I love the concept of FaaS, but the rush to reduce everything to *aaS has omitted intelligent scaling in favor of code atomicity. Let’s say your function oper

I love the concept of FaaS, but the rush to reduce everything to *aaS has omitted intelligent scaling in favor of code atomicity. Let’s say your function operates on a huge dataset, and requires 120ms responses. How can you do this consistently on a virtualized shared tenancy platform like AWS where (a) you don’t control the ‘ticks’ allotted your Vcpu and (b) you don’t have control of, or even insight, into the co-tenancy of the host machine? Easy answer. You can’t. IMHO, since you can’t control wether another process is awarded priority of Vcpu ticks OR memory, it can’t be done consistently over time on any non-dedicated platform. I have two full racks of servers, and I am regularly pricing the clouding of those server functions, and have been for years. Not once has the cost of moving to the cloud gone down. At the moment, the cost of moving all my servers to the cloud is $18.8k/mo versus the $2k I pay now, and I would lose all control over the throughput of the instances because a profit-only-motivated host will have final decision over my Vcpu and IOps ratios. Since my hardware hasn’t changed in several years, and the cost of clouding has increased over 100%, the only explanation is that providers are slowly and consistently slowing down Vcpus to maximize profits. They may be lowering the per-minute cost, but they’re lowering the Vcpu tick ratios much faster. There just isn’t any other explanation. For core functions, where latency is key, you either need to find a way to scale the sensitive functions across multiple instances, or host your own fully controlled instances and route only latency sensitive functions to them instead of the cloud. In the data tables case I mentioned above, you might consider a switch that will spawn multiple requests to FaaS instances with specific ranges of scope, effectively minimizing the work each call must do by systematically decreasing the scope of data it must operate on, and spreading that across (hopefully) multiple virtual hosts that may or may not be on different physical servers. Or, you could spend $100 a month on a dedicated machine at a colo provider that is honest and well known, and I believe you will find over time what I have... Profit comes from having control of your on-premise cloud, not farming it out. Cheers