kube-scheduler-Container Compute Service(ACS)-阿里云帮助中心

The kube-scheduler is a control plane component that schedules pods to suitable nodes in a cluster based on their resource requirements.

kube-scheduler

Based on pod and node resources and other properties, the kube-scheduler schedules each pod to a suitable virtual node in an ACS cluster. For more information, see the official Kubernetes documentation about kube-scheduler.

Note

Starting from Kubernetes v1.32, the versioning rules for the ACS scheduler are consistent with those for ACK. For more information, see kube-scheduler.

Usage

The kube-scheduler component is installed by default when you create a cluster. For more information about its features, see scheduling overview.

Component configuration

To configure custom parameters for the kube-scheduler component, follow these steps:

Log on to the ACS console. In the left navigation pane, click Clusters.
On the Clusters page, click the name of the target cluster. In the left navigation pane, click Add-ons.

On the Core Components tab, locate the kube-scheduler component and click Configuration in the lower-right corner of the card. In the dialog box that appears, configure the parameters.

Different scheduler versions support different features and custom parameters. For more information about the features of each scheduler version, see kube-scheduler. The following table describes the custom parameters.

Parameter	Description	Type	Value	Default
Enable Zone Recommendation	During scheduling, ACS automatically filters out availability zones with insufficient resources. For more information, see the resource recommendation feature.	bool	`false` `true`	`true`
Enable custom labels and schedulers for GPU-HPN nodes	For more information, see Use a custom scheduler and Manage node labels and taints.	bool	`false` `true`	`false`
scorePluginWeights	The weight parameters for scheduler scoring plugins. This includes native community plugins and Alibaba Cloud proprietary plugins: Community plugins include NodeAffinity, PodTopologySpread, InnerPodAffinity, and TaintToleration. For more information, see the documentation for affinity and toleration policies. Alibaba Cloud proprietary plugins include: ServerlessScheduling: For general-purpose, performance, and GPU compute classes, this plugin prioritizes availability zones with more available platform resources based on resource recommendations. The weight of a scoring plugin affects which nodes the scheduler prioritizes. For a detailed description of scoring weights, see the community documentation. Important ACS automatically filters out availability zones with insufficient resources during the scheduling process. This filtering stage is not affected by scoring policies. When you use affinity-related scoring policies, make sure that you select multiple recommended availability zones for your pods to ensure optimal performance of the scoring policies. For more information, see the resource recommendation feature.	plugin: string weight: int	The plugin parameter supports only plugins from the public list. The weight must be an integer from 1 to 10,000.	The default weights for each scoring plugin are as follows: NodeAffinity: 1 PodTopologySpread: 1 InnerPodAffinity: 1 TaintToleration: 1 ServerlessScheduling: 2

Change history

Version 1.32

Version	Release date	Changes
v1.32.0-apsara.6.11.8.507bee55	December 22, 2025	New features: Added support for using the label `alibabacloud.com/acs: "true"` to directly schedule pods to ACS compute resources (general-purpose, performance, or GPU), bypassing pod affinity constraints. Enhancements: Expanded the coverage scenarios for GPU-HPN topology-aware scheduling. For more information, see GPU-HPN topology-aware scheduling. Enabled the Enable custom labels and schedulers for GPU-HPN nodes feature by default. Bug fixes: Fixed an issue where GPU-HPN pods were scheduled to nodes with mismatched GPU resource names. Trigger condition: The Enable custom labels and schedulers for GPU-HPN nodes feature is enabled, and the pod uses the default cluster scheduler.
v1.32.0-aliyun.6.9.7.eb18a8a9	September 22, 2025	Bug fixes: Fixed an issue where pod scheduling was stuck in the Pending state when using strong spread constraints with PodAntiAffinity and topology spread constraints. This issue was introduced in version v1.32.0-aliyun.6.9.6.4e1407c2.
v1.32.0-aliyun.6.9.6.4e1407c2	September 17, 2025	New features: Added a switch to enable or disable the resource recommendation feature for availability zones. Enhancements: Optimized the scheduling retry efficiency for pods that use a PersistentVolumeClaim (PVC). Optimized the PodTopologySpread policy. When `whenUnsatisfiable` is set to `ScheduleAnyway`, pods that are being created are now included in the topology distribution calculation.
v1.32.0-aliyun.6.9.5.ccfc0094	July 09, 2025	Initial release of the component. This version is compatible with ACS cluster v1.32 and includes all ACS features from v1.31.0-aliyun-1.4.2.

