feat: add kep md

docs/designs/node-resource-fit-plus-scoring.md

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+# Node Resource Fit plus Scheduling
+
+<!-- toc -->
+- [Summary](#summary)
+- [Motivation](#motivation)
+- [Design Consideration](#design-consideration)
+  - [Goals](#goals)
+  - [Non-Goals](#non-goals)
+- [Proposal](#proposal)
+- [Design Details](#design-details)
+  - [NodeResourcesFitPlus](#noderesourcesfitplus)
+  - [ScarceResourceAvoidance](#scarceresourceavoidance)
+  - [Test Plan](#test-plan)
+  - [Graduation Criteria](#graduation-criteria)
+    - [Alpha](#alpha)
+    - [Beta](#beta)
+- [Implementation History](#implementation-history)
+<!-- /toc -->
+
+
+## Summary
+
+The NodeResourcesFit plug-in of native k8s can only adopt a type of strategy for all resources, such as MostRequestedPriority and LeastRequestedPriority. However, in industrial practice, this design does not apply to some scenarios. For example: In AI scenarios, businesses that apply for GPUs prefer to occupy the entire GPU machine first to prevent GPU fragmentation; businesses that apply for CPU & MEM are prioritized and dispersed to non-GPU machines to prevent excessive consumption of CPU & MEM on GPU machines, resulting in real tasks of applying for GPUs. Pending due to insufficient non-GPU resources
+. Therefore, two plugins are extended to solve this common problem.
+
+## Motivation
+case: 
+- GPU tasks take priority over the entire GPU
+- CPU&MEM tasks are distributed to the CPU machine first
+
+## Design Consideration
+
+- The solution is more versatile, not limited to AI clusters or CPU clusters, and not limited to common CPU resources or extended GPU resources.
+
+- Different resource policies can be configured for different cluster types and prioritized in the form of weights.
+
+- Easy to expand
+
+### Goals
+
+- Different types of resources can be configured with different strategies to prioritize them in the form of weights
+
+- Prevent pods that have not applied for scarce resources from being scheduled to nodes with scarce resources.
+
+### Non-Goals
+
+- None.
+
+## Proposal
+
+Extend two plug-ins to meet the above needs
+
+- NodeResourcesFitPlus
+- ScarceResourceAvoidance
+
+## Design Details
+
+### NodeResourcesFitPlus
+
+config：
+```
+resources: 
+  nvidia.com/gpu:
+    type: MostAllocated
+    weight: 2
+  cpu:
+    type: LeastAllocated
+    weight: 1
+  memory:
+    type: LeastAllocated
+    weight: 1
+```
+config description：
+
+![image](/img/node-resource-fit-plus-scoring-en.png)
+
+node score:
+```
+finalScoreNode = [(weight1 * resource1) + (weight2 * resource2) + … + (weightN* resourceN)] /(weight1+weight2+ … +weightN)
+```
+
+### ScarceResourceAvoidance
+config：
+```
+resources: 
+- nvidia.com/gpu 
+```
+config description：
+- Obtain the resource type requested by the pod and the list of resource types that the node can allocate
+- Node redundant resource type = node total resource type - pod application resource type
+- The number of core resource types in the node redundant resource type = the intersection of the node redundant resource type and the core resource type list
+- The more core resource types there are in the redundant resource types of node, the lower the score will be.
+
+node score:
+```
+finalScoreNode = (allocatablesResourcesNum - requestsResourcesNum) * framework.MaxNodeScore / allocatablesResourcesNum
+```
+
+### Test Plan
+
+Comprehensive unit tests will be added to ensure that each functionality works as expected.
+
+### Graduation Criteria
+
+#### Alpha
+
+- Implement the NodeResourcesFitPlus and ScarceResourceAvoidance scheduler plugins
+- Provide a reference implementation of the NodeResourcesFitPlus and ScarceResourceAvoidance
+- Unit tests and integration test
+
+#### Beta
+
+- Add E2E tests.
+- Provide beta-level documentation.
+
+## Implementation History
+
+- 2024-12-24: KEP created

