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autoscaler
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Respect GPU limits in scale_down

This commit is contained in:
Łukasz Osipiuk 2018-06-11 14:45:35 +02:00
parent 0ca0b1bec3
commit 087a5cc9a9
7 changed files with 374 additions and 25 deletions
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7
cluster-autoscaler/cloudprovider/cloud_provider.go
View File

@ -163,6 +163,13 @@ const (
ResourceNameMemory = "memory"
)
// IsGpuResource checks if given resource name point denotes a gpu type
func IsGpuResource(resourceName string) bool {
// hack: we assume anything which is not cpu/memory to be a gpu.
// we are not getting anything more that a map string->limits from the user
return resourceName != ResourceNameCores && resourceName != ResourceNameMemory
}
// ResourceLimiter contains limits (max, min) for resources (cores, memory etc.).
type ResourceLimiter struct {
minLimits map[string]int64

35
cluster-autoscaler/context/autoscaling_context.go
View File

@ -51,6 +51,16 @@ type AutoscalingContext struct {
LogRecorder *utils.LogEventRecorder
}
// GpuLimits define lower and upper bound on GPU instances of given type in cluster
type GpuLimits struct {
// Type of the GPU (e.g. nvidia-tesla-k80)
GpuType string
// Lower bound on number of GPUs of given type in cluster
Min int64
// Upper bound on number of GPUs of given type in cluster
Max int64
}
// AutoscalingOptions contain various options to customize how autoscaling works
type AutoscalingOptions struct {
// MaxEmptyBulkDelete is a number of empty nodes that can be removed at the same time.
@ -73,6 +83,8 @@ type AutoscalingOptions struct {
MaxMemoryTotal int64
// MinMemoryTotal sets the maximum memory (in bytes) in the whole cluster
MinMemoryTotal int64
// GpuTotal is a list of strings with configuration of min/max limits for different GPUs.
GpuTotal []GpuLimits
// NodeGroupAutoDiscovery represents one or more definition(s) of node group auto-discovery
NodeGroupAutoDiscovery []string
// EstimatorName is the estimator used to estimate the number of needed nodes in scale up.
@ -134,6 +146,25 @@ type AutoscalingOptions struct {
Regional bool
}
// NewResourceLimiterFromAutoscalingOptions creates new instance of cloudprovider.ResourceLimiter
// reading limits from AutoscalingOptions struct.
func NewResourceLimiterFromAutoscalingOptions(options AutoscalingOptions) *cloudprovider.ResourceLimiter {
// build min/max maps for resources limits
minResources := make(map[string]int64)
maxResources := make(map[string]int64)
minResources[cloudprovider.ResourceNameCores] = options.MinCoresTotal
minResources[cloudprovider.ResourceNameMemory] = options.MinMemoryTotal
maxResources[cloudprovider.ResourceNameCores] = options.MaxCoresTotal
maxResources[cloudprovider.ResourceNameMemory] = options.MaxMemoryTotal
for _, gpuLimits := range options.GpuTotal {
minResources[gpuLimits.GpuType] = gpuLimits.Min
maxResources[gpuLimits.GpuType] = gpuLimits.Max
}
return cloudprovider.NewResourceLimiter(minResources, maxResources)
}
// NewAutoscalingContext returns an autoscaling context from all the necessary parameters passed via arguments
func NewAutoscalingContext(options AutoscalingOptions, predicateChecker *simulator.PredicateChecker,
kubeClient kube_client.Interface, kubeEventRecorder kube_record.EventRecorder,
@ -143,9 +174,7 @@ func NewAutoscalingContext(options AutoscalingOptions, predicateChecker *simulat
cloudProvider := cloudProviderBuilder.Build(cloudprovider.NodeGroupDiscoveryOptions{
NodeGroupSpecs: options.NodeGroups,
NodeGroupAutoDiscoverySpecs: options.NodeGroupAutoDiscovery},
cloudprovider.NewResourceLimiter(
map[string]int64{cloudprovider.ResourceNameCores: int64(options.MinCoresTotal), cloudprovider.ResourceNameMemory: options.MinMemoryTotal},
map[string]int64{cloudprovider.ResourceNameCores: options.MaxCoresTotal, cloudprovider.ResourceNameMemory: options.MaxMemoryTotal}))
NewResourceLimiterFromAutoscalingOptions(options))
expanderStrategy, err := factory.ExpanderStrategyFromString(options.ExpanderName,
cloudProvider, listerRegistry.AllNodeLister())
if err != nil {