Version 1.31

Version	Release date	Changes
v1.31.0-aliyun-1.5.0	December 22, 2025	New features: Added support for using the label `alibabacloud.com/acs: "true"` to directly schedule pods to ACS compute resources (general-purpose, performance, or GPU), bypassing pod affinity constraints. Enhancements: Expanded the coverage scenarios for GPU-HPN topology-aware scheduling. For more information, see GPU-HPN topology-aware scheduling. Enabled the Enable custom labels and schedulers for GPU-HPN nodes feature by default. Bug fixes: Fixed an issue where GPU-HPN pods were scheduled to nodes with mismatched GPU resource names. Trigger condition: The Enable custom labels and schedulers for GPU-HPN nodes feature is enabled, and the pod uses the default cluster scheduler.
v1.31.0-aliyun-1.4.4	September 22, 2025	Bug fixes: Fixed an issue where pod scheduling was stuck in the Pending state when using strong spread constraints with PodAntiAffinity and topology spread constraints. This issue was introduced in version v1.31.0-aliyun-1.4.3.
v1.31.0-aliyun-1.4.3	September 17, 2025	New features: Added a switch to enable or disable the resource recommendation feature for availability zones. Enhancements: Optimized the scheduling retry efficiency for pods that use a PVC. Optimized the PodTopologySpread policy. When `whenUnsatisfiable` is set to `ScheduleAnyway`, pods that are being created are now included in the topology distribution calculation.
v1.31.0-aliyun-1.4.2	July 09, 2025	Optimized internal logging implementation and base image modifications.
v1.31.0-aliyun-1.4.1	May 19, 2025	Added support for configuring custom weight parameters for scoring plugins. For more information, see scorePluginWeights.
v1.31.0-aliyun-1.4.0	April 09, 2025	Optimized the scheduling process for pods that use PersistentVolumeClaims (PVCs) of the WaitForFirstConsumer (WFFC) type. When a pod uses a WFFC-type PVC and specifies a vSwitch, you must also specify the corresponding availability zone in the pod affinity settings. The scheduler ensures that the availability zone assigned to the PVC matches the vSwitch to prevent the pod from remaining in the Pending state. For more information, see Pod annotation features.
v1.31.0-aliyun-1.3.1	March 20, 2025	GPU sharing and scheduling now supports the static policy and QoS configuration. Improved fault tolerance for invalid configurations in custom priority scheduling.
v1.31.0-aliyun-1.3.0	February 08, 2025	Fixed a cloud disk scheduling issue for pods that use WaitForFirstConsumer-type PVCs. Added support for configuring custom schedulers for GPU-HPN type pods.
v1.31.0-aliyun-1.2.0	November 29, 2024	Initial release of the component. This version is compatible with ACS cluster v1.31.

Version 1.30

Version	Release date	Changes
v1.30.3-aliyun-1.6.0	December 22, 2025	New features: Added support for using the label `alibabacloud.com/acs: "true"` to directly schedule pods to ACS compute resources (general-purpose, performance, or GPU), bypassing pod affinity constraints. Enhancements: Expanded the coverage scenarios for GPU-HPN topology-aware scheduling. For more information, see GPU-HPN topology-aware scheduling. Enabled the Enable custom labels and schedulers for GPU-HPN nodes feature by default. Bug fixes: Fixed an issue where GPU-HPN pods were scheduled to nodes with mismatched GPU resource names. Trigger condition: The Enable custom labels and schedulers for GPU-HPN nodes feature is enabled, and the pod uses the default cluster scheduler.
v1.30.3-aliyun-1.4.4	September 22, 2025	Bug fixes: Fixed an issue where pod scheduling was stuck in the Pending state when using strong spread constraints with PodAntiAffinity and topology spread constraints. This issue was introduced in version v1.30.3-aliyun-1.4.3.
v1.30.3-aliyun-1.4.3	September 17, 2025	New features: Added a switch to enable or disable the resource recommendation feature for availability zones. Enhancements: Optimized the scheduling retry efficiency for pods that use a PVC. Optimized the PodTopologySpread policy. When `whenUnsatisfiable` is set to `ScheduleAnyway`, pods that are being created are now included in the topology distribution calculation.
v1.30.3-aliyun-1.4.2	July 09, 2025	Optimized internal logging implementation and base image modifications.
v1.30.3-aliyun-1.4.1	May 19, 2025	Added support for configuring custom weight parameters for scoring plugins. For more information, see scorePluginWeights.
v1.30.3-aliyun-1.4.0	April 09, 2025	Optimized the scheduling process for pods that use WFFC-type PVCs. When a pod uses a WFFC-type PVC and specifies a vSwitch, you must also specify the corresponding availability zone in the pod affinity settings. The scheduler ensures that the availability zone assigned to the PVC matches the vSwitch to prevent the pod from remaining in the Pending state. For more information, see Pod annotation features.
v1.30.3-aliyun-1.3.1	March 20, 2025	GPU sharing and scheduling now supports the static policy and QoS configuration. Improved fault tolerance for invalid configurations in custom priority scheduling.
v1.30.3-aliyun-1.3.0	February 08, 2025	Fixed a cloud disk scheduling issue for pods that use WaitForFirstConsumer-type PVCs. Added support for configuring custom schedulers for GPU-HPN type pods.
v1.30.3-aliyun-1.2.0	November 29, 2024	Optimized pod scheduling efficiency. Adapted to the new version of the acs-virtual-node component. The acs-virtual-node component must be version v2.12.0-acs.9 or later.
v1.30.3-aliyun-1.1.1	September 09, 2024	Initial release of the component. This version is compatible with ACS cluster v1.30.

