Uber started using docker containers at scale in 2015, and has gone through a few generations of cluster management and service discovery technologies. In early 2019, we started working on migration from Mesos to Kubernetes to support secure service mesh and machine learning workloads.

This is a complex problem - there are thousands of services, tens of millions of containers to be launched daily while maintaining high machine resource utilization. To that end, a lot of customizations are built into our Kubernetes stack including elastic resource sharing, oversubscription, fast rollback and deploy, changes to service discovery and attestation etc.

This talk will cover:
- Overview of Uber Compute Infra
- API server benchmark and tweaks
- Custom controller and scheduler logic
- CRI: resource, health check, logging, isolation
- SPIRE and service discovery setup at Uber