New scheduling framework in Kubernetes 1.15

The scheduling framework is a new pluggable architecture for Kubernetes Scheduler that makes scheduler customizations easy. It adds a new set of “plugin” APIs to the existing scheduler. Plugins are compiled into the scheduler. The APIs allow most scheduling features to be implemented as plugins, while keeping the scheduling “core” simple and maintainable.

https://kubernetes.io/docs/concepts/configuration/scheduling-framework/

Need to evaluate how this fits into kube-batch.  It appears there is some overlap.  

Example of implementing scoring:

func ScoreNode(_ *v1.pod, n *v1.Node) (int, error) {
   return getBlinkingLightCount(n)
}

However, the maximum count of blinking lights may be small compared to NodeScoreMax. To fix this, BlinkingLightScorer should also register for this extension point.

func NormalizeScores(scores map[string]int) {
   highest := 0
   for _, score := range scores {
      highest = max(highest, score)
   }
   for node, score := range scores {
      scores[node] = score*NodeScoreMax/highest
   }
}

It appears that it's fairly simple process to create a plugin.  It should be possible to tie into the existence of a DataPond with the correct classification as the scoring mechanism.  Additional scoring could be based on how busy a node is etc.

Note: scoring could also take into account the location of items in the local filesystem on the machine in addition to the category of the database.