130
cluster-autoscaler/core/scale_down.go
View File

@ -44,6 +44,7 @@ import (
"github.com/golang/glog"
"k8s.io/apimachinery/pkg/util/sets"
"k8s.io/autoscaler/cluster-autoscaler/utils/gpu"
)
// ScaleDownResult represents the state of scale down.
@ -109,27 +110,57 @@ type scaleDownResourcesDelta map[string]int64
// used as a value in scaleDownResourcesLimits if actual limit could not be obtained due to errors talking to cloud provider
const limitUnknown = math.MinInt64
func computeScaleDownResourcesLeftLimits(nodes []*apiv1.Node, resourceLimiter *cloudprovider.ResourceLimiter, timestamp time.Time) scaleDownResourcesLimits {
totals := make(map[string]int64)
totals[cloudprovider.ResourceNameCores], totals[cloudprovider.ResourceNameMemory] = calculateCoresAndMemoryTotal(nodes, timestamp)
resultScaleDownLimits := make(scaleDownResourcesLimits)
func computeScaleDownResourcesLeftLimits(nodes []*apiv1.Node, resourceLimiter *cloudprovider.ResourceLimiter, cp cloudprovider.CloudProvider, timestamp time.Time) scaleDownResourcesLimits {
totalCores, totalMem := calculateCoresAndMemoryTotal(nodes, timestamp)
var totalGpus map[string]int64
var totalGpusErr error
if containsGpuResources(resourceLimiter.GetResources()) {
totalGpus, totalGpusErr = calculateGpusTotal(nodes, cp, timestamp)
}
resultScaleDownLimits := make(scaleDownResourcesLimits)
for _, resource := range resourceLimiter.GetResources() {
total := totals[resource]
min := resourceLimiter.GetMin(resource)
// we put only actual limits into final map. No entry means no limit.
if min > 0 {
if total > min {
resultScaleDownLimits[resource] = total - min
switch {
case resource == cloudprovider.ResourceNameCores:
resultScaleDownLimits[resource] = computeLeft(totalCores, min)
case resource == cloudprovider.ResourceNameMemory:
resultScaleDownLimits[resource] = computeLeft(totalMem, min)
case cloudprovider.IsGpuResource(resource):
if totalGpusErr != nil {
resultScaleDownLimits[resource] = limitUnknown
} else {
resultScaleDownLimits[resource] = 0
resultScaleDownLimits[resource] = computeLeft(totalGpus[resource], min)
}
default:
glog.Errorf("Scale down limits defined for unsupported resource '%s'", resource)
}
}
}
return resultScaleDownLimits
}
func containsGpuResources(resources []string) bool {
for _, resource := range resources {
if cloudprovider.IsGpuResource(resource) {
return true
}
}
return false
}
func computeLeft(total int64, min int64) int64 {
if total > min {
return total - min
}
return 0
}
func calculateCoresAndMemoryTotal(nodes []*apiv1.Node, timestamp time.Time) (int64, int64) {
var coresTotal, memoryTotal int64
for _, node := range nodes {
@ -146,6 +177,60 @@ func calculateCoresAndMemoryTotal(nodes []*apiv1.Node, timestamp time.Time) (int
return coresTotal, memoryTotal
}
func calculateGpusTotal(nodes []*apiv1.Node, cp cloudprovider.CloudProvider, timestamp time.Time) (map[string]int64, error) {
type gpuInfo struct {
name string
count int64
}
result := make(map[string]int64)
ngCache := make(map[string]gpuInfo)
for _, node := range nodes {
if isNodeBeingDeleted(node, timestamp) {
// Nodes being deleted do not count towards total cluster resources
continue
}
nodeGroup, err := cp.NodeGroupForNode(node)
if err != nil {
return nil, errors.ToAutoscalerError(errors.CloudProviderError, err).AddPrefix("can not get node group for node %v when calculating cluster gpu usage", node.Name)
}
if reflect.ValueOf(nodeGroup).IsNil() {
// We do not trust cloud providers to return properly constructed nil for interface type - hence the reflection check.
// See https://golang.org/doc/faq#nil_error
// TODO[lukaszos] consider creating cloud_provider sanitizer which will wrap cloud provider and ensure sane behaviour.
nodeGroup = nil
}
var gpuType string
var gpuCount int64
var cached gpuInfo
var cacheHit bool
