Naga Chand Putta - Engineering-Led Cloud Cost Optimization for SQL Server ...

### Engineering-Led Cloud Cost Optimization for SQL Server and Data-Intensive Financial Workloads

As financial institutions modernize SQL Server and data platform workloads in the cloud, infrastructure costs often grow faster than anticipated. Without disciplined engineering controls, performance tuning, storage expansion, and compliance requirements can quickly inflate monthly spend. This session presents practical, engineering-driven strategies to systematically optimize cloud costs for SQL Server–based financial applications, without compromising performance, resilience, or regulatory standards.
We will explore workload-aware optimization techniques including intelligent resource rebalancing, automated instance right-sizing, and hybrid pricing strategies (on-demand vs. reserved capacity) tailored specifically for SQL Server environments. The session will also examine serverless and elastic compute models for batch and reporting workloads, demonstrating when and how to shift non-critical processes to lower-cost execution patterns.
Advanced storage optimization strategies, such as tiered storage architectures, data compression, partitioning, lifecycle policies, and automated cleanup routines, will be presented as high-impact cost levers for transactional and analytical systems. We will also cover data efficiency techniques including deduplication approaches, optimized indexing strategies, and batch-processing design patterns that reduce both compute and storage overhead while preserving performance and data integrity.
Through real-world case studies from production financial systems, attendees will see measurable cost reductions achieved through disciplined engineering governance. You will leave with actionable frameworks, cost modeling techniques, and implementation checklists to help your organization optimize SQL Server workloads in the cloud with confidence and operational excellence.