Hello, everyone. My name is Neetu Gangwani. Today, I'm going to represent energy efficient, cost optimized serverless computing strategies, challenges and future directions. Serverless computing has transformed cloud computing, offering remarkable cost saving and operational simplicity. However, the growing adoption of serverless workloads raises concern about energy footprints. This presentation explores the intersection of energy efficiency and cost effectiveness in serverless computing, highlighting innovative strategies and addressing key challenges. Join us as we delve into the future of sustainable cloud computing. Now let's see why the serverless computing is in trend. The main reason serverless computing is in trend is because scaling on demand. Serverless platforms dynamically adjusts computing resources within milliseconds, automatically scaling from handling a few requests to the millions without intervention. This intelligence scaling ensures optimal performance while preventing both resource wastages and the application's bottleneck. Another one is pay per use pricing. With a revolutionary pricing model, organizations only pay for precise computation time in milliseconds. This granular approach can reduce cloud costs by 40 80 percent compared to traditional servers, making enterprise grade computing accessible to all. Another one is Simplified Operations By abstracting away infrastructure complexity, serverless enables developers to deploy 4x faster. Teams can focus on innovation and business logic rather than managing servers, security patches, scaling, configurations, dramatically accelerating time to market. Next, Addressing the Energy Footprints of Serverless So first one is energy aware auto scaling. Advanced machine learning algorithm analyze historical workload patterns in real time metrics to dynamically optimize resource allocation, reducing energy waste by up to 30 percent while maintaining sub millisecond response time. Another one is hardware software co design. Integration of ARM based processor and simply specialized hardware escalator. delivers up to 40 percent power saving compared to traditional x86 architecture while custom firmware optimization further energy efficiency. Third one is function chaining optimization intelligent function orchestration reduces inter function communication overhead by 50 percent through strategic co location and data caching while automated workflow analysis eliminates redundant compute cycle and memory operations. Emerging Energy Aware Pricing Model. So what is 40 percent is a reduction, whereas 25 percent is the cost saving. Advanced Carbon Aware Pricing Model factor in real time energy cost and environmental impact driving up to 40 percent reduction in data center power. consumption through smart workload scheduling and resource optimization and 25 percent in the cost saving implementation of AI driven resources allocations and energy monitoring tools results in 25 percent average cost saving enabling. Organizational automatically shift workloads to time and reason with optimal energy efficiency. Let's see the real world case studies and success stories. First one is retail. A Fortune 500 retailer transformed their Black Friday operation by implementing serverless computing, handling 2. 5 million transactions per reducing server energy consumption by 60%. This resulted in 2. 1 million annual cost saving while maintaining 100ms response time. Healthcare, a national healthcare network, revolutionized patient care by processing real time health data through serverless function. This enables analysis of 50, 000 patients record per minute while cutting energy usage by 40%, leading the faster diagnosis and 800, 000 dollars in annual infrastructure saving. Another one is financial services. A global investment firm modernized their trending platform using serverless architecture, processing 100, 000 transactions per second with 99. 99 percent reliability. This transformation slashed energy consumption by 30 percent and reduce transaction processing cost by 45 percent while improving response time by 65%. Let's see the challenges and opportunities for the sustainable serverless. First one is standardized benchmark. Establishing industry wide energy efficient metrics and testing protocol is essential for meaningful platform comparison. Current benchmark varies by up to 40 percent across providers, highlighting the urgent need for standardization. Multi tenant energy measurement. Accurate per tenant energy attribution in shared environment remains a critical challenge. Advanced monitoring system must track resource usage with 99. 9 percent accuracy while maintaining performance and privacy standards. Regulatory compliances organization must navigate an expanding framework of environmental regulations, including the EU's Green Deal, regional carbon Reporting requirements proactive adoption of sustainable practice can reduce compliance risk by 60%. What are the future direction? To build a sustainable serverless ecosystem. First one, technological innovation. Pioneering breakthrough advancement. In energy efficient serverless architecture through quantum computing integration, AI powered work to optimize and next generation cooling system. Second, industry wide collaboration for ranging strategic Partnership between lending cloud providers, academic institutions and enterprise stakeholders to establish universal green computing standards and accelerate sustainable serverless adoption. Third, developer empowerment, cultivating a culture of environmental responsibility by equipping Developers with energy, monitoring tools, sustainable metrics, and practical guidelines for building eco friendly serverless applications. Let's go to the future. The future of serverless, a new era of sustainability. First one, cost optimization. Next generation serverless platform will revolutionize cost management through AI powered resource allocation and granular usage based on pricing, potentially reducing cloud spending by up to 40 percent while maximizing computational efficiency. Another one, performance optimization. Machine learning driven scaling algorithm and containerized function execution will deliver consistent sub 50 millisecond response time, enabling real time application to handle million of concurrent requests while automatically balancing resource utilization. Another one is environmental responsibility, the biggest responsibility. The future of serverless embarrasses sustainability through smart power management, carbon aware scheduling, and renewable energy integration. Organizations can expect to reduce their computing carbon footprint by up to 60 percent while maintaining optimal performance through innovative green computing practice. Let's see the conclusion. A sustainable path forward. First one, energy efficiency. Implement next generation serverless architecture with intelligent workload distribution and automated resource optimization to reduce energy consumption. by up to 40 percent cost effectiveness, deploy advanced monitoring system and AI driven resource allocation to achieve 30 percent cost saving while maintaining peak performance through intelligent scaling decisions. Environmental impact drive positive environmental change through renewable energy integration. Achieving carbon neutral operations and supporting global sustainability goals with measurable carbon and reduction metrics. Thank you. Have a good one.