Abstract: Rapidly escalating cloud expenses and unpredictable performance pose significant challenges for organizations deploying Agentic AI applications in hybrid multi-cloud environments.

This workshop introduces modern cost optimization, performance control, and FinOps cloud solutions. This approach leverages automated observability alongside advanced modeling and gradient optimization techniques.

Automated observability enables precise workload tuning. Learn how to:

• Identify the most resource-intensive applications
• Pinpoint queries with the highest resource usage and failure rates
• Highlight applications with substantial data spills to local and remote storage

Modeling and optimization capabilities then determine optimal configurations, resource allocations, and workload management changes. You can then accurately predict budgets to consistently achieve Service Level Goals (SLGs) across all hybrid multi-cloud environments. These modeling results mitigate financial and operational risks.

We will review practical scenarios through detailed case studies, including pre-deployment application sizing, cloud platform selection, optimized cloud migration strategies, and dynamic capacity management. Additionally, we will review the results of validating recommendation accuracy by comparing predicted and actual cost and performance outcomes. Using this knowledge your CFO and CIO will both be pleased.