if nodeGroup != nil {
cached, cacheHit = ngCache[nodeGroup.Id()]
if cacheHit {
gpuType = cached.name
gpuCount = cached.count
}
}
if !cacheHit {
gpuType, gpuCount, err = gpu.GetNodeTargetGpus(node, nodeGroup)
if err != nil {
return nil, errors.ToAutoscalerError(errors.CloudProviderError, err).AddPrefix("can not get gpu count for node %v when calculating cluster gpu usage")
}
if nodeGroup != nil {
ngCache[nodeGroup.Id()] = gpuInfo{name: gpuType, count: gpuCount}
}
}
if gpuType == "" || gpuCount == 0 {
continue
}
result[gpuType] += gpuCount
}
return result, nil
}
func isNodeBeingDeleted(node *apiv1.Node, timestamp time.Time) bool {
deleteTime, _ := deletetaint.GetToBeDeletedTime(node)
return deleteTime != nil && (timestamp.Sub(*deleteTime) < MaxCloudProviderNodeDeletionTime || timestamp.Sub(*deleteTime) < MaxKubernetesEmptyNodeDeletionTime)
@ -163,13 +248,21 @@ func copyScaleDownResourcesLimits(source scaleDownResourcesLimits) scaleDownReso
return copy
}
func computeScaleDownResourcesDelta(node *apiv1.Node) (scaleDownResourcesDelta, errors.AutoscalerError) {
nodeCPU, nodeMemory := getNodeCoresAndMemory(node)
func computeScaleDownResourcesDelta(node *apiv1.Node, nodeGroup cloudprovider.NodeGroup, resourcesWithLimits []string) (scaleDownResourcesDelta, errors.AutoscalerError) {
resultScaleDownDelta := make(scaleDownResourcesDelta)
return scaleDownResourcesDelta{
cloudprovider.ResourceNameCores: nodeCPU,
cloudprovider.ResourceNameMemory: nodeMemory,
}, nil
nodeCPU, nodeMemory := getNodeCoresAndMemory(node)
resultScaleDownDelta[cloudprovider.ResourceNameCores] = nodeCPU
resultScaleDownDelta[cloudprovider.ResourceNameMemory] = nodeMemory
if containsGpuResources(resourcesWithLimits) {
gpuType, gpuCount, err := gpu.GetNodeTargetGpus(node, nodeGroup)
if err != nil {
return scaleDownResourcesDelta{}, errors.ToAutoscalerError(errors.CloudProviderError, err).AddPrefix("Failed to get node %v gpu: %v", node.Name)
}
resultScaleDownDelta[gpuType] = gpuCount
}
return resultScaleDownDelta, nil
}
type limitCheckResult struct {
@ -490,9 +583,10 @@ func (sd *ScaleDown) TryToScaleDown(allNodes []*apiv1.Node, pods []*apiv1.Pod, p
errCP)
}
scaleDownResourcesLeft := computeScaleDownResourcesLeftLimits(nodesWithoutMaster, resourceLimiter, currentTime)
scaleDownResourcesLeft := computeScaleDownResourcesLeftLimits(nodesWithoutMaster, resourceLimiter, sd.context.CloudProvider, currentTime)
nodeGroupSize := getNodeGroupSizeMap(sd.context.CloudProvider)
resourcesWithLimits := resourceLimiter.GetResources()
for _, node := range nodesWithoutMaster {
if val, found := sd.unneededNodes[node.Name]; found {
@ -538,7 +632,7 @@ func (sd *ScaleDown) TryToScaleDown(allNodes []*apiv1.Node, pods []*apiv1.Pod, p
continue
}
scaleDownResourcesDelta, err := computeScaleDownResourcesDelta(node)
scaleDownResourcesDelta, err := computeScaleDownResourcesDelta(node, nodeGroup, resourcesWithLimits)
if err != nil {
glog.Errorf("Error getting node resources: %v", err)
continue
@ -651,6 +745,8 @@ func getEmptyNodes(candidates []*apiv1.Node, pods []*apiv1.Pod, maxEmptyBulkDele
availabilityMap := make(map[string]int)
result := make([]*apiv1.Node, 0)
resourcesLimitsCopy := copyScaleDownResourcesLimits(resourcesLimits) // we do not want to modify input parameter
resourcesNames := sets.StringKeySet(resourcesLimits).List()
for _, node := range emptyNodes {
nodeGroup, err := cloudProvider.NodeGroupForNode(node)
if err != nil {
@ -676,7 +772,7 @@ func getEmptyNodes(candidates []*apiv1.Node, pods []*apiv1.Pod, maxEmptyBulkDele
availabilityMap[nodeGroup.Id()] = available
}
if available > 0 {
resourcesDelta, err := computeScaleDownResourcesDelta(node)
resourcesDelta, err := computeScaleDownResourcesDelta(node, nodeGroup, resourcesNames)
if err != nil {
glog.Errorf("Error: %v", err)
continue

