HAMi Enterprise 2.10.0-r1

The HAMi Enterprise 2.10 series improves shared compute-resource management, device support, and operations integrations. It introduces optional resource-pool management while retaining Enterprise GPU allocation management and GPU memory auto-expansion. v2.10.0-r1 also incorporates open-source HAMi dynamic MIG, combined GPU scheduling policies, init-container resource accounting, multi-device quota improvements, and stability fixes.

Version information

Item	Value
Enterprise release	HAMi Enterprise v2.10.0-r1
Release date	2026-08-28
Enterprise upgrade baseline	v2.9.0-r3 (the last release in the 2.9 series)
Open-source baseline	HAMi v2.10.0
Helm Chart	hami-enterprise, version 2.10.0-r1
Chart appVersion	2.10.0-r1
Default component image tag	v2.10.0-r1

Software changes

Changes compared with Enterprise v2.9.0-r3

Enterprise license management, NVIDIA GPU allocation management, GPU memory auto-expansion, and Alibaba PPU integration were already available in Enterprise 2.9 and remain available in this release.

Monitoring and collection improvements

• Adds workload information for compute-allocation mode, memory overcommit, and auto-expansion status to help platforms display resource configuration and feature enablement.
• Fixes metric attribution issues in some workloads containing init containers.
• Updates container-memory and MIG monitoring metrics. Review metrics and labels used by existing dashboards and alert rules; see “Configuration migration and platform integration.”

Device support and stability fixes

• Fixes mode matching for some Ascend vNPU workloads and improves memory-request handling.
• Fixes cleanup of residual data in scenarios such as task failures.
• Synchronizes open-source scheduling, device-support, quota, and concurrency improvements, including dynamic MIG and combined GPU scheduling policies. See “Upstream changes included in this release” and the referenced PRs.

Enterprise extensions compared with open-source HAMi v2.10.0

Resource-pool management (optional in the 2.10 series)

The 2.10 series introduces optional resource-pool management. It organizes device resources by team or business unit and configures the namespaces that can use each resource pool, helping manage compute-resource access in shared clusters.

Resource-pool management is disabled by default and is not enabled automatically when the v2.10.0-r1 main Chart is installed. Install and enable the companion components according to their deployment instructions.

Enterprise license management

• Manages licenses by device instance or device-model count to support deployments of different sizes.
• Provides license-validity status, remaining validity, and error events to help plan renewals and investigate issues.
• License coverage varies by device type; select the license plan that matches the deployment.

GPU resource usage and memory auto-expansion

• Provides Enterprise NVIDIA GPU allocation management with container-level device allocation and memory and compute limits.
• Supports adjusting memory limits as needed for NVIDIA GPU workloads with auto-expansion enabled, for example when memory demand grows at runtime.
• Expansion is constrained by remaining device memory and currently applies to regular workload containers, not init containers.

Heterogeneous devices and platform integration

• Provides resource scheduling, quota management, license integration, and deployment configuration for Alibaba PPU.
• AWS Neuron resource accounting and AMD device-type identifiers differ from the open-source baseline. Verify the relevant accounting semantics and type mappings when integrating with an existing resource-management platform.
• Adds Enterprise monitoring information for resource configuration, auto-expansion status, and license validity, and extends CDI integration settings for existing operations platforms and container runtimes.

Upstream changes included in this release

v2.10.0-r1 includes the following major open-source features and fixes. See the referenced PRs for background; Enterprise configuration requirements and differences are described in “Upgrade notes.”

