HAMI vGPU Principle Analysis Part 2: hami-webhook Principle Analysis

In the last article, we analyzed hami-device-plugin-nvidia and understood how HAMI's NVIDIA device plugin works.

Previous article: "HAMI vGPU Solution Principle Analysis Part 1: hami-device-plugin-nvidia Implementation"

This is the second article in the HAMI principle analysis series, analyzing the implementation of hami-scheduler.

To achieve vGPU-based scheduling, HAMI implements its own scheduler: hami-scheduler. In addition to basic scheduling logic, it also includes advanced scheduling strategies like spread & binpack.

This raises several key questions:

  1. How do Pods get scheduled by hami-scheduler? When creating a Pod without specifying a SchedulerName, it should be scheduled by the default-scheduler.
  2. What is the logic of hami-scheduler, and how are advanced scheduling strategies like spread & binpack implemented?

Due to the amount of content, this topic will be split into three articles: hami-webhook, hami-scheduler, and the Spread & Binpack scheduling strategy. This article will focus on answering the first question.

The following analysis is based on HAMI v2.4.0.

1. hami-scheduler Startup Command

The hami-scheduler actually consists of two components:

  • hami-webhook
  • hami-scheduler

Although they are two components, their code is located together. The startup file is cmd/scheduler/main.go:

This is a command-line tool implemented using the Cobra library.

var (
 sher        *scheduler.Scheduler
 tlsKeyFile  string
 tlsCertFile string
 rootCmd     = &cobra.Command{
  Use:   "scheduler",
  Short: "kubernetes vgpu scheduler",
  Run: func(cmd *cobra.Command, args []string) {
   start()
  },
 }
)

func main() {
 if err := rootCmd.Execute(); err != nil {
  klog.Fatal(err)
 }
}

The start method that is ultimately called is as follows:

func start() {
 // Initialize GPU inventory
 device.InitDevices()

 // Build and start the scheduler
 sher = scheduler.NewScheduler()
 sher.Start()
 defer sher.Stop()

 // Background goroutines
 go sher.RegisterFromNodeAnnotations()     // Sync node GPU annotations
 go initMetrics(config.MetricsBindAddress) // Prometheus metrics

 // HTTP routes
 router := httprouter.New()
 router.POST("/filter",  routes.PredicateRoute(sher))
 router.POST("/bind",    routes.Bind(sher))
 router.POST("/webhook", routes.WebHookRoute())
 router.GET("/healthz",  routes.HealthzRoute())

 // Start server (plain or TLS)
 klog.Info("listen on ", config.HTTPBind)
 if len(tlsCertFile) == 0 || len(tlsKeyFile) == 0 {
  if err := http.ListenAndServe(config.HTTPBind, router); err != nil {
   klog.Fatal("Listen and Serve error, ", err)
  }
 } else {
  if err := http.ListenAndServeTLS(config.HTTPBind, tlsCertFile, tlsKeyFile, router); err != nil {
   klog.Fatal("Listen and Serve error, ", err)
  }
 }
}

First, it initializes the devices.

This will be used by the Webhook later, we'll look at it in a moment.

// device.InitDevices() scans local GPU devices via NVML,
// parses node annotations, and builds the in-memory inventory.
device.InitDevices()

Then it starts the Scheduler.

sher = scheduler.NewScheduler() // create scheduler instance
sher.Start()                  // start scheduling loop
defer sher.Stop()             // graceful shutdown on exit```