38
cluster-autoscaler/core/scale_down_test.go
View File

@ -28,7 +28,6 @@ import (
"k8s.io/apimachinery/pkg/api/errors"
metav1 "k8s.io/apimachinery/pkg/apis/meta/v1"
"k8s.io/apimachinery/pkg/runtime"
"k8s.io/autoscaler/cluster-autoscaler/cloudprovider"
testprovider "k8s.io/autoscaler/cluster-autoscaler/cloudprovider/test"
"k8s.io/autoscaler/cluster-autoscaler/clusterstate"
"k8s.io/autoscaler/cluster-autoscaler/clusterstate/utils"
@ -47,6 +46,7 @@ import (
"github.com/golang/glog"
"github.com/stretchr/testify/assert"
"k8s.io/autoscaler/cluster-autoscaler/utils/deletetaint"
"k8s.io/autoscaler/cluster-autoscaler/utils/gpu"
)
func TestFindUnneededNodes(t *testing.T) {
@ -925,6 +925,35 @@ func TestScaleDownEmptyMinMemoryLimitHit(t *testing.T) {
simpleScaleDownEmpty(t, config)
}
func TestScaleDownEmptyMinGpuLimitHit(t *testing.T) {
options := defaultScaleDownOptions
options.GpuTotal = []context.GpuLimits{
{
GpuType: gpu.DefaultGPUType,
Min: 4,
Max: 50,
},
{
GpuType: "nvidia-tesla-p100", // this one should not trigger
Min: 5,
Max: 50,
},
}
config := &scaleTestConfig{
nodes: []nodeConfig{
{"n1", 1000, 1000 * MB, 1, true, "ng1"},
{"n2", 1000, 1000 * MB, 1, true, "ng1"},
{"n3", 1000, 1000 * MB, 1, true, "ng1"},
{"n4", 1000, 1000 * MB, 1, true, "ng1"},
{"n5", 1000, 1000 * MB, 1, true, "ng1"},
{"n6", 1000, 1000 * MB, 1, true, "ng1"},
},
options: options,
expectedScaleDowns: []string{"n1", "n2"},
}
simpleScaleDownEmpty(t, config)
}
func TestScaleDownEmptyMinGroupSizeLimitHit(t *testing.T) {
options := defaultScaleDownOptions
config := &scaleTestConfig{
@ -946,6 +975,9 @@ func simpleScaleDownEmpty(t *testing.T, config *scaleTestConfig) {
groups := make(map[string][]*apiv1.Node)
for i, n := range config.nodes {
node := BuildTestNode(n.name, n.cpu, n.memory)
if n.gpu > 0 {
AddGpusToNode(node, n.gpu)
}
SetNodeReadyState(node, n.ready, time.Time{})
nodesMap[n.name] = node
nodes[i] = node
@ -985,9 +1017,7 @@ func simpleScaleDownEmpty(t *testing.T, config *scaleTestConfig) {
}
}
resourceLimiter := cloudprovider.NewResourceLimiter(
map[string]int64{cloudprovider.ResourceNameCores: config.options.MinCoresTotal, cloudprovider.ResourceNameMemory: config.options.MinMemoryTotal},
map[string]int64{cloudprovider.ResourceNameCores: config.options.MaxCoresTotal, cloudprovider.ResourceNameMemory: config.options.MaxMemoryTotal})
resourceLimiter := context.NewResourceLimiterFromAutoscalingOptions(config.options)
provider.SetResourceLimiter(resourceLimiter)
assert.NotNil(t, provider)