Scheduling and resource allocation

Change	Impact on usage and integration	Upstream PR
Init-container resource accounting	Improves resource accounting and release for init and workload containers. The subsequent slot-count fix is not included; see “Known differences from the open-source baseline.”	#1773
GPU mutual-exclusion scheduling policy	Adds the mutex policy for exclusive GPU allocation.	#2011
Combined GPU scheduling policies	Combines multiple GPU scheduling policies and applies them in configured order.	#2621
PodGroup support	Improves scheduling retries for tasks in a group and supports Kubernetes SchedulingGroup recognition.	#2066, #2206
Scheduling evaluation on template nodes	Evaluates whether a task can be scheduled on a template node, providing a basis for integration with scale-up decisions. A complete autoscaling solution still requires separate integration.	#2046
NVIDIA NUMA information	Optionally provides vGPU NUMA topology information; disabled by default.	#2065
Dynamic MIG	Dynamically allocates and releases MIG instances based on task requirements and improves MIG profile management.	#2378
RTX PRO 6000 Blackwell MIG	Adds dynamic MIG support and profile configuration for this model.	#2135

Device support

Change	Impact on usage and integration	Upstream PR
AMD vGPU	Supports resource requests and allocation for AMD virtual devices.	#2290
Biren devices	Adds device recognition and scheduling support for Biren hardware.	#1711
Ascend hybrid-mode scheduling	Workloads without an explicit mode can match both vNPU-template and HAMi-core nodes.	#2035
Ascend 910C templates	Adds resource profiles such as vir05_1c_16g and vir10_3c_32g.	#2005
Ascend memory requests	Preserves the user-requested memory value instead of rounding it to a template value during parsing.	#2696

Quotas and stability

Change	Impact on usage and integration	Upstream PR
Zero quotas and quota updates	Treats an explicitly configured zero quota as zero capacity and improves limit handling after quota updates.	#2313, #2386
Multi-device quota checks	Improves quota validation across device backends, including Cambricon percentage-memory and full-card memory requests.	#2347, #2536
Release resources after scheduling failures	Fixes stale allocation records that could leave resources occupied after some scheduling failures.	#1927
Concurrent scheduling stability	Fixes data races when Pods and node information are processed concurrently.	#2055, #2472, #2333, #2504
Recover device scheduling	Fixes release of node locks for Cambricon devices to avoid affecting subsequent scheduling.	#2329
Read monitoring data	Improves handling of abnormal or unready data, reducing interference from unrelated files and invalid device information during collection.	#2529, #2503, #2465

Chart changes

Deployment and runtime integration

• Adds an installation setting for the Enterprise NVIDIA GPU allocation mode; the default behavior is unchanged and can be configured for the deployment.
• Extends CDI configuration to support a custom device-identifier prefix and improves dynamic MIG device integration.
• Completes PPU scheduling resource configuration to improve deployment integration for the existing PPU capability.
• Improves deployment health checks so abnormal tasks in other namespaces do not affect the check.

Upstream installation-configuration changes

Change	Impact on usage and integration	Upstream PR
Device Plugin security configuration	Configures the Device Plugin security context through Helm values to fit cluster security policies.	#1887
Custom device configuration	Provides a complete device configuration through device-config.content for consistent management by integrators.	#2277

Upgrade notes

Packages and component selection

Obtain the Helm package, component images, and component manifest for this release through the agreed delivery channel. Use the companion delivery manifest when deploying and recording software versions.

When introducing resource pools, plan resource access by team or business unit and deploy the companion components.

Configuration migration and platform integration

• Custom device configuration: device-config.content replaces the entire default device configuration; it does not merge individual fields. If you use this setting or a custom device-configuration file in the Chart, maintain the Enterprise device options required by your deployment.
• Monitoring integrations: When upgrading from Enterprise 2.9, hami_container_device_memory_bytes no longer has the context_size, module_size, buffer_size, and offset labels. Use the corresponding hami_vgpu_memory_*_bytes metrics for memory breakdowns. Labels on hami_mig_device_info have also changed; update dashboards and alert rules that use the old labels. When integrating AMD or AWS Neuron, also verify Enterprise device-type mappings and accounting semantics.
• Optional features: NVIDIA NUMA topology information is disabled by default and can be enabled with devicePlugin.enableNumaTopology as needed. GPU memory auto-expansion must be enabled for the relevant workload, and sufficient allocatable memory must be available.
• Ascend runtime environment: Enterprise HAMi-core runtime startup requirements differ from the open-source version. Use the Enterprise companion runtime and configuration for deployment. See upstream change #2062.
• DRA integration: Enterprise retains an optional DRA component, disabled by default. Open-source HAMi has removed that component from its main Chart, so its installation layout cannot be copied directly. See upstream change #2038.

