Cloud Computing
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Growing need for automated cloud and edge resource management

The proliferation of AI is creating new paradigms in cloud resource management, as AI-driven automation (AIOps) becomes essential. Cloud providers are now embedding AI assistants into their platforms to automate complex tasks, such as resource provisioning - selecting and deploying computing resources for optimal application performance - and performance tuning.

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In addition, the massive energy footprint of AI workloads is accelerating the push towards green computing, with a focus on sustainable data centres and intelligent workload scheduling. To manage the unpredictable costs, institutions are adopting FinOps (Financial Operations), which is the practice of financial governance that unites IT, finance, and research faculties to optimise cloud spending and maximise value.

Maturity

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Changing dynamics in Responsible AI From large to small language models AR and smart glasses become more prominent Increasing AI-enhanced user experience Growing big tech competition for the XR stack Increased application of FAIR principles to enable digital ecosystems in Europe Growing relevance of TRUST principles for data repositories to secure data More decentralisation of data ownership enabled by SSI solutions Emergence of organisational wallets Push for transparent supply chains with digital product passports Bringing computing resources closer to the ‘edge’ Growing need for automated cloud and edge resource management Growing emphasis on neuromorphic (brain-inspired) computing Integrating photonics for accelerated information processing The battle for airwaves AI/Ops, digital twinning and the emergence of the LLM in network operations Power usage and ecological footprint From ad hoc experiments to applications Towards Fault-Tolerant Quantum Computing (FTQC) Cyber-physical technology calls for resilient minds A growing urge for chip sovereignty in Europe

Drivers

Impact

education

Education

  • As students engage with AI-driven cloud and DevOps tools, they will need focused skills in AIOps, FinOps, and sustainable computing to learn how to manage automation, costs, and environmental impact effectively.
Research

Research

  • The rise of AI-driven cloud management and DevOps practices enables researchers to accelerate experimentation and scale workloads efficiently, but also demands greater focus on cost management, sustainability, and cross-disciplinary collaboration.
Operations

Operations

  • These new paradigms and practices are helping institutions to manage IT complexity and to meet sustainability goals.
  • Although the integration of AI-driven cloud tools and DevOps practices enhances efficiency and scalability, new strategies for financial governance, sustainability, and cross-departmental coordination may need to be considered.
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