns about carbon emissions and environmental sustainability. Smart infrastructure integrated with Sustainable AI Data Centres represents a transformative approach to addressing these challenges. This research explores carbon-native Data Centre Infrastructure Management (DCIM), intelligent big data storage optimization, advanced observability frameworks, and AI-driven cloud resource optimization as foundational pillars of sustainable digital ecosystems. Carbon-native DCIM systems embed real-time carbon intensity metrics into operational decision-making, enabling dynamic workload shifting, renewable energy alignment, and energy-aware orchestration. Observability platforms enhanced by AI provide predictive insights into cooling efficiency, power usage effectiveness (PUE), and hardware utilization patterns. Furthermore, intelligent storage tiering and cloud elasticity mechanisms reduce redundant processing and idle resource waste. The study proposes a comprehensive framework that integrates sustainability metrics into infrastructure automation, ensuring energy efficiency without compromising performance or scalability. By leveraging machine learning, digital twins, and autonomous control systems, sustainable AI data centres can significantly reduce environmental impact while maintaining high computational throughput. The findings demonstrate that carbon-aware optimization not only lowers operational costs but also strengthens regulatory compliance and long-term digital resilience.

 

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Published

2024-08-16

How to Cite

Smart Infrastructure and Sustainable AI Data Centres Carbon-Native DCIM Big Data Storage Observability and Cloud Resource Optimization. (2024). International Journal of Computer Technology and Electronics Communication, 7(4), 9162-9171. https://doi.org/10.15680/IJCTECE.2024.0704010