Version 1.28

Version	Release date	Changes
v1.28.12-aliyun-1.4.5	December 22, 2025	Bug fixes: Fixed an issue where GPU-HPN pods were scheduled to nodes with mismatched GPU resource types. Trigger condition: The Enable custom labels and schedulers for GPU-HPN nodes feature is enabled, and the pod uses the default cluster scheduler.
v1.28.12-aliyun-1.4.4	September 22, 2025	Bug fixes: Fixed an issue where pod scheduling was stuck in the Pending state when using strong spread constraints with PodAntiAffinity and topology spread constraints. This issue was introduced in version v1.28.12-aliyun-1.4.3.
v1.28.12-aliyun-1.4.3	September 17, 2025	New features: Added a switch to enable or disable the resource recommendation feature for availability zones. Enhancements: Optimized the scheduling retry efficiency for pods that use a PVC. Optimized the PodTopologySpread policy. When `whenUnsatisfiable` is set to `ScheduleAnyway`, pods that are being created are now included in the topology distribution calculation.
v1.28.12-aliyun-1.4.2	July 09, 2025	Optimized internal logging implementation and base image modifications.
v1.28.12-aliyun-1.4.1	May 19, 2025	Added support for configuring custom weight parameters for scoring plugins. For more information, see scorePluginWeights.
v1.28.12-aliyun-1.4.0	April 09, 2025	Optimized the scheduling process for pods that use WFFC-type PVCs. When a pod uses a WFFC-type PVC and specifies a vSwitch, you must also specify the corresponding availability zone in the pod affinity settings. The scheduler ensures that the availability zone assigned to the PVC matches the vSwitch to prevent the pod from remaining in the Pending state. For more information, see Pod annotation features.
v1.28.9-aliyun-1.3.1	March 20, 2025	GPU sharing and scheduling now supports the static policy and QoS configuration. Improved fault tolerance for invalid configurations in custom priority scheduling.
v1.28.9-aliyun-1.3.0	February 08, 2025	Fixed a cloud disk scheduling issue for pods that use WaitForFirstConsumer-type PVCs. Added support for configuring custom schedulers for GPU-HPN type pods.
v1.28.9-aliyun-1.2.0	November 29, 2024	Optimized pod scheduling efficiency. Adapted to the new version of the acs-virtual-node component. The acs-virtual-node component must be version v2.12.0-acs.9 or later.
v1.28.9-aliyun-1.1.1	September 06, 2024	Optimized event notification messages.
v1.28.9-aliyun-1.1.0	August 22, 2024	Added support for custom resource priority scheduling.
v1.28.9-aliyun-1.0.1.dfd9511f	July 12, 2024	Optimized internal interfaces.
v1.28.9-aliyun-1.0.0b72f000	June 15, 2024	Initial release of the component. This version is compatible with ACS cluster v1.28.

Version 1.26

Version	Release date	Changes
v1.26.3-aliyun-1.3.1	March 20, 2025	GPU sharing and scheduling now supports the static policy and QoS configuration. Improved fault tolerance for invalid configurations in custom priority scheduling.
v1.26.3-aliyun-1.3.0	February 08, 2025	Fixed a cloud disk scheduling issue for pods that use WaitForFirstConsumer-type PVCs. Added support for configuring custom schedulers for GPU-HPN type pods.
v1.26.3-aliyun-1.2.0	November 29, 2024	Optimized pod scheduling efficiency. Adapted to the new version of the acs-virtual-node component. The acs-virtual-node component must be version v2.12.0-acs.9 or later.
v1.26.3-aliyun-1.1.1	September 06, 2024	Optimized event notification messages.
v1.26.3-aliyun-1.1.0	August 22, 2024	Added support for custom resource priority scheduling.
v1.26.3-aliyun-1.0.1.4d326e78	July 12, 2024	Optimized internal interfaces.
v1.26.3-aliyun-1.0.fa88f9ae	June 25, 2024	Initial release of the component. This version is compatible with ACS cluster v1.26.