Resource Strategy Fit 插件用户指南

简介

Resource Strategy Fit 插件是 Volcano 调度器插件，为 Pod 调度提供智能资源分配策略。支持全局配置与 Pod 级注解，以优化不同工作负载的资源利用率。

主要特性

• 多种评分策略：支持 LeastAllocated 与 MostAllocated 策略
• 按资源类型配置：可为 CPU、Memory、GPU 等不同资源类型配置不同策略
• Pod 级覆盖：单个 Pod 可通过注解覆盖全局配置
• 加权评分：通过可配置权重微调各资源的重要性
• 通配符支持：使用通配符模式匹配资源名称

安装

1. 安装 Volcano

请参阅 安装指南 安装 Volcano。

2. 配置插件

更新 Volcano 调度器配置：

kubectl edit cm -n volcano-system volcano-scheduler-configmap

在配置中加入 resource-strategy-fit 插件：

kind: ConfigMap
apiVersion: v1
metadata:
  name: volcano-scheduler-configmap
  namespace: volcano-system
data:
  volcano-scheduler.conf: |
    actions: "reclaim, allocate, backfill, preempt"
    tiers:
    - plugins:
      - name: priority
      - name: gang
      - name: conformance
    - plugins:
      - name: drf
      - name: predicates
      - name: resource-strategy-fit
        arguments:
          resourceStrategyFitWeight: 10
          resources:
            cpu:
              type: "LeastAllocated"
              weight: 1
            memory:
              type: "LeastAllocated"
              weight: 1
            nvidia.com/gpu:
              type: "MostAllocated"
              weight: 2

全局配置

基本配置

插件支持两种主要评分策略：

策略	说明	适用场景
LeastAllocated	优先选择可用资源更多的节点	通用工作负载、负载均衡
MostAllocated	优先选择资源利用率更高的节点	GPU 工作负载、资源集中

配置参数

arguments:
  resourceStrategyFitWeight: 10          # 插件权重（默认：10）
  resources:                              # 按资源类型的配置
    cpu:                                 # 资源名称
      type: "LeastAllocated"             # 评分策略
      weight: 1                          # 资源权重
    memory:
      type: "LeastAllocated"
      weight: 1
    nvidia.com/gpu:
      type: "MostAllocated"
      weight: 2

高级配置示例

1. GPU 优化配置

arguments:
  resourceStrategyFitWeight: 20
  resources:
    cpu:
      type: "LeastAllocated"
      weight: 1
    memory:
      type: "LeastAllocated"
      weight: 1
    nvidia.com/gpu:
      type: "MostAllocated"
      weight: 5
    nvidia.com/gpu/*:                     # 通配符匹配所有 GPU 类型
      type: "MostAllocated"
      weight: 3

2. 混合策略配置

arguments:
  resourceStrategyFitWeight: 15
  resources:
    cpu:
      type: "LeastAllocated"
      weight: 3
    memory:
      type: "MostAllocated"
      weight: 1
    example.com/custom-resource:
      type: "LeastAllocated"
      weight: 2

Pod 级配置

Pod 注解

单个 Pod 可通过注解覆盖全局配置：

注解键	说明	示例
volcano.sh/resource-strategy-scoring-type	覆盖评分策略	"LeastAllocated" 或 "MostAllocated"
volcano.sh/resource-strategy-weight	覆盖资源权重	{"cpu": 2, "memory": 1, "nvidia.com/gpu": 3}

Pod 级示例

1. 为特定 Pod 覆盖策略

apiVersion: v1
kind: Pod
metadata:
  name: gpu-workload
  annotations:
    volcano.sh/resource-strategy-scoring-type: "MostAllocated"
    volcano.sh/resource-strategy-weight: '{"nvidia.com/gpu": 5, "cpu": 1}'
spec:
  containers:
  - name: gpu-container
    image: nvidia/cuda:11.0-runtime
    resources:
      requests:
        nvidia.com/gpu: 1
        cpu: "2"
        memory: "4Gi"
      limits:
        nvidia.com/gpu: 1
        cpu: "2"
        memory: "4Gi"
  schedulerName: volcano

2. 自定义资源权重

apiVersion: v1
kind: Pod
metadata:
  name: custom-resource-pod
  annotations:
    volcano.sh/resource-strategy-scoring-type: "LeastAllocated"
    volcano.sh/resource-strategy-weight: '{"cpu": 3, "memory": 2, "example.com/custom": 5}'
spec:
  containers:
  - name: app
    image: my-app:latest
    resources:
      requests:
        cpu: "1"
        memory: "2Gi"
        example.com/custom: "1"
  schedulerName: volcano

