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Tweak page style for resource-bin-packing
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tengqm committed Nov 18, 2020
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{{< feature-state for_k8s_version="v1.16" state="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.


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.

<!-- body -->

## 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 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 `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`

```json
{
"kind" : "Policy",
"apiVersion" : "v1",

...

"priorities" : [

...
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
`requestedToCapacityRatioArguments`. 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`.

{
"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}
]
}
}
}
],
}
```yaml
apiVersion: v1
kind: Policy
# ...
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
### Tuning the Priority Function

`shape` is used to specify the behavior of the `RequestedToCapacityRatioPriority` function.
`shape` is used to specify the behavior of the
`RequestedToCapacityRatioPriority` function.

```yaml
{"utilization": 0, "score": 0},
{"utilization": 100, "score": 10}
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.
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.

```yaml
{"utilization": 0, "score": 100},
{"utilization": 100, "score": 0}
shape:
- utilization: 0
score: 100
- utilization: 100
score: 0
```

`resources` is an optional parameter which by defaults is set to:
`resources` is an optional parameter which defaults to:

``` yaml
"resources": [
{"name": "CPU", "weight": 1},
{"name": "Memory", "weight": 1}
]
resources:
- name: CPU
weight: 1
- name: Memory
weight: 1
```

It can be used to add extended resources as follows:

```yaml
"resources": [
{"name": "intel.com/foo", "weight": 5},
{"name": "CPU", "weight": 3},
{"name": "Memory", "weight": 1}
]
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.
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
### Node scoring for capacity allocation

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
Requested resources:

```
intel.com/foo : 2
Memory: 256MB
CPU: 2
```

Resource Weights
Resource weights:

```
intel.com/foo : 5
Memory: 1
CPU: 3
```

FunctionShapePoint {{0, 0}, {100, 10}}

Node 1 Spec
Node 1 spec:

```
Available:
intel.com/foo : 4
Memory : 1 GB
CPU: 8
intel.com/foo: 4
Memory: 1 GB
CPU: 8
Used:
intel.com/foo: 1
Memory: 256MB
CPU: 1
intel.com/foo: 1
Memory: 256MB
CPU: 1
```

Node Score:
Node score:

```
intel.com/foo = resourceScoringFunction((2+1),4)
= (100 - ((4-3)*100/4)
= (100 - 25)
Expand All @@ -152,24 +174,24 @@ CPU = resourceScoringFunction((2+1),8)
NodeScore = (7 * 5) + (5 * 1) + (3 * 3) / (5 + 1 + 3)
= 5
```

Node 2 spec:

Node 2 Spec
```
Available:
intel.com/foo: 8
Memory: 1GB
CPU: 8
intel.com/foo: 8
Memory: 1GB
CPU: 8
Used:
intel.com/foo: 2
Memory: 512MB
CPU: 6
```

intel.com/foo: 2
Memory: 512MB
CPU: 6
Node Score:
Node score:

```
intel.com/foo = resourceScoringFunction((2+2),8)
= (100 - ((8-4)*100/8)
= (100 - 50)
Expand All @@ -194,4 +216,8 @@ NodeScore = (5 * 5) + (7 * 1) + (10 * 3) / (5 + 1 + 3)
```

## {{% heading "whatsnext" %}}

- Read more about the [scheduling framework](/docs/concepts/scheduling-eviction/scheduling-framework/)
- Read more about [scheduler configuration](/docs/reference/scheduling/config/)

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