WorkloadSpread
FEATURE STATE: Kruise v0.10.0
WorkloadSpread can distribute Pods of workload to different types of Node according to some polices, which empowers single workload the abilities for multi-domain deployment and elastic deployment.
Some common policies include:
- fault toleration spread (for example, spread evenly among hosts, az, etc)
- spread according to the specified ratio (for example, deploy Pod to several specified az according to the proportion)
- subset management with priority, such as
- deploy Pods to ecs first, and then deploy to eci when its resources are insufficient.
- deploy a fixed number of Pods to ecs first, and the rest Pods are deployed to eci.
- subset management with customization, such as
- control how many pods in a workload are deployed in different cpu arch
- enable pods in different cpu arch to have different resource requirements
The feature of WorkloadSpread is similar with UnitedDeployment in OpenKruise community. Each WorkloadSpread defines multi-domain
called subset
. Each domain may provide the limit to run the replicas number of pods called maxReplicas
.
WorkloadSpread injects the domain configuration into the Pod by Webhook, and it also controls the order of scale in and scale out.
Kruise with version lower than 1.3.0
supports CloneSet
, Deployment
, ReplicaSet
.
Since Kruise 1.3.0
, WorkloadSpread supports StatefulSet
.
In particular, for StatefulSet
, WorkloadSpread supports manage its subsets only when scale up
. The order of scale down
is still controlled by StatefulSet controller. The subset management of StatefulSet is based on ordinals of Pods, and more details can be found here.
Since Kruise 1.5.0
, WorkloadSpread supports customized workloads
that have scale sub-resource.
Demo
apiVersion: apps.kruise.io/v1alpha1
kind: WorkloadSpread
metadata:
name: workloadspread-demo
spec:
targetRef:
apiVersion: apps/v1 | apps.kruise.io/v1alpha1
kind: Deployment | CloneSet
name: workload-xxx
subsets:
- name: subset-a
requiredNodeSelectorTerm:
matchExpressions:
- key: topology.kubernetes.io/zone
operator: In
values:
- zone-a
preferredNodeSelectorTerms:
- weight: 1
preference:
matchExpressions:
- key: another-node-label-key
operator: In
values:
- another-node-label-value
maxReplicas: 3
tolerations: [ ]
patch:
metadata:
labels:
xxx-specific-label: xxx
- name: subset-b
requiredNodeSelectorTerm:
matchExpressions:
- key: topology.kubernetes.io/zone
operator: In
values:
- zone-b
scheduleStrategy:
type: Adaptive | Fixed
adaptive:
rescheduleCriticalSeconds: 30
targetRef
: specify the target workload. Can not be mutated,and one workload can only correspond to one WorkloadSpread.
subsets
subsets
consists of multiple domain called subset
, and each topology has different configuration.
sub-fields
name
: the name ofsubset
, it is distinct in a WorkloadSpread, which represents a topology.maxReplicas
:the replicas limit ofsubset
, and must be Integer and >= 0. There is no replicas limit while themaxReplicas
is nil.Don't support percentage type in current version.
requiredNodeSelectorTerm
: match zone hardly。preferredNodeSelectorTerms
: match zone softly。
Caution:requiredNodeSelectorTerm
corresponds the requiredDuringSchedulingIgnoredDuringExecution
of nodeAffinity.
preferredNodeSelectorTerms
corresponds the preferredDuringSchedulingIgnoredDuringExecution
of nodeAffinity.
tolerations
: the tolerations of Pod insubset
.
tolerations:
- key: "key1"
operator: "Equal"
value: "value1"
effect: "NoSchedule"
patch
: customize the Pod configuration ofsubset
, such as Annotations, Labels, Env.
Example:
# patch pod with a topology label:
patch:
metadata:
labels:
topology.application.deploy/zone: "zone-a"
# patch pod container resources:
patch:
spec:
containers:
- name: main
resources:
limit:
cpu: "2"
memory: 800Mi
# patch pod container env with a zone name:
patch:
spec:
containers:
- name: main
env:
- name: K8S_AZ_NAME
value: zone-a
Schedule strategy
WorkloadSpread provides two kind strategies, the default strategy is Fixed
.
scheduleStrategy:
type: Adaptive | Fixed
adaptive:
rescheduleCriticalSeconds: 30
Fixed:
Workload is strictly spread according to the definition of the subset.
Adaptive:
Reschedule: Kruise will check the unschedulable Pods of subset. If it exceeds the defined duration, the failed Pods will be rescheduled to the other
subset
.
Requirements
WorkloadSpread defaults to be disabled. You have to configure the feature-gate WorkloadSpread when install or upgrade Kruise:
$ helm install kruise https://... --set featureGates="WorkloadSpread=true"
Pod Webhook
WorkloadSpread uses webhook
to inject fault domain rules.
If the PodWebhook
feature-gate is set to false, WorkloadSpread will also be disabled.
deletion-cost feature
CloneSet
has supported deletion-cost feature in the latest versions.
The other native workload need kubernetes version >= 1.21. (In 1.21, users need to enable PodDeletionCost feature-gate, and since 1.22 it will be enabled by default)
Scale order:
The workload managed by WorkloadSpread will scale according to the defined order in spec.subsets
.
The order of subset
in spec.subsets
can be changed, which can adjust the scale order of workload.
