132 lines
4.9 KiB
Go
132 lines
4.9 KiB
Go
/*
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Copyright 2019 The Kubernetes Authors.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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*/
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package noderesources
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import (
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"context"
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"fmt"
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"math"
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v1 "k8s.io/api/core/v1"
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"k8s.io/apimachinery/pkg/runtime"
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"k8s.io/kubernetes/pkg/scheduler/apis/config"
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"k8s.io/kubernetes/pkg/scheduler/apis/config/validation"
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"k8s.io/kubernetes/pkg/scheduler/framework"
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"k8s.io/kubernetes/pkg/scheduler/framework/plugins/feature"
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"k8s.io/kubernetes/pkg/scheduler/framework/plugins/names"
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)
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// BalancedAllocation is a score plugin that calculates the difference between the cpu and memory fraction
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// of capacity, and prioritizes the host based on how close the two metrics are to each other.
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type BalancedAllocation struct {
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handle framework.Handle
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resourceAllocationScorer
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}
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var _ = framework.ScorePlugin(&BalancedAllocation{})
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// BalancedAllocationName is the name of the plugin used in the plugin registry and configurations.
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const BalancedAllocationName = names.NodeResourcesBalancedAllocation
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// Name returns name of the plugin. It is used in logs, etc.
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func (ba *BalancedAllocation) Name() string {
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return BalancedAllocationName
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}
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// Score invoked at the score extension point.
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func (ba *BalancedAllocation) Score(ctx context.Context, state *framework.CycleState, pod *v1.Pod, nodeName string) (int64, *framework.Status) {
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nodeInfo, err := ba.handle.SnapshotSharedLister().NodeInfos().Get(nodeName)
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if err != nil {
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return 0, framework.AsStatus(fmt.Errorf("getting node %q from Snapshot: %w", nodeName, err))
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}
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// ba.score favors nodes with balanced resource usage rate.
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// It calculates the standard deviation for those resources and prioritizes the node based on how close the usage of those resources is to each other.
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// Detail: score = (1 - std) * MaxNodeScore, where std is calculated by the root square of Σ((fraction(i)-mean)^2)/len(resources)
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// The algorithm is partly inspired by:
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// "Wei Huang et al. An Energy Efficient Virtual Machine Placement Algorithm with Balanced Resource Utilization"
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return ba.score(pod, nodeInfo)
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}
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// ScoreExtensions of the Score plugin.
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func (ba *BalancedAllocation) ScoreExtensions() framework.ScoreExtensions {
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return nil
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}
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// NewBalancedAllocation initializes a new plugin and returns it.
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func NewBalancedAllocation(baArgs runtime.Object, h framework.Handle, fts feature.Features) (framework.Plugin, error) {
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args, ok := baArgs.(*config.NodeResourcesBalancedAllocationArgs)
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if !ok {
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return nil, fmt.Errorf("want args to be of type NodeResourcesBalancedAllocationArgs, got %T", baArgs)
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}
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if err := validation.ValidateNodeResourcesBalancedAllocationArgs(nil, args); err != nil {
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return nil, err
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}
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resToWeightMap := make(resourceToWeightMap)
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for _, resource := range args.Resources {
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resToWeightMap[v1.ResourceName(resource.Name)] = resource.Weight
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}
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return &BalancedAllocation{
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handle: h,
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resourceAllocationScorer: resourceAllocationScorer{
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Name: BalancedAllocationName,
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scorer: balancedResourceScorer,
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useRequested: true,
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resourceToWeightMap: resToWeightMap,
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enablePodOverhead: fts.EnablePodOverhead,
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},
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}, nil
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}
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func balancedResourceScorer(requested, allocable resourceToValueMap) int64 {
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var resourceToFractions []float64
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var totalFraction float64
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for name, value := range requested {
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fraction := float64(value) / float64(allocable[name])
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if fraction > 1 {
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fraction = 1
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}
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totalFraction += fraction
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resourceToFractions = append(resourceToFractions, fraction)
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}
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std := 0.0
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// For most cases, resources are limited to cpu and memory, the std could be simplified to std := (fraction1-fraction2)/2
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// len(fractions) > 2: calculate std based on the well-known formula - root square of Σ((fraction(i)-mean)^2)/len(fractions)
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// Otherwise, set the std to zero is enough.
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if len(resourceToFractions) == 2 {
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std = math.Abs((resourceToFractions[0] - resourceToFractions[1]) / 2)
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} else if len(resourceToFractions) > 2 {
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mean := totalFraction / float64(len(resourceToFractions))
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var sum float64
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for _, fraction := range resourceToFractions {
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sum = sum + (fraction-mean)*(fraction-mean)
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}
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std = math.Sqrt(sum / float64(len(resourceToFractions)))
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}
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// STD (standard deviation) is always a positive value. 1-deviation lets the score to be higher for node which has least deviation and
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// multiplying it with `MaxNodeScore` provides the scaling factor needed.
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return int64((1 - std) * float64(framework.MaxNodeScore))
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}
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