Update resource-bin-packing.md

kubernetes · Oct 12, 2020 · 50404c9 · 50404c9
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diff --git a/content/en/docs/concepts/scheduling-eviction/resource-bin-packing.md b/content/en/docs/concepts/scheduling-eviction/resource-bin-packing.md
@@ -20,7 +20,7 @@ The kube-scheduler can be configured to enable bin packing of resources along wi
 
 ## 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
+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`