Next, it starts a Goroutine to continuously parse GPU information from the Annotations that the device plugin previously added to the Node objects.

```go
// background goroutine: continuously syncs GPU inventory
// from Node annotations into the scheduler cache
go sher.RegisterFromNodeAnnotations()

Finally, it starts an HTTP service.

router := httprouter.New()
router.POST("/filter",  routes.PredicateRoute(sher)) // scheduler predicate plugin
router.POST("/bind",    routes.Bind(sher))           // scheduler bind plugin
router.POST("/webhook", routes.WebHookRoute())       // mutating/validating webhook
router.GET("/healthz",  routes.HealthzRoute())       // liveness probe

Here:

  • /webhook is the Webhook component.
  • /filter and /bind are the Scheduler components.
  • /healthz is used for health checks.

Next, we will analyze the implementation of the Webhook and Scheduler through the source code.

2. hami-webhook

The Webhook here is a Mutating Webhook, primarily serving the Scheduler.

Its core function is: To determine if a Pod is using HAMI vGPU based on the ResourceName in the Pod's Resource field. If so, it modifies the Pod's SchedulerName to hami-scheduler so that it can be scheduled by hami-scheduler. Otherwise, it does nothing.

MutatingWebhookConfiguration

To make the Webhook effective, HAMI creates a MutatingWebhookConfiguration object during deployment. The content is as follows:

apiVersion: admissionregistration.k8s.io/v1
kind: MutatingWebhookConfiguration
metadata:
  annotations:
    meta.helm.sh/release-name: vgpu
    meta.helm.sh/release-namespace: kube-system
  labels:
    app.kubernetes.io/managed-by: Helm
  name: vgpu-hami-webhook
webhooks:
- admissionReviewVersions:
  - v1beta1
  clientConfig:
    caBundle: xxx
    service:
      name: vgpu-hami-scheduler
      namespace: kube-system
      path: /webhook
      port: 443
  failurePolicy: Ignore
  matchPolicy: Equivalent
  name: vgpu.hami.io
  namespaceSelector:
    matchExpressions:
    - key: hami.io/webhook
      operator: NotIn
      values:
      - ignore
  objectSelector:
    matchExpressions:
    - key: hami.io/webhook
      operator: NotIn
      values:
      - ignore
  reinvocationPolicy: Never
  rules:
  - apiGroups:
    - ""
    apiVersions:
    - v1
    operations:
    - CREATE
    resources:
    - pods
    scope: '*'
  sideEffects: None
  timeoutSeconds: 10

The effect is that when a Pod is created, the kube-apiserver will call the webhook corresponding to this service, thus injecting our custom logic.

It targets the CREATE event for Pods:

rules:
- apiGroups:
  - ""
  apiVersions:
  - v1
  operations:
  - CREATE
  resources:
  - pods
  scope: '*'

However, it excludes the following objects:

namespaceSelector:
  matchExpressions:
  - key: hami.io/webhook
    operator: NotIn
    values:
    - ignore
objectSelector:
  matchExpressions:
  - key: hami.io/webhook
    operator: NotIn
    values:
    - ignore

This means that any namespace or resource object with the label hami.io/webhook=ignore will not trigger this Webhook logic.

The requested Webhook is:

service:
  name: vgpu-hami-scheduler
  namespace: kube-system
  path: /webhook
  port: 443

This means that for a CREATE event on a matching Pod, the kube-apiserver will call the service specified, which is our hami-webhook.

Now let's analyze what hami-webhook actually does.

Source Code Analysis

The specific implementation of this Webhook is as follows:

// pkg/scheduler/webhook.go#L52
func (h *webhook) Handle(_ context.Context, req admission.Request) admission.Response {
 pod := &corev1.Pod{}
 if err := h.decoder.Decode(req, pod); err != nil {
  klog.Errorf("Failed to decode request: %v", err)
  return admission.Errored(http.StatusBadRequest, err)
 }
 if len(pod.Spec.Containers) == 0 {
  klog.Warningf(template+" - Denying admission as pod has no containers", req.Namespace, req.Name, req.UID)
  return admission.Denied("pod has no containers")
 }

 klog.Infof(template, req.Namespace, req.Name, req.UID)
 hasResource := false
 for idx, ctr := range pod.Spec.Containers {
  c := &pod.Spec.Containers[idx]
  if ctr.SecurityContext != nil && ctr.SecurityContext.Privileged != nil && *ctr.SecurityContext.Privileged {
   klog.Warningf(template+" - Denying admission as container %s is privileged", req.Namespace, req.Name, req.UID, c.Name)
   continue
  }
  for _, val := range device.GetDevices() {
   found, err := val.MutateAdmission(c)
   if err != nil {
    klog.Errorf("validating pod failed:%s", err.Error())
    return admission.Errored(http.StatusInternalServerError, err)
   }
