[NathanKP]

AWS employee here. If you are able to achieve consistent greater than 50% utilization of your EC2 instances or have a high percentage of spot or reserved instances then ECS on EC2 is still cheaper than Fargate. If your workload is very large, requiring many instances this may make the economics of ECS on EC2 more attractive than using Fargate. (Almost never the case for small workloads though).

Additionally, a major use case for ECS is machine learning workloads powered by GPU's and Fargate does not yet have this support. With ECS you can run p2 or p3 instances and orchestrate machine learning containers across them with even GPU reservation and GPU pinning.

[chrissnell]

I'm not totally up to speed on ECS vs EKS economics but it seems like EKS with p2/p3 would be a sweet solution for this. Even better if you have a mixed workload and you want to easily target GPU-enabled instances by adding a taint to the podspec.

[NathanKP]

Kubernetes GPU scheduling is currently still marked as experimental: https://kubernetes.io/docs/tasks/manage-gpus/scheduling-gpus...

ECS GPU scheduling is production ready, and streamlined quite a bit on the initial getting started workflow due to the fact that we provide a maintained GPU optimized AMI for ECS that already has your NVIDIA kernel drivers and Docker GPU runtime. ECS supports GPU pinning for maximum performance, as well as mixed CPU and GPU workloads in the same cluster: https://docs.aws.amazon.com/AmazonECS/latest/developerguide/...