Comments (1)
你提供的内容中包含一些错误,以下是修正后的内容:
是的,实际上 averageUtilization 和 averageValue 的触发条件在逻辑上是相似的,区别在于:
• averageUtilization:以百分比形式表示,目标是所有 Pod 的平均利用率。
• averageValue:以具体的资源值(如内存量)表示,目标是所有 Pod 的平均资源使用量。
配置示例
假设目标是内存利用率的 80%,即 averageUtilization: 80,我们来计算具体的扩缩条件。
扩容和缩容条件
- 从 1 个副本扩容到 2 个副本的条件:
• 内存使用达到 88%。
• 公式:
- 从 2 个副本扩容到 3 个副本的条件:
• 内存使用达到 88%。
• 公式:
- 从 3 个副本缩容到 2 个副本的条件:
• 内存使用降至 53%。
• 公式:
- 从 2 个副本缩容到 1 个副本的条件:
• 内存使用降至 40%。
• 公式:
配置示例
apiVersion: autoscaling/v2beta2
kind: HorizontalPodAutoscaler
metadata:
name: hpa-memory-utilization
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: your-deployment-name
minReplicas: 1
maxReplicas: 10
metrics:
- type: Resource
resource:
name: memory
target:
type: Utilization
averageUtilization: 80
behavior:
scaleUp:
stabilizationWindowSeconds: 300 # 300 秒的扩容稳定窗口期
policies:
- type: Pods
value: 2 # 每次最多扩展 2 个 Pod
periodSeconds: 60 # 每 60 秒检查一次
selectPolicy: Max
scaleDown:
stabilizationWindowSeconds: 300 # 300 秒的缩容稳定窗口期
policies:
- type: Pods
value: 1 # 每次最多缩减 1 个 Pod
periodSeconds: 60 # 每 60 秒检查一次
selectPolicy: Min
解释
• averageUtilization:HPA 会根据所有 Pod 的平均内存使用率进行扩缩容操作。
• 扩容和缩容的触发条件:通过配置扩容和缩容的触发条件,可以确保在内存使用量达到特定比例时进行扩容或缩容操作。
对比 averageUtilization 和 averageValue
本质上,averageUtilization 和 averageValue 在触发扩缩容的条件和逻辑上是类似的。不同的是,averageUtilization 使用百分比形式,而 averageValue 使用具体值。两者都遵循相同的公式来计算所需的副本数。
总结
无论使用 averageUtilization 还是 averageValue,HPA 的扩缩容机制都基于当前的实际指标值和目标值的比率进行计算和调整。因此,它们在触发条件和行为上没有本质区别,只是表示方式不同。通过正确配置 behavior 字段,你可以更精细地控制扩缩容的行为,以满足具体的需求。
from groovy.
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