Known differences from the open-source baseline

The following open-source v2.10.0 features and fixes are not included in Enterprise v2.10.0-r1; account for these limitations when integrating.

Scenario	Limitation in this release	Upstream PR
Device requests from init containers	Init-container resource accounting is supported, but the subsequent device-slot-count fix is not included.	#2623
Stop assigning new tasks to one GPU	Does not yet include dynamic blocking of new allocations to an individual GPU through hami.io/device-cordon.	#2298
Quota monitoring	Does not provide a separate hami_resource_quota_limit metric. Monitoring rules should not depend on it.	#2715
Device count becomes zero	Does not yet include the fix that clears stale device information when a device reports zero. Check whether displayed resources match actual device state.	#2550
Invalid scheduling API requests	Does not yet include validation for Filter requests that lack Pod information. Integrators should ensure requests are complete.	#2689

See the Chart and appVersion mapping or the software center.

Values reference

The following parameter descriptions are taken from the README bundled with the Chart 2.10.0-r1 release package and are preserved as published. Use this version's values.yaml as the source of default configuration.

Expand values table

Key	Type	Default	Description
birenResourceName	string	"birentech.com/gpu"	Biren GPU resource name
dcuResourceCores	string	"hygon.com/dcucores"	Hygon DCU cores resource name
dcuResourceMem	string	"hygon.com/dcumem"	Hygon DCU memory resource name
dcuResourceName	string	"hygon.com/dcunum"	Hygon DCU resource name
device-config.content	string	""
devicePlugin.cdiVendor	string	""	CDI vendor for generated specs and device annotations (default: k8s.device-plugin.nvidia.com)
devicePlugin.createRuntimeClass	bool	false	Whether to create runtime class
devicePlugin.deviceCoreScaling	int	1	Device core scaling factor
devicePlugin.deviceListStrategy	string	"envvar"	Device list strategy. Supported values: envvar, volume-mounts, cdi-annotations
devicePlugin.deviceMemoryScaling	int	1	Device memory scaling factor
devicePlugin.deviceSplitCount	int	10	Number of slices to split each GPU into
devicePlugin.disablecorelimit	string	"false"	Disable core limit
devicePlugin.enableNumaTopology	bool	false	Advertise the physical GPU's NUMA node on each vGPU replica
devicePlugin.enabled	bool	true	Enable device plugin
devicePlugin.extraArgs	list	["-v=4"]	Extra arguments for device plugin
devicePlugin.extraEnvs	object	{}	Extra environment variables for device plugin
devicePlugin.gdrcopyEnabled	bool	false	Enable GDRCopy
devicePlugin.gdsEnabled	bool	false	Enable GDS
devicePlugin.gpuOperatorToolkitReady.enabled	bool	false	Enable GPU operator toolkit ready check
devicePlugin.gpuOperatorToolkitReady.hostPath	string	"/run/nvidia/validations"	Host path for GPU operator toolkit ready check
devicePlugin.gpuOperatorToolkitReady.securityContext	object	{"privileged":true,"runAsUser":0}	Security context for the toolkit-ready init container
devicePlugin.hostNetwork	bool	false	Share the host network namespace with the device plugin pod
devicePlugin.hostPID	bool	true	Share the host PID namespace with the device plugin pod
devicePlugin.image.pullPolicy	string	"IfNotPresent"	Device plugin image pull policy
devicePlugin.image.pullSecrets	list	[]	Specify docker-registry secret names as an array
