> Where big iron might be something between a raspberry pi with an NVMe hat and a gaming PC.
At my last startup (with ~3 technical employees), I was talking to the CTO about our cloud spend and planning for properly scaling infra after we got our first customer. We weren't "a SaaS website", but (hand-waving) we did complex physics modeling and analytics on data streams. The (physicist) CTO had heard of k8s and cloud stuff and wanted me to investigate how we should scale our cloud. He was convinced it'd be expensive to do "all those physics calculation with 64 bit numbers".
I showed him our entire cloud - gateway, database(s), physics modeling, metrics collection, log aggregation, etc - running at 1000x estimated 1-customer load from a MacBook. I offered to set him up a personal raspberry pi to stress test before a k8s cluster.
We ended up with a sensible single medium EC2 instance running everything, with some extra stuff for fail-over. AFAIK the only change made after I left was using a cloud-vendor DB.
At my last startup (with ~3 technical employees), I was talking to the CTO about our cloud spend and planning for properly scaling infra after we got our first customer. We weren't "a SaaS website", but (hand-waving) we did complex physics modeling and analytics on data streams. The (physicist) CTO had heard of k8s and cloud stuff and wanted me to investigate how we should scale our cloud. He was convinced it'd be expensive to do "all those physics calculation with 64 bit numbers".
I showed him our entire cloud - gateway, database(s), physics modeling, metrics collection, log aggregation, etc - running at 1000x estimated 1-customer load from a MacBook. I offered to set him up a personal raspberry pi to stress test before a k8s cluster.
We ended up with a sensible single medium EC2 instance running everything, with some extra stuff for fail-over. AFAIK the only change made after I left was using a cloud-vendor DB.