Escalating cloud costs and unpredictable performance are major challenges for organizations, particularly when deploying Generative AI (GenAI) applications in hybrid multi-cloud environments—a market projected to reach nearly $20 trillion by 2030. This paper introduces a novel systems approach to cost optimization, performance control, and FinOps decision-making through automated observability, advanced queueing network modeling, and gradient optimization. Observability automation narrows the scope of the tuning efforts by focusing on the most resource-consuming and credit use applications, applications with the highest rate of performance and cost anomalies, applications with the highest frequency of failed queries, and applications with the highest volume of data spilled to local and remote storage. Modeling and optimization determine the minimal configurations, resource allocation, workload management, and budgets needed to meet Service Level Goals (SLGs) for all business applications running on different cloud data platforms in the Hybrid Multi-Cloud environment. Modeling and optimization evaluate options and set cost and performance expectations for proposed changes. By comparing actual performance and costs with expectations, our approach enables closed-loop performance and cost control, mitigating the risks of unexpected financial and operational outcomes. The presented case studies highlight the value of our technology in optimizing application costs and controlling performance across diverse projects, including sizing new applications before cloud deployment, selecting appropriate cloud platforms, optimizing cloud migration strategies, and managing dynamic capacity in hybrid multi-cloud environments.
Dr. Boris Zibitsker is a founder and CEO of BEZNext. His focus is on the development of cloud performance and financial governance software optimizing cloud migration and dynamic capacity management decisions for Hybrid Multi-Cloud environments. Boris consults with many Fortune 500 companies. Dr. Zibitsker is a member of SPEC Research Group.
