This is some amazing scale: ------------------- We run a peak of 500 r3.8xl instances in support of our batch users. That represents 16,000 cores of compute

This is some amazing scale: ------------------- We run a peak of 500 r3.8xl instances in support of our batch users. That represents 16,000 cores of compute with 120 TB of memory. We also added support for GPUs as a resource type using p2.8xl instances to power deep learning with neural nets and mini-batch. In the early part of 2017, our stream-processing-as-a-service team decided to leverage Titus to enable simpler and faster cluster management for their Flink based system. This usage has resulted in over 10,000 service job containers that are long running and re-deployed as stream processing jobs are changed. These and other services use thousands of m4.4xl instances. While the above use cases are critical to our business, issues with these containers do not impact Netflix customers immediately. That has changed as Titus containers recently started running services that satisfy Netflix customer requests.