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https://issues.apache.org/jira/browse/FLINK-27314?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17524710#comment-17524710
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Yang Wang commented on FLINK-27314:
-----------------------------------
Given that the reactive mode now could only work with standalone cluster, so we
might need to support standalone deployment first in the
flink-kubernetes-operator. The title of this ticket is a little confusing. I
think you mean support reactive mode in Flink Kubernetes Operator. The active
resource manager in Flink refers to YarnResourceManager,
KubernetesResourceManager, etc., which could actively allocate resource from
underlying cluster.
cc [~dannycranmer]
> Enable active resource management (reactive scaling) in Flink Kubernetes
> Operator
> ---------------------------------------------------------------------------------
>
> Key: FLINK-27314
> URL: https://issues.apache.org/jira/browse/FLINK-27314
> Project: Flink
> Issue Type: New Feature
> Components: Kubernetes Operator
> Reporter: Fuyao Li
> Priority: Major
>
> Generally, this task is a low priority task now.
> Flink has some system level Flink metrics, Flink kubernetes operator can
> detect these metrics and rescale automatically based checkpoint(similar to
> standalone reactive mode) and rescale policy configured by users.
> The rescale behavior can be based on CPU utilization or memory utilization.
> # Before rescaling, Flink operator should check whether the cluster has
> enough resources, if not, the rescaling will be aborted.
> # We can create a addition field to support this feature. The fields below
> is just a rough suggestion.
> {code:java}
> reactiveScaling:
> enabled: boolean
> scaleMetric: enum ["CPU", "MEM"]
> scaleDownThreshold:
> scaleUpThreshold:
> minimumLimit:
> maximumLimit:
> increasePolicy: <increase/decrease exponentially or linearly..>
> <some other timeout configuration...>{code}
>
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