Uber, one of the original ride-hailing services, developed a distributed infrastructure before most anyone even considered it for their enterprise. It ran Mesos before moving to Kubernetes three years ago.
The company is now moving from on premises to multicloud, which has its pros and cons as Uber wrestles with how to optimize GPU usage across multiple cloud providers, juggle workloads and create a cohesive converged infrastructure.
In a presentation at the co-located AI Day at KubeCon + CloudNativeCon North America in Atlanta this month,
