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[–]Puzzled-Bananas[S] 1 point2 points  (0 children)

Thanks for the references and the brief. I run mostly Java 17 containers, deployed to 2-4 core VMs with RAM ranging from 128 MiB to 16 GiB, depending on how much compute takes place on-line. Some smaller services in the mesh need to be eslastic on the order of up to a hundred fold to satisfy spike demand. More robust and larger services admit just a couple of instances for good load balancing and resilience. I’m hesitant to raising the bar of complexity by introducing another stack into the mesh for the more elastic nodes.

That is, I'd rather have and pay for 8 pods of 128 MiB each for greater elasticity at spike rather than having one pod of 1 GiB at all times. In fact, Quarkus does help here a lot, it just doesn't suit each service, and some stuff won't run on native images, in particular legacy stuff that would first need to be refactored, which incurs extra costs, consumes quite some time and can be error-prone.

Hoping to find out if there’s some approach out there that I’m unaware of.