The exponential growth of Generative AI (GenAI) is simultaneously revolutionizing business and creating an unsustainable demand on global energy infrastructure. Are you ready to scale your Cloud capabilities without compromising your corporate sustainability goals? Our presentation introduces a strategic framework for Sustainable Cloud Solutions that turns resource intensity into an opportunity for operational efficiency and environmental stewardship. Stop settling for legacy infrastructure that strains the grid and join the movement toward performant systems engineered for a zero-carbon future. This presentation tackles the urgent and growing environmental footprint of GenAI, driven by its high-resource training and deployment. We will detail the alarming reality of GenAI training clusters, which exhibit an intense power density consuming 7-8 times the energy of typical workloads, rapidly necessitating reliance on fossil fuel-based data centers. Using concrete examples, such as the estimated 1,287 MWh and 552 tons of CO2 generated by the training of a major model like GPT-3, we establish the critical need for change. We then pivot to the practical application of Performance Engineering and Sustainable Software Development—the only viable solution to manage these demands. The session will cover key mitigation strategies ranging from architectural redesigns to code-level optimizations. Attendees will leave this session equipped with actionable knowledge and a strategic roadmap to immediately reduce the environmental and operational cost of their Cloud Solutions. You will learn how to: Implement Green Coding Practices: Discover specific techniques to optimize code for maximum computational efficiency and minimum energy consumption. Architect for Sustainability: Master the adoption of Sustainable Software Architectures, including the strategic deployment of serverless computing and microservices to ensure resources are consumed only during active execution, eliminating wasteful energy use from idle servers. Apply Energy-Efficient Algorithms: Identify and deploy algorithms and data structures that offer equivalent performance with a significantly smaller energy and carbon footprint, future-proofing your GenAI projects.
Almudena is of a mathematical vocation and has been dedicated to performance engineering for 18 years. Almudena has worked on projects with high traffic and high availability from online television platforms, job portals, security proxies, and now a European retailer. For 15 years, she has been actively involved in the dissemination of DevOps and performance culture in Spain. She is also an activist for the integration of female talent in STEM in Spain.