50
cluster-autoscaler/main.go
View File

@ -113,6 +113,7 @@ var (
maxNodesTotal = flag.Int("max-nodes-total", 0, "Maximum number of nodes in all node groups. Cluster autoscaler will not grow the cluster beyond this number.")
coresTotal = flag.String("cores-total", minMaxFlagString(0, config.DefaultMaxClusterCores), "Minimum and maximum number of cores in cluster, in the format <min>:<max>. Cluster autoscaler will not scale the cluster beyond these numbers.")
memoryTotal = flag.String("memory-total", minMaxFlagString(0, config.DefaultMaxClusterMemory), "Minimum and maximum number of gigabytes of memory in cluster, in the format <min>:<max>. Cluster autoscaler will not scale the cluster beyond these numbers.")
gpuTotal = multiStringFlag("gpu-total", "Minimum and maximum number of different GPUs in cluster, in the format <gpu_type>:<min>:<max>. Cluster autoscaler will not scale the cluster beyond these numbers. Can be passed multiple times. CURRENTLY THIS FLAG ONLY WORKS ON GKE.")
cloudProviderFlag = flag.String("cloud-provider", cloudBuilder.DefaultCloudProvider,
"Cloud provider type. Available values: ["+strings.Join(cloudBuilder.AvailableCloudProviders, ",")+"]")
maxEmptyBulkDeleteFlag = flag.Int("max-empty-bulk-delete", 10, "Maximum number of empty nodes that can be deleted at the same time.")
@ -161,6 +162,11 @@ func createAutoscalingOptions() context.AutoscalingOptions {
minMemoryTotal = minMemoryTotal * units.Gigabyte
maxMemoryTotal = maxMemoryTotal * units.Gigabyte
parsedGpuTotal, err := parseMultipleGpuLimits(*gpuTotal)
if err != nil {
glog.Fatalf("Failed to parse flags: %v", err)
}
return context.AutoscalingOptions{
CloudConfig: *cloudConfig,
CloudProviderName: *cloudProviderFlag,
@ -177,6 +183,7 @@ func createAutoscalingOptions() context.AutoscalingOptions {
MinCoresTotal: minCoresTotal,
MaxMemoryTotal: maxMemoryTotal,
MinMemoryTotal: minMemoryTotal,
GpuTotal: parsedGpuTotal,
NodeGroups: *nodeGroupsFlag,
ScaleDownDelayAfterAdd: *scaleDownDelayAfterAdd,
ScaleDownDelayAfterDelete: *scaleDownDelayAfterDelete,
@ -445,3 +452,46 @@ func validateMinMaxFlag(min, max int64) error {
func minMaxFlagString(min, max int64) string {
return fmt.Sprintf("%v:%v", min, max)
}
func parseMultipleGpuLimits(flags MultiStringFlag) ([]context.GpuLimits, error) {
parsedFlags := make([]context.GpuLimits, 0, len(flags))
for _, flag := range flags {
parsedFlag, err := parseSingleGpuLimit(flag)
if err != nil {
return nil, err
}
parsedFlags = append(parsedFlags, parsedFlag)
}
return parsedFlags, nil
}
func parseSingleGpuLimit(config string) (context.GpuLimits, error) {
parts := strings.Split(config, ":")
if len(parts) != 3 {
return context.GpuLimits{}, fmt.Errorf("Incorrect gpu limit specification: %v", config)
}
gpuType := parts[0]
minVal, err := strconv.ParseInt(parts[1], 10, 64)
if err != nil {
return context.GpuLimits{}, fmt.Errorf("Incorrect gpu limit - min is not integer: %v", config)
}
maxVal, err := strconv.ParseInt(parts[2], 10, 64)
if err != nil {
return context.GpuLimits{}, fmt.Errorf("Incorrect gpu limit - max is not integer: %v", config)
}
if minVal < 0 {
return context.GpuLimits{}, fmt.Errorf("Incorrect gpu limit - min is less than 0; %v", config)
}
if maxVal < 0 {
return context.GpuLimits{}, fmt.Errorf("Incorrect gpu limit - max is less than 0; %v", config)
}
if minVal > maxVal {
return context.GpuLimits{}, fmt.Errorf("Incorrect gpu limit - min is greater than max; %v", config)
}
parsedGpuLimits := context.GpuLimits{
GpuType: gpuType,
Min: minVal,
Max: maxVal,
}
return parsedGpuLimits, nil
}