Volcano Job 集成

基本 Volcano Job

apiVersion: batch.volcano.sh/v1alpha1
kind: Job
metadata:
  name: resource-strategy-job
spec:
  minAvailable: 2
  schedulerName: volcano
  plugins:
    env: []
    svc: []
  tasks:
  - replicas: 2
    name: worker
    template:
      metadata:
        annotations:
          volcano.sh/resource-strategy-scoring-type: "LeastAllocated"
          volcano.sh/resource-strategy-weight: '{"cpu": 2, "memory": 1}'
      spec:
        containers:
        - name: worker
          image: my-worker:latest
          resources:
            requests:
              cpu: "2"
              memory: "4Gi"
            limits:
              cpu: "2"
              memory: "4Gi"
        restartPolicy: Never

多 Task、多策略 Job

apiVersion: batch.volcano.sh/v1alpha1
kind: Job
metadata:
  name: mixed-strategy-job
spec:
  minAvailable: 3
  schedulerName: volcano
  plugins:
    env: []
    svc: []
  tasks:
  - replicas: 1
    name: gpu-task
    template:
      metadata:
        annotations:
          volcano.sh/resource-strategy-scoring-type: "MostAllocated"
          volcano.sh/resource-strategy-weight: '{"nvidia.com/gpu": 5, "cpu": 1}'
      spec:
        containers:
        - name: gpu-worker
          image: gpu-app:latest
          resources:
            requests:
              nvidia.com/gpu: 1
              cpu: "1"
              memory: "2Gi"
  - replicas: 2
    name: cpu-task
    template:
      metadata:
        annotations:
          volcano.sh/resource-strategy-scoring-type: "LeastAllocated"
          volcano.sh/resource-strategy-weight: '{"cpu": 3, "memory": 2}'
      spec:
        containers:
        - name: cpu-worker
          image: cpu-app:latest
          resources:
            requests:
              cpu: "2"
              memory: "4Gi"

使用场景

1. GPU 工作负载优化

对 GPU 密集型工作负载，使用 MostAllocated 策略以集中使用 GPU：

# 全局配置
arguments:
  resourceStrategyFitWeight: 20
  resources:
    nvidia.com/gpu:
      type: "MostAllocated"
      weight: 5
    cpu:
      type: "LeastAllocated"
      weight: 1

2. 负载均衡

对通用工作负载，使用 LeastAllocated 策略以均衡分布负载：

# 全局配置
arguments:
  resourceStrategyFitWeight: 10
  resources:
    cpu:
      type: "LeastAllocated"
      weight: 2
    memory:
      type: "LeastAllocated"
      weight: 1

3. 混合工作负载

为不同资源类型组合不同策略：

# 全局配置
arguments:
  resourceStrategyFitWeight: 15
  resources:
    cpu:
      type: "LeastAllocated"
      weight: 3
    memory:
      type: "LeastAllocated"
      weight: 2
    nvidia.com/gpu:
      type: "MostAllocated"
      weight: 5

故障排查

验证插件配置

查看调度器日志，确认插件已正确加载：

kubectl logs -n volcano-system deployment/volcano-scheduler | grep "resource-strategy-fit"

预期输出：

Initialize resource-strategy-fit plugin with configuration: {resourceStrategyFitWeight: 10, resources: {...}}

常见问题

1. 插件未加载：确认调度器配置中已包含该插件
2. 注解无效：检查 Pod 级权重注解的 JSON 格式是否正确
3. 资源未找到：确认资源名称完全匹配（区分大小写）
4. 评分未生效：检查插件权重与各资源权重是否配置正确

调试信息

启用调试日志以查看评分决策：

# 添加到调度器配置
arguments:
  resourceStrategyFitWeight: 10
  # ... 其他配置
  logLevel: 4  # 启用调试日志

最佳实践

1. 优先使用全局配置，保证集群内行为一致
2. 谨慎使用 Pod 级注解，仅用于有特殊需求的工作负载
3. 对比测试不同策略，找到适合业务的配置
4. 应用插件后监控资源利用率
5. 合理设置权重，平衡不同资源类型
6. 结合工作负载特征，在 LeastAllocated 与 MostAllocated 之间选择合适策略