We built Fluid with noisy neighbors(=requests to the same instance) in mind. So because we are a data-driven team, we
1. track metrics and have our own dashboards to ensure we proactively understand and act whenever something like that happens
2. also use these metrics in our routing to smartly know when to scale up. we have tested a lot of variations of all the metrics we gather and things are looking good
anyway, the more workload types we will host with this system, the more we know and the better/performant it will get. we're running this for a while now, and it shows great results.
there's no magic, just data coming from a complex system, fed into a fairly complex system!
hope that answers the question, and thanks for trusting us
So if undertood 1. correctly I could use this solution to potencially save money, but it could turn into a nigthmare very quickly if you guys aren't watching?
1. track metrics and have our own dashboards to ensure we proactively understand and act whenever something like that happens 2. also use these metrics in our routing to smartly know when to scale up. we have tested a lot of variations of all the metrics we gather and things are looking good
anyway, the more workload types we will host with this system, the more we know and the better/performant it will get. we're running this for a while now, and it shows great results.
there's no magic, just data coming from a complex system, fed into a fairly complex system!
hope that answers the question, and thanks for trusting us