91
cluster-autoscaler/main_test.go Normal file
View File

@ -0,0 +1,91 @@
/*
Copyright 2018 The Kubernetes Authors.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
package main
import (
"github.com/stretchr/testify/assert"
"k8s.io/autoscaler/cluster-autoscaler/context"
"testing"
)
func TestParseSingleGpuLimit(t *testing.T) {
type testcase struct {
input string
expectError bool
expectedLimits context.GpuLimits
expectedErrorMessage string
}
testcases := []testcase{
{
input: "gpu:1:10",
expectError: false,
expectedLimits: context.GpuLimits{
GpuType: "gpu",
Min: 1,
Max: 10,
},
},
{
input: "gpu:1",
expectError: true,
expectedErrorMessage: "Incorrect gpu limit specification: gpu:1",
},
{
input: "gpu:1:10:x",
expectError: true,
expectedErrorMessage: "Incorrect gpu limit specification: gpu:1:10:x",
},
{
input: "gpu:x:10",
expectError: true,
expectedErrorMessage: "Incorrect gpu limit - min is not integer: gpu:x:10",
},
{
input: "gpu:1:y",
expectError: true,
expectedErrorMessage: "Incorrect gpu limit - max is not integer: gpu:1:y",
},
{
input: "gpu:-1:10",
expectError: true,
expectedErrorMessage: "Incorrect gpu limit - min is less than 0; gpu:-1:10",
},
{
input: "gpu:1:-10",
expectError: true,
expectedErrorMessage: "Incorrect gpu limit - max is less than 0; gpu:1:-10",
},
{
input: "gpu:10:1",
expectError: true,
expectedErrorMessage: "Incorrect gpu limit - min is greater than max; gpu:10:1",
},
}
for _, testcase := range testcases {
limits, err := parseSingleGpuLimit(testcase.input)
if testcase.expectError {
assert.NotNil(t, err)
if err != nil {
assert.Equal(t, testcase.expectedErrorMessage, err.Error())
}
} else {
assert.Equal(t, testcase.expectedLimits, limits)
}
}
}

46
cluster-autoscaler/utils/gpu/gpu.go
View File

@ -19,8 +19,10 @@ package gpu
import (
apiv1 "k8s.io/api/core/v1"
"k8s.io/apimachinery/pkg/api/resource"
"k8s.io/autoscaler/cluster-autoscaler/cloudprovider"
"github.com/golang/glog"
"k8s.io/autoscaler/cluster-autoscaler/utils/errors"
)
const (
@ -156,3 +158,47 @@ func GetGpuRequests(pods []*apiv1.Pod) map[string]GpuRequestInfo {
}
return result
}
// GetNodeTargetGpus returns the number of gpus on a given node. This includes gpus which are not yet
// ready to use and visible in kubernetes.
func GetNodeTargetGpus(node *apiv1.Node, nodeGroup cloudprovider.NodeGroup) (gpuType string, gpuCount int64, err error) {
gpuLabel, found := node.Labels[GPULabel]
if !found {
return "", 0, nil
}
gpuAllocatable, found := node.Status.Allocatable[ResourceNvidiaGPU]
if found && gpuAllocatable.Value() > 0 {
return gpuLabel, gpuAllocatable.Value(), nil
}
// A node is supposed to have GPUs (based on label), but they're not available yet
// (driver haven't installed yet?).
// Unfortunately we can't deduce how many GPUs it will actually have from labels (just
// that it will have some).
// Ready for some evil hacks? Well, you won't be disappointed - let's pretend we haven't
// seen the node and just use the template we use for scale from 0. It'll be our little
// secret.
if nodeGroup == nil {
// We expect this code path to be triggered by situation when we are looking at a node which is expected to have gpus (has gpu label)
// But those are not yet visible in node's resource (e.g. gpu drivers are still being installed).
// In case of node coming from autoscaled node group we would look and node group template here.
// But for nodes coming from non-autoscaled groups we have no such possibility.
// Let's hope it is a transient error. As long as it exists we will not scale nodes groups with gpus.
return "", 0, errors.NewAutoscalerError(errors.InternalError, "node without with gpu label, without capacity not belonging to autoscaled node group")
}
template, err := nodeGroup.TemplateNodeInfo()
if err != nil {
glog.Errorf("Failed to build template for getting GPU estimation for node %v: %v", node.Name, err)
return "", 0, errors.ToAutoscalerError(errors.CloudProviderError, err)
}
if gpuCapacity, found := template.Node().Status.Capacity[ResourceNvidiaGPU]; found {
return gpuLabel, gpuCapacity.Value(), nil
}
// if template does not define gpus we assume node will not have any even if ith has gpu label
glog.Warningf("Template does not define gpus even though node from its node group does; node=%v", node.Name)
return "", 0, nil
}