devicePlugin.image.registry	string	"ghcr.io"	Device plugin image registry
devicePlugin.image.repository	string	"dynamia-ai/hami-enterprise"	Device plugin image repository
devicePlugin.image.tag	string	""	Device plugin image tag (immutable tags are recommended)
devicePlugin.libPath	string	"/usr/local/vgpu"	Library path for vGPU
devicePlugin.migStrategy	string	"none"	MIG strategy. Supported values: none, single, mixed
devicePlugin.mofedEnabled	bool	false	Enable Mellanox OFED
devicePlugin.monitor.ctrPath	string	"/usr/local/vgpu/containers"	Container path for monitor
devicePlugin.monitor.extraArgs	list	["-v=4"]	Extra arguments for monitor
devicePlugin.monitor.extraEnvs	object	{}	Extra environment variables for monitor
devicePlugin.monitor.image.pullPolicy	string	"IfNotPresent"	Monitor image pull policy
devicePlugin.monitor.image.pullSecrets	list	[]	Specify docker-registry secret names as an array
devicePlugin.monitor.image.registry	string	"ghcr.io"	Monitor image registry
devicePlugin.monitor.image.repository	string	"dynamia-ai/hami-enterprise"	Monitor image repository
devicePlugin.monitor.image.tag	string	""	Monitor image tag (immutable tags are recommended)
devicePlugin.monitor.resources	object	{}	Resources for monitor container
devicePlugin.monitor.resyncInterval	string	"5m"	Resync interval for monitor
devicePlugin.monitor.securityContext	object	{"allowPrivilegeEscalation":false,"capabilities":{"add":["SYS_ADMIN"],"drop":["ALL"]}}	Security context for the monitor container
devicePlugin.nodeConfiguration.config	string	"{\n \"nodeconfig\": [\n {\n \"name\": \"your-node-name\",\n \"operatingmode\": \"hami-core\",\n \"devicememoryscaling\": 1,\n \"devicesplitcount\": 10,\n \"preconfigureddevicememory\": 0,\n \"enablenumatopology\": false,\n \"migstrategy\": \"none\",\n \"filterdevices\": {\n \"uuid\": [],\n \"index\": []\n },\n \"enablegetpreferredallocation\": false\n }\n ]\n}\n"	Node configuration for device plugin. If set, overrides the default config.json
devicePlugin.nodeConfiguration.externalConfigName	string	""	Name of an existing ConfigMap to use for node configuration
devicePlugin.nvidiaDriverRoot	string	""	Root path for NVIDIA driver
devicePlugin.nvidiaHookPath	string	""	Path for NVIDIA hook
devicePlugin.nvidiaNodeSelector	object	{"gpu":"on"}	Node selector for NVIDIA device plugin
devicePlugin.passDeviceSpecsEnabled	bool	false	Enable passing device specs
devicePlugin.pluginPath	string	"/var/lib/kubelet/device-plugins"	Path for device plugin socket
devicePlugin.podAnnotations	object	{}	Annotations for device plugin pod
devicePlugin.preConfiguredDeviceMemory	int	0	Pre-configured device memory in MB for GPUs that don't support memory query. Set to 0 for auto-detection
devicePlugin.resources	object	{}	Resources for device plugin container
devicePlugin.runtimeClassName	string	""	Runtime class name to be used by the device plugin
devicePlugin.securityContext	object	{"allowPrivilegeEscalation":true,"capabilities":{"add":["SYS_ADMIN"],"drop":["ALL"]},"privileged":true}	Security context for the device plugin container
devicePlugin.service.annotations	object	{}	Annotations for device plugin service
devicePlugin.service.httpPort	int	31992	HTTP port for device plugin service
devicePlugin.service.labels	object	{}	Labels for device plugin service
devicePlugin.service.type	string	"NodePort"	Service type for device plugin
