June Monthly CASSUG Meeting
Details
Greetings, data enthusiasts!
Our June meeting is scheduled for Monday, June 15th, at 5:30 pm! We will meet in person at: Troy Web Consulting, 135 Mohawk St, Cohoes, NY 12047.
Please RSVP if you are attending, so we can purchase an appropriate amount of food for everyone. Food is TBA and will be announced closer to the meeting date. For this meeting, we are welcoming Kalyan Inturi, a longtime employee at Oracle with years of problem-solving experience! Thank you for taking the time and energy to join us and share your knowledge!
Our meeting schedule is as follows:
5:30 PM: Food, soft drinks, and networking
6:15 PM: Chapter news and announcements
6:30 PM: Presentation
We usually wrap up between 7:30 PM and 8:00 PM. Kalyan will be presenting on a real-world (and interesting) case study: "Centralizing Identity Data at Scale: Lessons from Building a Unified Auth Platform on SQL Server"
Session Details:
As SaaS organizations grow through acquisitions, authentication and authorization data often becomes fragmented across multiple databases, schemas, and user stores creating challenges for consistency, security, and operations. This session presents a real-world case study of unifying identity data across multiple products using a centralized, SQL Server–backed identity platform.
Built on OpenID Connect and OAuth 2.0, the architecture leveraged a central identity store, token-time claim enrichment, and event-driven replication to maintain consistency across distributed systems while supporting near-zero-downtime migrations. The talk explores how SQL Server was used to model identity relationships, support reliable change propagation, and enable auditing, deprovisioning, and session management at scale.
Attendees will learn how database design choices, asynchronous replication patterns, and careful separation of state improved reliability, reduced integration timelines, and simplified post-acquisition onboarding. The lessons apply broadly to any system where identity, consistency, and operational stability depend on well-designed, highly available data platforms.
