Learn Kubernetes Basics

Concepts

Kubernetes v1.16 documentation is no longer actively maintained. The version you are currently viewing is a static snapshot. For up-to-date documentation, see the latest version.

Edit This Page

Resource Bin Packing for Extended Resources

FEATURE STATE: Kubernetes 1.16 alpha
This 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. Resources consists 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 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
               =  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

Feedback