devicePlugin.tolerations	list	[]	Tolerations for device plugin pod
devicePlugin.updateStrategy.rollingUpdate.maxUnavailable	int	1	Maximum unavailable pods during update
devicePlugin.updateStrategy.type	string	"RollingUpdate"	Update strategy for device plugin DaemonSet
devices.alibaba.customresources	list	["alibaba.com/ppu","alibaba.com/ppu-memory","alibaba.com/gpu-core"]	Custom resource definitions for Alibaba devices
devices.alibaba.enabled	bool	true	Enable Alibaba PPU device
devices.alibaba.ppuCorePolicy	string	"default"	PPU core policy for Alibaba devices
devices.amd.customresources	list	["amd.com/gpu","amd.com/gpumem","amd.com/gpucores"]	Custom resource definitions for AMD devices
devices.ascend.customresources	list	["huawei.com/Ascend910A","huawei.com/Ascend910A-memory","huawei.com/Ascend910A-core","huawei.com/Ascend910B2","huawei.com/Ascend910B2-memory","huawei.com/Ascend910B2-core","huawei.com/Ascend910B3","huawei.com/Ascend910B3-memory","huawei.com/Ascend910B3-core","huawei.com/Ascend910B4","huawei.com/Ascend910B4-memory","huawei.com/Ascend910B4-core","huawei.com/Ascend910B4-1","huawei.com/Ascend910B4-1-memory","huawei.com/Ascend910B4-1-core","huawei.com/Ascend310P","huawei.com/Ascend310P-memory","huawei.com/Ascend310P-core","huawei.com/Ascend910C","huawei.com/Ascend910C-memory","huawei.com/Ascend910C-core"]	Custom resource definitions for Ascend devices
devices.ascend.enabled	bool	false	Enable Ascend device plugin
devices.ascend.extraArgs	list	[]	Extra arguments for Ascend device plugin
devices.ascend.hamiVnpuCore	bool	false	Enable soft-partitioning based on hami-vnpu-core (node-level annotation takes higher priority)
devices.ascend.image	string	""	Ascend device plugin image
devices.ascend.imagePullPolicy	string	"IfNotPresent"	Image pull policy for Ascend device plugin
devices.ascend.nodeSelector	object	{"ascend":"on"}	Node selector for Ascend device plugin
devices.ascend.runtimeClassName	string	""	Runtime class name for Ascend NPU pods
devices.ascend.tolerations	list	[]	Tolerations for Ascend device plugin
devices.awsneuron.customresources	list	["aws.amazon.com/neuron","aws.amazon.com/neuroncore"]	Custom resource definitions for AWS Neuron devices
devices.biren.customresources	list	["birentech.com/gpu"]	Custom resource definitions for Biren devices
devices.biren.enabled	bool	true	Enable Biren device plugin
devices.enflame.customresources	list	["enflame.com/drs-gcu","enflame.com/gcu-memory","enflame.com/gcu-core","enflame.com/gcu","enflame.com/vgcu","enflame.com/vgcu-percentage"]	Custom resource definitions for Enflame devices
devices.enflame.enabled	bool	true	Enable Enflame device plugin
devices.iluvatar.customresources	list	["iluvatar.ai/BI-V100-vgpu","iluvatar.ai/BI-V100.vCore","iluvatar.ai/BI-V100.vMem","iluvatar.ai/BI-V150-vgpu","iluvatar.ai/BI-V150.vCore","iluvatar.ai/BI-V150.vMem","iluvatar.ai/MR-V100-vgpu","iluvatar.ai/MR-V100.vCore","iluvatar.ai/MR-V100.vMem","iluvatar.ai/MR-V50-vgpu","iluvatar.ai/MR-V50.vCore","iluvatar.ai/MR-V50.vMem"]	Custom resource definitions for Iluvatar devices
devices.iluvatar.enabled	bool	false	Enable Iluvatar device plugin
devices.kunlun.customresources	list	["kunlunxin.com/xpu","kunlunxin.com/vxpu","kunlunxin.com/vxpu-memory"]	Custom resource definitions for Kunlun devices
devices.kunlun.enabled	bool	true	Enable Kunlun device plugin
