By eyeballing the graphs it looks like "tl:dr", yes by about 10%, and sometimes just because a job takes longer. Another thing to note is that redis and postgr

By eyeballing the graphs it looks like "tl:dr", yes by about 10%, and sometimes just because a job takes longer. Another thing to note is that redis and postgres are i/o heavy and many production environments (esp in aws) will choose not to dockerise i/o heavy stuff. I wish they had included a statement like that so I didn't have to stick my neck out and give an eyeball estimate, but I suppose this kind of statement is harder to defend and the data they provided was more nuanced. With that said, power is largely divorced from cost in actual operation except at extreme scale. This is because purchaseable and billable units of compute are usually not utilised to 100% capacity, both in cloud and bare-metal situations. Another way to say this is, most people essentially prepay more "power budget" than they actually use. Since a primary use of docker (esp via kube) is workload consolidation, it's hard to know what real impact this has on the world.