Commoditizing Music Machine Learning : Services

Five years ago, music personalization at Spotify was a tiny team. The team read papers, developed models, wrote data pipelines and built services. Today personalization involves multiple teams in New York, Boston & Stockholm producing datasets, feature engineering and serving up products to users. Features like Discover Weekly and Release Radar are but the tip of […]


ELS: latency based load balancer, part 1

Load Balancing Most Spotify clients connect to our back-end via accesspoint which forwards client requests to other servers. In the picture below, the accesspoint has a choice of sending each metadataproxy request to one of 4 metadataproxy machines on behalf of the end user. The client should get a quick reply from our servers, so if one machine becomes too slow, it […]


How we use Python at Spotify

The most frequent question we heard at PyCon this weekend, was how do we use Python at Spotify. Hopefully this post answers the question! At Spotify the main two places we use Python are backend services and data analysis. Python has a habit of turning up in other random places, as most of our developers […]