Delivering Music Recommendations to Millions
At its heart, presenting personalized data and experiences for users is simple. But transferring, delivering and serving this data at high scale can become quite challenging.
In this session, we will speak about the scalability lessons we learned building Spotify's Discover system. This system generates terabytes of music recommendations that need to be delivered to tens of millions of users every day.
We will focus on the problems encountered when big data needs to be replicated across the globe to power interactive media applications, and share strategies for coping with data at this scale.
Rohan is a software engineer at Spotify's infrastructure team, building the infrastructure that is used to deliver music to millions of listeners each day. His previous experience includes building open data products for government agencies, and building scalable backend services for Fortune 500 companies.
Sriram has more than six years of experience as a software engineer. Along the way, he has worked on the whole stack of software development from UIs to backend services to data pipelines. He has been at Spotify for the past two years working on different ways to help users find new music including the Radio and Discover apps.