docs/user-manuals/node-resource-fit-plus-scoring.md

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+# Node resource adaptation enhanced scheduling
+
+<!-- toc -->
+- [Summary](#summary)
+- [Motivation](#motivation)
+- [Design Consideration](#design-consideration)
+  - [Goals](#goals)
+  - [Non-Goals](#non-goals)
+- [Proposal](#proposal)
+- [Design Details](#design-details)
+  - [NodeResourcesFitPlus](#noderesourcesfitplus)
+  - [ScarceResourceAvoidance](#scarceresourceavoidance)
+- [Example](#example)
+  - [Scheduler Configuration](#scheduler-configuration)
+  - [GPU](#gpu)
+  - [CPU](#cpu)
+<!-- /toc -->
+
+
+## summary
+
+The NodeResourcesFit plug-in of native k8s can only adopt a type of strategy for all resources, such as MostRequestedPriority and LeastRequestedPriority. However, in industrial practice, this design does not apply to some scenarios. For example: In AI scenarios, businesses that apply for GPUs prefer to occupy the entire GPU machine first to prevent GPU fragmentation; businesses that apply for CPU & MEM are prioritized and dispersed to non-GPU machines to prevent excessive consumption of CPU & MEM on GPU machines, resulting in real tasks of applying for GPUs. Pending due to insufficient non-GPU resources
+. It is therefore hoped that both strategies can be extended to address this business need.
+
+## motivation
+case:
+- GPU tasks take priority over the entire GPU
+- CPU&MEM tasks are distributed to the CPU machine first
+
+## design-consideration
+
+- The solution is more versatile, not limited to AI clusters or CPU clusters, and not limited to common CPU resources or extended GPU resources.
+
+- Different resource policies can be configured for different cluster types and prioritized in the form of weights.
+
+- Easy to expand
+
+### goals
+
+- Different types of resources can be configured with different strategies to prioritize them in the form of weights
+
+- Prevent pods that have not applied for scarce resources from being scheduled to nodes with scarce resources.
+
+### non-goals
+
+- None.
+
+## proposal
+
+Extend two plug-ins to meet the above needs
+
+- NodeResourcesFitPlus
+- ScarceResourceAvoidance
+
+## design-details
+
+### NodeResourcesFitPlus
+config:
+```
+resources: 
+  nvidia.com/gpu:
+    type: MostAllocated
+    weight: 2
+  cpu:
+    type: LeastAllocated
+    weight: 1
+  memory:
+    type: LeastAllocated
+    weight: 1
+```
+config description:
+
+![image](/img/node-resource-fit-plus-scoring-en.png)
+
+node score:
+```
+finalScoreNode = [(weight1 * resource1) + (weight2 * resource2) + … + (weightN* resourceN)] /(weight1+weight2+ … +weightN)
+```
+
+### ScarceResourceAvoidance
+config:
+```
+resources: 
+- nvidia.com/gpu 
+```
+config description:
+- Obtain the resource type requested by the pod and the list of resource types that the node can allocate
+- Node redundant resource type = node total resource type - pod application resource type
+- The number of core resource types in the node redundant resource type = the intersection of the node redundant resource type and the core resource type list
+- The more core resource types there are in the redundant resource types of node, the lower the score will be.
+
+node score:
+```
+finalScoreNode = (allocatablesResourcesNum - requestsResourcesNum) * framework.MaxNodeScore / allocatablesResourcesNum
+```
+
+## example
+### scheduler-configuration
+
+```
+
+profiles:
+- pluginConfig:
+  - args:
+      apiVersion: kubescheduler.config.k8s.io/v1beta2
+      kind: ResourceTypesArgs
+      resources: 
+        nvidia.com/gpu:
+          type: MostAllocated
+          weight: 2
+        cpu:
+          type: LeastAllocated
+          weight: 1
+        memory:
+          type: LeastAllocated
+          weight: 1
+    name: NodeResourcesFitPlus
+  - args:
+      resources: 
+      - nvidia.com/gpu
+    name: ScarceResourceAvoidance
+  plugins:
+    score:
+      enabled:
+      - name: NodeResourcesFitPlus
+        weight: 2
+      - name: ScarceResourceAvoidance
+        weight: 2
+      disabled:
+      - name: "*"
+  schedulerName: koord-scheduler
+```
+
+### gpu
+
+deployment Resource application
+
+```
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: test-scheduler1
+spec:
+  replicas: 1
+  selector:
+    matchLabels:
+      app: test-scheduler1
+  template:
+    metadata:
+      labels:
+        app: test-scheduler1
+    spec:
+      schedulerName: koord-scheduler
+      containers:
+        - image: dockerpull.com/nginx
+          imagePullPolicy: IfNotPresent
+          name: nginx
+          ports:
+            - containerPort: 80
+          resources:
+            requests:
+              cpu: "100"
+              memory: "100"
+              nvidia.com/gpu: 2
+            limits:
+              cpu: "100"
+              memory: "100"
+              nvidia.com/gpu: 2
+```
+
+Node allocation rate information
+```
+node1: cpu 58%, memory 21%, nvidia.com/gpu 6 (total 8)
+
+node2: cpu 22%, memory 5%, nvidia.com/gpu 0 (total 8)
+```
+
+Result: Prioritize GPU machines and pool GPU resources
+
+Log view => ```Top10 scores for pod```
+```
+| # | Pod | Node | Score | NodeResourcesFitPlus | ScarceResourceAvoidance |
+| 0 | test-scheduler1-xxx | node1 | 358 | 158 | 200 |
+| 1 | test-scheduler1-xxx | node2 | 296 | 96 | 200 |
+```
+
+### cpu
+
+deployment Resource application
+
+```
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: test-scheduler1
+spec:
+  replicas: 1
+  selector:
+    matchLabels:
+      app: test-scheduler1
+  template:
+    metadata:
+      labels:
+        app: test-scheduler1
+    spec:
+      schedulerName: koord-scheduler
+      containers:
+        - image: dockerpull.com/nginx
+          imagePullPolicy: IfNotPresent
+          name: nginx
+          ports:
+            - containerPort: 80
+          resources:
+            requests:
+              cpu: "100"
+              memory: "100"
+            limits:
+              cpu: "100"
+              memory: "100"
+```
+
+Node allocation rate information
+```
+node1: cpu 22%, memory 10%, nvidia.com/gpu 6 (total 8)
+node2: cpu 40%, memory 50%
+node3: cpu 30%, memory 20%
+```
+
+Result: Prioritize CPU machines and disperse CPU and MEM resources
+
+Log view => ```Top10 scores for pod```
+```
+| # | Pod | Node | Score | NodeResourcesFitPlus | ScarceResourceAvoidance |
+| 0 | test-scheduler1-xxx | node1 | 310 | 144 | 166 |
+| 1 | test-scheduler1-xxx | node2 | 262 | 62 | 200 |
+| 2 | test-scheduler1-xxx | node3 | 326 | 126 | 200 |
+```