[barrkel]

We max out our compute about 3% of the time, and run at about 10% load the rest of the time. It's a similar story for memory consumption. And we run this multitenanted, where the max doesn't overlap for different tenants. And we can't move our customer data out of our data centre, so we can't use cloud elastic compute.

It's in this kind of a world that elastic compute provided by a cluster scheduler with efficient packing looks really appealing. And our jobs, while meaty in time and space, are stateless once the initial data is poured in, up until the results pop out - they are big functions, basically. Good match for a stateless container.

So k8s looks quite attractive.