devices.mthreads.customresources	list	["mthreads.com/vgpu"]	Custom resource definitions for MThreads devices
devices.mthreads.enabled	bool	true	Enable MThreads device plugin
devices.nvidia.gpuCorePolicy	string	"default"	GPU core policy for NVIDIA devices
devices.nvidia.libCudaLogLevel	int	2	libCUDA log level
devices.vastai.customresources	list	["vastaitech.com/va"]	Custom resource definitions for Vastai devices
devices.vastai.enabled	bool	true	Enable Vastai device plugin
dra.enabled	bool	false	Enable DRA (Dynamic Resource Allocation)
enflameResourceNameDRSGCU	string	"enflame.com/drs-gcu"	Enflame DRS GCU resource name
enflameResourceNameGCUCore	string	"enflame.com/gcu-core"	Enflame GCU core resource name
enflameResourceNameGCUMemory	string	"enflame.com/gcu-memory"	Enflame GCU memory resource name
enflameResourceNameVGCU	string	"enflame.com/vgcu"	Enflame VGCU resource name
enflameResourceNameVGCUPercentage	string	"enflame.com/vgcu-percentage"	Enflame VGCU percentage resource name
fullnameOverride	string	""	Override the fullname of the chart
global.annotations	object	{}	Global annotations to add to all resources
global.gpuHookPath	string	"/usr/local"	Path for GPU hook installation on nodes
global.imagePullSecrets	list	[]	Global Docker image pull secrets
global.imageRegistry	string	""	Global Docker image registry
global.imageTag	string	"v2.10.0-r1"	Global image tag for HAMi Enterprise components
global.labels	object	{}	Global labels to add to all resources
global.managedNodeSelector	object	{"usage":"gpu"}	Node selector configuration for managed GPU nodes
global.managedNodeSelectorEnable	bool	false	Enable managed node selector for GPU nodes
hami-dra.drivers.nvidia.containerDriver	bool	true	Enable container driver for NVIDIA DRA
hami-dra.drivers.nvidia.enabled	bool	true	Enable NVIDIA DRA driver
hami-dra.drivers.nvidia.image.repository	string	"ghcr.io/project-hami/k8s-dra-driver"	NVIDIA DRA driver image repository
hami-dra.drivers.nvidia.image.tag	string	"main"	NVIDIA DRA driver image tag
hami-dra.monitor.enabled	bool	true	Enable monitor for hami-dra
kunlunResourceName	string	"kunlunxin.com/xpu"	Kunlun XPU resource name
kunlunResourceVCountName	string	"kunlunxin.com/vxpu"	Kunlun virtual XPU count resource name
kunlunResourceVMemoryName	string	"kunlunxin.com/vxpu-memory"	Kunlun virtual XPU memory resource name
legacyMetrics	bool	false	Enable legacy metrics
metaxResourceCore	string	"metax-tech.com/vcore"	Metax sGPU core resource name
metaxResourceMem	string	"metax-tech.com/vmemory"	Metax sGPU memory resource name
metaxResourceName	string	"metax-tech.com/sgpu"	Metax sGPU resource name
metaxsGPUTopologyAware	string	"false"	Enable Metax sGPU topology awareness
mluResourceCores	string	"cambricon.com/mlu.smlu.vcore"	MLU cores resource name
mluResourceMem	string	"cambricon.com/mlu.smlu.vmemory"	MLU memory resource name
mluResourceName	string	"cambricon.com/vmlu"	MLU resource name
mockDevicePlugin.enabled	bool	false	Enable mock device plugin
mockDevicePlugin.image.pullPolicy	string	"IfNotPresent"	Mock device plugin image pull policy
mockDevicePlugin.image.pullSecrets	list	[]	Specify docker-registry secret names as an array
mockDevicePlugin.image.registry	string	"docker.io"	Mock device plugin image registry
mockDevicePlugin.image.repository	string	"projecthami/mock-device-plugin"	Mock device plugin image repository
mockDevicePlugin.image.tag	string	"1.0.1"	Mock device plugin image tag