   hasResource = hasResource || found
  }
 }

 if !hasResource {
  klog.Infof(template+" - Allowing admission for pod: no resource found", req.Namespace, req.Name, req.UID)
 } else if len(config.SchedulerName) > 0 {
  pod.Spec.SchedulerName = config.SchedulerName
 }

 marshaledPod, err := json.Marshal(pod)
 if err != nil {
  klog.Errorf(template+" - Failed to marshal pod, error: %v", req.Namespace, req.Name, req.UID, err)
  return admission.Errored(http.StatusInternalServerError, err)
 }
 return admission.PatchResponseFromRaw(req.Object.Raw, marshaledPod)
}

The logic is quite simple:

  1. Determine if the Pod needs to be scheduled by hami-scheduler.
  2. If it does, change the Pod's SchedulerName field to hami-scheduler (the name is configurable).

So, the core question is: how does it determine if the Pod needs to be scheduled by hami-scheduler?

How to Determine if hami-scheduler Should Be Used

The Webhook mainly determines this based on whether the Pod requests vGPU resources, but there are some special cases.

Privileged Pods

First, HAMI ignores privileged Pods directly.

if ctr.SecurityContext != nil {
 if ctr.SecurityContext.Privileged != nil && *ctr.SecurityContext.Privileged {
  klog.Warningf(template+" - Denying admission as container %s is privileged", req.Namespace, req.Name, req.UID, c.Name)
  continue
 }
}

This is because when privileged mode is enabled, the Pod can access all devices on the host, making restrictions meaningless. Therefore, it is ignored here.

Specific Judgment Logic

Then, it determines whether to use hami-scheduler based on the resources in the Pod:

for _, val := range device.GetDevices() {
 found, err := val.MutateAdmission(c)
 if err != nil {
  klog.Errorf("validating pod failed:%s", err.Error())
  return admission.Errored(http.StatusInternalServerError, err)
 }
 hasResource = hasResource || found
}

If the Pod's resources request a vGPU resource supported by HAMI, then it needs to be scheduled by hami-scheduler.

And which devices does HAMI support? These are the ones initialized in the start function:

var devices map[string]Devices

func GetDevices() map[string]Devices {
 return devices
}

func InitDevices() {
 devices = make(map[string]Devices)
 DevicesToHandle = []string{}

 devices[cambricon.CambriconMLUDevice] = cambricon.InitMLUDevice()
 devices[nvidia.NvidiaGPUDevice]       = nvidia.InitNvidiaDevice()
 devices[hygon.HygonDCUDevice]         = hygon.InitDCUDevice()
 devices[iluvatar.IluvatarGPUDevice]   = iluvatar.InitIluvatarDevice()

 DevicesToHandle = append(DevicesToHandle,
  nvidia.NvidiaGPUCommonWord,
  cambricon.CambriconMLUCommonWord,
  hygon.HygonDCUCommonWord,
  iluvatar.IluvatarGPUCommonWord,
 )

 for _, dev := range ascend.InitDevices() {
  devices[dev.CommonWord()] = dev
  DevicesToHandle = append(DevicesToHandle, dev.CommonWord())
 }
}

devices is a global variable, and InitDevices initializes it for use by the Webhook, including support for NVIDIA, Hygon, Iluvatar, Ascend, etc.

Let's take NVIDIA as an example to explain how HAMI determines if a Pod needs its scheduling. The MutateAdmission implementation is as follows:

func (dev *NvidiaGPUDevices) MutateAdmission(ctr *corev1.Container) (bool, error) {
 // GPU-related mutations
 if priority, ok := ctr.Resources.Limits[corev1.ResourceName(ResourcePriority)]; ok {
  ctr.Env = append(ctr.Env, corev1.EnvVar{
   Name:  api.TaskPriority,
   Value: fmt.Sprint(priority.Value()),
  })
 }

 _, resourceNameOK := ctr.Resources.Limits[corev1.ResourceName(ResourceName)]
 if resourceNameOK {
  return resourceNameOK, nil
 }

 _, resourceCoresOK := ctr.Resources.Limits[corev1.ResourceName(ResourceCores)]
 _, resourceMemOK := ctr.Resources.Limits[corev1.ResourceName(ResourceMem)]
 _, resourceMemPercentageOK := ctr.Resources.Limits[corev1.ResourceName(ResourceMemPercentage)]

 if resourceCoresOK || resourceMemOK || resourceMemPercentageOK {
  if config.DefaultResourceNum > 0 {
   ctr.Resources.Limits[corev1.ResourceName(ResourceName)] =
    *resource.NewQuantity(int64(config.DefaultResourceNum), resource.BinarySI)
   resourceNameOK = true
  }
 }

 if !resourceNameOK && OverwriteEnv {
  ctr.Env = append(ctr.Env, corev1.EnvVar{
   Name:  "NVIDIA_VISIBLE_DEVICES",
   Value: "none",
  })
 }
 return resourceNameOK, nil
}

First, if the Pod's requested resources contain the corresponding ResourceName, it directly returns true.

_, resourceNameOK := ctr.Resources.Limits[corev1.ResourceName(ResourceName)]
if resourceNameOK {
 return resourceNameOK, nil
}

The corresponding ResourceName for NVIDIA GPUs is:

