Hello, Thanks for your notice. Than what is the purpose of using 'reactive', if this doesn't do anything itself? What is the difference if I use auto-scaler without 'reactive' mode?
Regards, Jung 2023년 8월 18일 (금) 오후 7:51, Gyula Fóra <gyula.f...@gmail.com>님이 작성: > Hi! > > I think what you need is probably not the reactive mode but a proper > autoscaler. The reactive mode as you say doesn't do anything in itself, you > need to build a lot of logic around it. > > Check this instead: > https://nightlies.apache.org/flink/flink-kubernetes-operator-docs-main/docs/custom-resource/autoscaler/ > > The Kubernetes Operator has a built in autoscaler that can scale jobs > based on kafka data rate / processing throughput. It also doesn't rely on > the reactive mode. > > Cheers, > Gyula > > On Fri, Aug 18, 2023 at 12:43 PM Dennis Jung <inylov...@gmail.com> wrote: > >> Hello, >> Sorry for frequent questions. This is a question about 'reactive' mode. >> >> 1. As far as I understand, though I've setup `scheduler-mode: reactive`, >> it will not change parallelism automatically by itself, by CPU usage or >> Kafka consumer rate. It needs additional resource monitor features (such as >> Horizontal Pod Autoscaler, or else). Is this correct? >> 2. Is it possible to create a custom resource monitor provider >> application? For example, if I want to increase/decrease parallelism by >> Kafka consumer rate, do I need to send specific API from outside, to order >> rescaling? >> 3. If 2 is correct, what is the difference when using 'reactive' mode? >> Because as far as I think, calling a specific API will rescale either using >> 'reactive' mode or not...(or is the API just working based on this mode)? >> >> Thanks. >> >> Regards >> >>