nameOverride	string	""	Override the chart name
namespaceOverride	string	""	Override the namespace
podSecurityPolicy.enabled	bool	false	Enable PodSecurityPolicy
prometheus.enabled	bool	false	Enable Prometheus metrics
resourceCores	string	"nvidia.com/gpucores"	NVIDIA GPU cores resource name
resourceMem	string	"nvidia.com/gpumem"	NVIDIA GPU memory resource name
resourceMemPercentage	string	"nvidia.com/gpumem-percentage"	NVIDIA GPU memory percentage resource name
resourceName	string	"nvidia.com/gpu"	NVIDIA GPU resource name
resourcePriority	string	"nvidia.com/priority"	NVIDIA GPU priority resource name
scheduler.admissionWebhook.customURL.enabled	bool	false	Enable custom webhook URL
scheduler.admissionWebhook.customURL.host	string	"127.0.0.1"	Webhook host (must be an endpoint using https)
scheduler.admissionWebhook.customURL.path	string	"/webhook"	Webhook path
scheduler.admissionWebhook.customURL.port	int	31998	Webhook port
scheduler.admissionWebhook.enabled	bool	true	Enable admission webhook. If disabled, pods must be configured with correct schedulerName manually
scheduler.admissionWebhook.failurePolicy	string	"Ignore"	Failure policy for webhook
scheduler.admissionWebhook.manageNamespaceSelector	bool	true	Whether the chart renders and manages the webhook's namespaceSelector field
scheduler.admissionWebhook.namespaceSelector	object	{"matchExpressions":[],"matchLabels":{}}	Namespace selector for webhook
scheduler.admissionWebhook.objectSelector	object	{"matchExpressions":[]}	Object selector for webhook
scheduler.admissionWebhook.reinvocationPolicy	string	"Never"	Reinvocation policy for webhook
scheduler.admissionWebhook.whitelistNamespaces	list	[]	Namespaces that the webhook will not be applied to
scheduler.certManager.enabled	bool	false	Enable cert-manager for TLS certificate generation
scheduler.defaultSchedulerPolicy.gpuSchedulerPolicy	string	"spread"	GPU-level scheduling policy. Supported values: binpack, spread
scheduler.defaultSchedulerPolicy.nodeSchedulerPolicy	string	"binpack"	Node-level scheduling policy. Supported values: binpack, spread
scheduler.extender.extraArgs	list	["--debug","-v=4"]	Extra arguments for scheduler extender
scheduler.extender.image.pullPolicy	string	"IfNotPresent"	Scheduler extender image pull policy
scheduler.extender.image.pullSecrets	list	[]	Specify docker-registry secret names as an array
scheduler.extender.image.registry	string	"ghcr.io"	Scheduler extender image registry
scheduler.extender.image.repository	string	"dynamia-ai/hami-enterprise"	Scheduler extender image repository
scheduler.extender.image.tag	string	""	Scheduler extender image tag (immutable tags are recommended)
scheduler.extender.resources	object	{}	Resources for scheduler extender container
scheduler.forceOverwriteDefaultScheduler	bool	true	Force overwrite the default scheduler name in pods when it equals the K8s default scheduler name
scheduler.kubeScheduler.enabled	bool	true	Whether to run kube-scheduler container in the scheduler pod
scheduler.kubeScheduler.extraArgs	list	["--policy-config-file=/config/config.json","-v=4"]	Extra arguments for kube-scheduler (legacy config format)
scheduler.kubeScheduler.extraNewArgs	list	["--config=/config/config.yaml","-v=4"]	Extra arguments for kube-scheduler (new config format)
scheduler.kubeScheduler.image.pullPolicy	string	"IfNotPresent"	kube-scheduler image pull policy
