Kubernetes v1.16 [alpha]
The kube-scheduler can be configured to enable bin packing of resources along with extended resources using RequestedToCapacityRatioResourceAllocation
priority function. Priority functions can be used to fine-tune the kube-scheduler as per custom needs.
Kubernetes allows the users to specify the resources along with weights for each resource to score nodes based on the request to capacity ratio. This allows users to bin pack extended resources by using appropriate parameters and improves the utilization of scarce resources in large clusters. The behavior of the RequestedToCapacityRatioResourceAllocation
priority function can be controlled by a configuration option called RequestedToCapacityRatioArgs
. This argument consists of two parameters shape
and resources
. The shape
parameter allows the user to tune the function as least requested or most requested based on utilization
and score
values. The resources
parameter consists of name
of the resource to be considered during scoring and weight
specify the weight of each resource.
Below is an example configuration that sets requestedToCapacityRatioArguments
to bin packing behavior for extended resources intel.com/foo
and intel.com/bar
.
apiVersion: kubescheduler.config.k8s.io/v1beta1
kind: KubeSchedulerConfiguration
profiles:
# ...
pluginConfig:
- name: RequestedToCapacityRatio
args:
shape:
- utilization: 0
score: 10
- utilization: 100
score: 0
resources:
- name: intel.com/foo
weight: 3
- name: intel.com/bar
weight: 5
Referencing the KubeSchedulerConfiguration
file with the kube-scheduler flag --config=/path/to/config/file
will pass the configuration to the scheduler.
This feature is disabled by default
shape
is used to specify the behavior of the RequestedToCapacityRatioPriority
function.
shape:
- utilization: 0
score: 0
- utilization: 100
score: 10
The above arguments give the node a score
of 0 if utilization
is 0% and 10 for utilization
100%, thus enabling bin packing behavior. To enable least requested the score value must be reversed as follows.
shape:
- utilization: 0
score: 10
- utilization: 100
score: 0
resources
is an optional parameter which defaults to:
resources:
- name: cpu
weight: 1
- name: memory
weight: 1
It can be used to add extended resources as follows:
resources:
- name: intel.com/foo
weight: 5
- name: cpu
weight: 3
- name: memory
weight: 1
The weight
parameter is optional and is set to 1 if not specified. Also, the weight
cannot be set to a negative value.
This section is intended for those who want to understand the internal details of this feature. Below is an example of how the node score is calculated for a given set of values.
Requested resources:
intel.com/foo : 2
memory: 256MB
cpu: 2
Resource weights:
intel.com/foo : 5
memory: 1
cpu: 3
FunctionShapePoint {{0, 0}, {100, 10}}
Node 1 spec:
Available:
intel.com/foo: 4
memory: 1 GB
cpu: 8
Used:
intel.com/foo: 1
memory: 256MB
cpu: 1
Node score:
intel.com/foo = resourceScoringFunction((2+1),4)
= (100 - ((4-3)*100/4)
= (100 - 25)
= 75 # requested + used = 75% * available
= rawScoringFunction(75)
= 7 # floor(75/10)
memory = resourceScoringFunction((256+256),1024)
= (100 -((1024-512)*100/1024))
= 50 # requested + used = 50% * available
= rawScoringFunction(50)
= 5 # floor(50/10)
cpu = resourceScoringFunction((2+1),8)
= (100 -((8-3)*100/8))
= 37.5 # requested + used = 37.5% * available
= rawScoringFunction(37.5)
= 3 # floor(37.5/10)
NodeScore = (7 * 5) + (5 * 1) + (3 * 3) / (5 + 1 + 3)
= 5
Node 2 spec:
Available:
intel.com/foo: 8
memory: 1GB
cpu: 8
Used:
intel.com/foo: 2
memory: 512MB
cpu: 6
Node score:
intel.com/foo = resourceScoringFunction((2+2),8)
= (100 - ((8-4)*100/8)
= (100 - 50)
= 50
= rawScoringFunction(50)
= 5
memory = resourceScoringFunction((256+512),1024)
= (100 -((1024-768)*100/1024))
= 75
= rawScoringFunction(75)
= 7
cpu = resourceScoringFunction((2+6),8)
= (100 -((8-8)*100/8))
= 100
= rawScoringFunction(100)
= 10
NodeScore = (5 * 5) + (7 * 1) + (10 * 3) / (5 + 1 + 3)
= 7
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Documentation Distributed under CC BY 4.0.
https://kubernetes.io/docs/concepts/scheduling-eviction/resource-bin-packing/