fs.StringVar(&ResourceName, "resource-name", "nvidia.com/gpu", "resource name")

If a Pod requests this resource in its Resource field, it needs to be scheduled by HAMI. The logic for other resources is similar.

HAMI supports GPUs from NVIDIA, Iluvatar, Huawei, Cambricon, Hygon, etc. The default ResourceNames are: nvidia.com/gpu, iluvatar.ai/vgpu, hygon.com/dcunum, cambricon.com/mlu, huawei.com/Ascend310, etc. Pods using these ResourceNames will be scheduled by hami-scheduler.
PS: These ResourceNames can be configured in the corresponding device plugins.

If the Pod does not directly request nvidia.com/gpu but requests resources like gpucore or gpumem, and the Webhook's DefaultResourceNum is greater than 0, it will also return true and automatically add the nvidia.com/gpu resource request.

_, resourceCoresOK := ctr.Resources.Limits[corev1.ResourceName(ResourceCores)]
_, resourceMemOK := ctr.Resources.Limits[corev1.ResourceName(ResourceMem)]
_, resourceMemPercentageOK := ctr.Resources.Limits[corev1.ResourceName(ResourceMemPercentage)]

if resourceCoresOK || resourceMemOK || resourceMemPercentageOK {
 if config.DefaultResourceNum > 0 {
  ctr.Resources.Limits[corev1.ResourceName(ResourceName)] =
   *resource.NewQuantity(int64(config.DefaultResourceNum), resource.BinarySI)
  resourceNameOK = true
 }
}

Modifying SchedulerName

For Pods that meet the above conditions, they need to be scheduled by hami-scheduler. The Webhook will change the Pod's spec.schedulerName to hami-scheduler.

The specific logic is as follows:

if !hasResource {
 klog.Infof(template+" - Allowing admission for pod: no resource found", req.Namespace, req.Name, req.UID)
} else if len(config.SchedulerName) > 0 {
 pod.Spec.SchedulerName = config.SchedulerName
}

This way, the Pod will be scheduled by hami-scheduler, and the hami-scheduler's work begins.

There is another special case: if nodeName is specified at creation time, the Webhook will reject the Pod. This is because specifying a nodeName means the Pod doesn't need scheduling and will be started directly on the specified node, but it hasn't gone through scheduling, so the node might not have sufficient resources.

if pod.Spec.NodeName != "" {
 klog.Infof(template+" - Pod already has node assigned", req.Namespace, req.Name, req.UID)
 return admission.Denied("pod has node assigned")
}

3. Summary

The purpose of this Webhook is: to change the scheduler for Pods requesting vGPU resources to hami-scheduler, which will then handle their scheduling.

There are also some special cases:

  • For privileged Pods, the Webhook will ignore them and will not switch them to be scheduled by hami-scheduler; they will still use the default-scheduler.
  • For Pods that directly specify a nodeName, the Webhook will reject and block the Pod's creation.

Based on these special cases, the following issue, which has been reported multiple times in the community, may occur:

A privileged Pod requests gpucore and gpumem resources, but after creation, it remains in a Pending state and cannot be scheduled, with an error indicating that no node has gpucore or gpumem resources.

This is because the Webhook skips privileged Pods, so the Pod is handled by the default-scheduler. The default-scheduler checks the Pod's ResourceName and finds that no Node has gpucore or gpumem resources, so it cannot be scheduled, and the Pod remains in a Pending state.

PS: gpucore and gpumem are virtual resources and are not advertised on the Node object itself; only hami-scheduler can handle them.

HAMI Webhook Workflow

  1. A user creates a Pod and requests vGPU resources in it.
  2. Based on the MutatingWebhookConfiguration, the kube-apiserver sends a request to the HAMI-Webhook.
  3. The HAMI-Webhook inspects the Pod's resources, finds that it is requesting a vGPU resource managed by HAMI, and therefore changes the Pod's SchedulerName to hami-scheduler. This ensures the Pod will be scheduled by hami-scheduler.
    • For privileged Pods, the Webhook will skip them without any processing.
    • For Pods using vGPU resources but with a specified nodeName, the Webhook will reject them.
  4. Next, the process enters the hami-scheduler's scheduling logic, which we will analyze in the next article.

With this, we have clarified why and which Pods will be scheduled by hami-scheduler. This also explains why privileged Pods might fail to be scheduled.

The next article will begin the analysis of the hami-scheduler implementation.

To learn more about the HAMI project, please visit the GitHub repository or join our Slack community.

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