The reactive mode reacts to available resources. The autoscaler reacts to changing load and processing capacity and adjusts resources.
Completely different concepts and applicability. Most people want the autoscaler , but this is a recent feature and is specific to the k8s operator at the moment. Gyula On Fri, 1 Sep 2023 at 04:50, Dennis Jung <inylov...@gmail.com> wrote: > 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 >>> >>>