Scale out
- The Pods are scheduled in the subset order defined in the
spec.subsets
. It will be scheduled in the nextsubset
while the replica number reaches the maxReplicas ofsubset
Scale in
- When the replica number of the
subset
is greater than themaxReplicas
, the extra Pods will be removed in a high priority. - According to the
subset
order in thespec.subsets
, the Pods of thesubset
at the back are deleted before the Pods at the front.
# subset-a subset-b subset-c
# maxReplicas 10 10 nil
# pods number 10 10 10
# deletion order: c -> b -> a
# subset-a subset-b subset-c
# maxReplicas 10 10 nil
# pods number 20 20 20
# deletion order: b -> a -> c
Use WorkloadSpread with customized workload
If you want to use WorkloadSpread with custom workloads, which is disabled by default, some additional configuration is required. This section uses the Rollout Workload from the Argo community as an example to demonstrate how to integrate it with WorkloadSpread.
Configure the custom workload watch whitelist
First, you need to add the custom workload to the WorkloadSpread_Watch_Custom_Workload_WhiteList
to ensure it can be
read and understood by WorkloadSpread.
apiVersion: v1
kind: ConfigMap
metadata:
name: kruise-configuration
namespace: kruise-system
data:
"WorkloadSpread_Watch_Custom_Workload_WhiteList": |
{
"workloads": [
{
"Group": "argoproj.io",
"Kind": "Rollout",
"replicasPath": "spec.replicas",
}
]
}
The specific configuration items are explained as follows:
- Group: ApiGroup of the customized workload.
- Kind: Kind of the customized workload.
- subResources: SubResources of the customized workload, including Group and Kind. For example: Deployment's ReplicaSet. This field is optional, and can be left as empty slice if no sub-workload is used for the customized workload.
- replicasPath: Resource path to the replicas in the resource. For example: spec.replicas.
Authorize kruise-manager
To use WorkloadSpread with custom workloads, you need to grant the kruise-manager service account read permissions for the respective resources.
Caution: The WorkloadSpread Webhook does not set a deletion cost for Pods created by custom workloads, so it cannot ensure the scaling-down order of custom workloads.
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
name: kruise-rollouts-access
rules:
- apiGroups: [ "argoproj.io" ]
resources: [ "rollouts" ]
verbs: [ "get" ]
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
name: kruise-rollouts-access-binding
subjects:
- kind: ServiceAccount
name: kruise-manager
namespace: kruise-system
roleRef:
kind: ClusterRole
name: kruise-rollouts-access
apiGroup: rbac.authorization.k8s.io
Reference the custom workload in WorkloadSpread
Once the configuration is complete, the custom workload can be referenced in the targetRef
field of WorkloadSpread.
apiVersion: apps.kruise.io/v1alpha1
kind: WorkloadSpread
metadata:
name: workloadspread-demo
spec:
targetRef:
apiVersion: argoproj.io/v1alpha1
kind: Rollout
name: rollouts-demo
subsets:
...
feature-gates
WorkloadSpread feature is turned off by default, if you want to turn it on set feature-gates WorkloadSpread.
$ helm install kruise https://... --set featureGates="WorkloadSpread=true"
Example
Elastic deployment
zone-a
(ACK) holds 100 Pods, zone-b
(ECI) as an elastic zone holds additional Pods.
- Create a WorkloadSpread instance.
apiVersion: apps.kruise.io/v1alpha1
kind: WorkloadSpread
metadata:
name: ws-demo
namespace: deploy
spec:
targetRef: # workload in the same namespace
apiVersion: apps.kruise.io/v1alpha1
kind: CloneSet
name: workload-xxx
subsets:
- name: ACK # zone ACK
requiredNodeSelectorTerm:
matchExpressions:
- key: topology.kubernetes.io/zone
operator: In
values:
- ack
maxReplicas: 100
patch: # inject label.
metadata:
labels:
deploy/zone: ack
- name: ECI # zone ECI
requiredNodeSelectorTerm:
matchExpressions:
- key: topology.kubernetes.io/zone
operator: In
values:
- eci
patch:
metadata:
labels:
deploy/zone: eci
- Creat a corresponding workload, the number of replicas ca be adjusted freely.
Effect
- When the number of
replicas
<= 100, the Pods are scheduled inACK
zone. - When the number of
replicas
> 100, the 100 Pods are inACK
zone, the extra Pods are scheduled inECI
zone. - The Pods in
ECI
elastic zone are removed first when scaling in.
Multi-domain deployment
Deploy 100 Pods to two zone
(zone-a, zone-b) separately.
- Create a WorkloadSpread instance.
apiVersion: apps.kruise.io/v1alpha1
kind: WorkloadSpread
metadata:
name: ws-demo
namespace: deploy
spec:
targetRef:
apiVersion: apps.kruise.io/v1alpha1
kind: CloneSet
name: workload-xxx
subsets:
- name: subset-a
requiredNodeSelectorTerm:
matchExpressions:
- key: topology.kubernetes.io/zone
operator: In
values:
- zone-a
maxReplicas: 100
patch:
metadata:
labels:
deploy/zone: zone-a
- name: subset-b
requiredNodeSelectorTerm:
matchExpressions:
- key: topology.kubernetes.io/zone
operator: In
values:
- zone-b
maxReplicas: 100
patch:
metadata:
labels:
deploy/zone: zone-b
Creat a corresponding workload with a 200 replicas, or perform a rolling update on an existing workload.
If the spread of zone needs to be changed, first adjust the
maxReplicas
ofsubset
, and then change thereplicas
of workload.