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It’s easy to overestimate that you’ll save money here - if you have waste, poor cost attribution, etc., you can easily do the same with Kubernetes managing the
by brown9-2 6y ago
It’s easy to overestimate that you’ll save money here - if you have waste, poor cost attribution, etc., you can easily do the same with Kubernetes managing the nodes and scheduling the processes. To actually save the money you have to fix those things first.
- cogman10 6y agoThe issue we have is that we are a very peeky computation requirements (not a steady stream of calculations going on). Further, we've got a fairly deep data processing pipeline. It's not unusual for us to see high loads on early parts of the system 1 hour and 1 hour later seeing high loads on the later parts of the system. Unfortunately, we don't currently have a way to scale out and reassign resources. That means we've built out for our peaks even though the majority of the time that hardware is sleeping. We could spend the time building out a scaling system (right now, our resources are all on prem). However, why do that when we can instead take advantage of k8s already built in scaling capabilities? So, technically not k8s that will be saving us money, but rather implementing autoscaling. However, the solution with k8s is really nice.
- brown9-2 6y agoCluster autoscaling with nodes on-prem, or in the cloud?