Resource Bin Packing for Extended Resources
FEATURE STATE: Kubernetes 1.16
alphaThis feature is currently in a alpha state, meaning:
- The version names contain alpha (e.g. v1alpha1).
- Might be buggy. Enabling the feature may expose bugs. Disabled by default.
- Support for feature may be dropped at any time without notice.
- The API may change in incompatible ways in a later software release without notice.
- Recommended for use only in short-lived testing clusters, due to increased risk of bugs and lack of long-term support.
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.
Enabling Bin Packing using RequestedToCapacityRatioResourceAllocation
Before Kubernetes 1.15, Kube-scheduler used to allow scoring nodes based on the request to capacity ratio of primary resources like CPU and Memory. Kubernetes 1.16 added a new parameter to the priority function that 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 improves the utilization of scarce resources in large clusters. The behavior of the RequestedToCapacityRatioResourceAllocation
priority function can be controlled by a configuration option called requestedToCapacityRatioArguments
. This argument consists of two parameters shape
and resources
. Shape allows the user to tune the function as least requested or most requested based on utilization
and score
values. Resourcesconsists of name
which specifies 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
{
"kind" : "Policy",
"apiVersion" : "v1",
...
"priorities" : [
...
{
"name": "RequestedToCapacityRatioPriority",
"weight": 2,
"argument": {
"requestedToCapacityRatioArguments": {
"shape": [
{"utilization": 0, "score": 0},
{"utilization": 100, "score": 10}
],
"resources": [
{"name": "intel.com/foo", "weight": 3},
{"name": "intel.com/bar", "weight": 5}
]
}
}
}
],
}
This feature is disabled by default
Tuning RequestedToCapacityRatioResourceAllocation Priority Function
shape
is used to specify the behavior of the RequestedToCapacityRatioPriority
function.
{"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.
{"utilization": 0, "score": 100},
{"utilization": 100, "score": 0}
resources
is an optional parameter which by defaults is set 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.
How the RequestedToCapacityRatioResourceAllocation Priority Function Scores Nodes
This section is intended for those who want to understand the internal detailsof 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
= rawScoringFunction(75)
= 7
Memory = resourceScoringFunction((256+256),1024)
= (100 -((1024-512)*100/1024))
= 50
= rawScoringFunction(50)
= 5
CPU = resourceScoringFunction((2+1),8)
= (100 -((8-3)*100/8))
= 37.5
= rawScoringFunction(37.5)
= 3
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 - 25)
= 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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