I'm the co-founder of a new startup called Springtail. Our mission is to: Power the next stage of SaaS growth through an incredibly simple and intelligent database service.

My last position within Freshworks was as a principal architect in the Freshworks Analytics Platform team. This team provides an analytics platform that is used by other internal products to provide analytics to their external customers. My goal was to help redefine the analytics architecture and to improve database performance while optimizing cost.Prior to the analytics team, I was the principal architect for the Freshsuccess product (the productization of Natero after acquisition). I was responsible for the complete product architecture including design and implementation. I worked closely with the design, product management and engineering management teams on feature definition, roadmap and sprint planning.https://www.freshworks.com/customer-success-software

I co-founded Natero in the summer of 2012 as part of the Summer 2012 Y-Combinator class. We built a B2B Customer Success Platform with a strong focus on data analytics. Natero integrates with dozens of 3rd party SaaS tools for CRM, billing, support, NPS, etc, in addition to event data from web and mobile applications. We use this data to build a complete view of our customer's customer. With this data a customer success manager can build health-scores, trigger email campaigns, generate alerts, etc.

Founding member of the Advanced Technology Group (ATG) at NetApp within the CTO office. Helped grow the team to 20 engineers across 3 sites. Built novel storage system and file system prototypes to hand off to the product teams.Explored tiering in novel local file system designs.Worked on the integration of flash memory technologies into the storage system through the exploration of flash translation layers (FTLs).Core contributor to pNFS (parallel NFS) specification as part of the NFSv4.1 IETF standard. Includes prototyping NetApp pNFS server and Linux client.

Fault-tolerant storage systems spread data redundantly across a set of storage-nodes in an effort to preserve and provide access to data despite failures. One difficulty created by this architecture is the need for a consistent view, across storage-nodes, of the most recent update. Such consistency is made difficult by concurrent updates from distinct clients, partial updates made by clients that fail, and failures of storage-nodes. Although protocols exist for achieving such consistency, they generally fall short in a number of areas including efficiency, scalability, and flexibility.My PhD. thesis demonstrated how to achieve scalable, highly fault-tolerant storage systems by leveraging an efficient and flexible family of strong consistency protocols enabled by server versioning. In particular, the design of block-based storage systems and file systems are evaluated. Furthermore, the tradeoffs involved in supporting file system semantics, above the consistency protocol, were explored.