scheduler.kubeScheduler.image.pullSecrets	list	[]	Specify docker-registry secret names as an array
scheduler.kubeScheduler.image.registry	string	"registry.cn-hangzhou.aliyuncs.com"	kube-scheduler image registry
scheduler.kubeScheduler.image.repository	string	"google_containers/kube-scheduler"	kube-scheduler image repository
scheduler.kubeScheduler.image.tag	string	""	kube-scheduler image tag (immutable tags are recommended)
scheduler.kubeScheduler.resources	object	{}	Resources for kube-scheduler container
scheduler.leaderElect	bool	true	Enable leader election for scheduler
scheduler.livenessProbe	bool	false	Enable liveness probe for scheduler
scheduler.metricsBindAddress	string	":9395"	Address to bind metrics server
scheduler.nodeLockExpire	string	"5m"	Node lock expiration time
scheduler.nodeName	string	""	Node name for scheduler pod. If installing as default scheduler, set this to skip the schedule workflow
scheduler.overwriteEnv	string	"false"	Overwrite environment variables
scheduler.patch.enabled	bool	true	Enable kube-webhook-certgen patch job
scheduler.patch.image.pullPolicy	string	"IfNotPresent"	kube-webhook-certgen image pull policy
scheduler.patch.image.pullSecrets	list	[]	Specify docker-registry secret names as an array
scheduler.patch.image.registry	string	"docker.io"	kube-webhook-certgen image registry
scheduler.patch.image.repository	string	"jettech/kube-webhook-certgen"	kube-webhook-certgen image repository
scheduler.patch.image.tag	string	"v1.5.2"	kube-webhook-certgen image tag
scheduler.patch.imageNew.pullPolicy	string	"IfNotPresent"	New kube-webhook-certgen image pull policy
scheduler.patch.imageNew.pullSecrets	list	[]	Specify docker-registry secret names as an array
scheduler.patch.imageNew.registry	string	"docker.io"	New kube-webhook-certgen image registry
scheduler.patch.imageNew.repository	string	"liangjw/kube-webhook-certgen"	New kube-webhook-certgen image repository
scheduler.patch.imageNew.tag	string	"v1.1.1"	New kube-webhook-certgen image tag
scheduler.patch.nodeSelector	object	{}	Node selector for patch job
scheduler.patch.podAnnotations	object	{}	Annotations for patch job pod
scheduler.patch.priorityClassName	string	""	Priority class name for patch job
scheduler.patch.runAsUser	int	2000	User ID to run patch job as
scheduler.patch.tolerations	list	[]	Tolerations for patch job
scheduler.podAnnotations	object	{}	Annotations for scheduler pod
scheduler.replicas	int	1	Number of scheduler replicas (only effective when leaderElect is true)
scheduler.service.annotations	object	{}	Annotations for scheduler service
scheduler.service.httpPort	int	443	HTTP port for scheduler service
scheduler.service.httpTargetPort	int	443	Target port for HTTP
scheduler.service.labels	object	{}	Labels for scheduler service
scheduler.service.monitorPort	int	31993	Monitoring port for scheduler service
scheduler.service.monitorTargetPort	int	9395	Target port for monitoring
scheduler.service.schedulerPort	int	31998	NodePort for scheduler HTTP
scheduler.service.type	string	"NodePort"	Service type for scheduler
scheduler.tolerations	list	[]	Tolerations for scheduler pod
scheduler.useDownward	bool	true	Whether to enable useDownward in the generated scheduler device config for NVIDIA devices
schedulerName	string	"hami-scheduler"	Name of the scheduler
vastaiResourceName	string	"vastaitech.com/va"	Vastai resource name