Tarun Kumar Chatterjee
West Bengal University of Technology
Phoenix, Arizona, United States
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Tarun Kumar Chatterjee is a seasoned software professional with 18 years of experience architecting and developing enterprise applications. As a specialized Azure DevOps, Single Page Applications expert and Xamarin for mobile app enhancements on Android and iOS, Tarun has successfully delivered innovative solutions across multiple industries including Retail, Travel, Hospitality, E-Commerce, and Real Estate.
Tarun possesses deep technical proficiency in Microsoft Azure, .NET Core, Angular, ASP.NET MVC, C#, TypeScript, and SQL Server. He is particularly skilled in Machine Learning Operations and AI application deployment using Azure services such as Azure Open AI, Cognitive Services, Blob Storage, Functions, CosmosDB, and Azure Monitor.
Throughout his career at organizations including New York Technology Partners, Cognizant Technology Solutions, Digital Avenues Limited, and IBM, Tarun has demonstrated exceptional technical leadership by designing scalable cloud-native architectures that meet both current demands and future needs. He has led development teams in Agile environments with a focus on best practices and code quality.
Tarun has extensive experience implementing containerization strategies using Docker and Kubernetes, creating automated CI/CD pipelines for seamless deployments, and developing AI-powered solutions that significantly reduced operational costs. His work with Azure Open AI and Cognitive Services has helped organizations automate workflows and enhance user experiences.
In addition to his Bachelor of Engineering degree from West Bengal University of Technology, Tarun holds multiple professional certifications including Microsoft Certified: Azure Solutions Architect Expert (AZ-300/301), AWS Certified Developer–Associate (DVA-C01), and various Microsoft Technology Specialist certifications. He actively contributes to the SharePoint/.NET community through his blog at SharePoint Pals.
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Optimizing Cloud Expenditure Through AI: Strategic Cost Reduction Without Performance Compromise
As organizations increasingly rely on cloud infrastructure, costs have escalated dramatically, constituting a growing portion of enterprise IT budgets. Our innovative research explores how artificial intelligence can transform cloud resource management, offering substantial cost optimization while maintaining peak performance standards.
Our approach leverages sophisticated machine learning algorithms to analyze extensive operational data across diverse enterprise environments, identifying usage patterns that enable precise resource forecasting. The implementation of custom reinforcement learning models has demonstrated remarkable efficiency gains, substantially reducing cloud expenditure without compromising service reliability or availability.
Cross-industry implementations have yielded compelling outcomes: financial institutions have realized significant annual cost reductions, while e-commerce platforms have successfully managed peak traffic periods with optimized infrastructure costs despite handling increased transaction volumes.
This presentation outlines a comprehensive framework for AI-driven cloud optimization, featuring: advanced predictive analytics for anticipating demand fluctuations, intelligent resource allocation strategies that minimize excess capacity, seamless integration methodologies for existing cloud management systems, and detailed case studies documenting return on investment across various sectors.
As cloud services continue to represent an expanding portion of technology spending, implementing AI-based optimization strategies has become essential for maintaining competitive advantage. Discover how your organization can achieve meaningful cost efficiency while building capacity for future growth requirements.
Tarun Kumar Chatterjee
West Bengal University of Technology
Phoenix, Arizona, United States
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