因此,这是我试图在K8S节点资源方面使用的示例场景。
假设我们有3个(Worker)节点 - 相同类型 - 分配了这些资源请求:
我希望理想地重新平衡节点(节点上的PODS),以便我可以删除N3(或其中任何一个):
- n1:70% + 20%从N3
- N2:60% + 30%的N3
- N3:要删除
(所有数字都是假设和简化的,我只想到达最少浪费
/
我正在查看 )) nofollow noreferrer“> descheduler 可能有助于使用节点/群集。
我正在考虑设置阈值
= targetThresholds
= 90%(或类似的东西) lownodeutilization 策略,然后使用或 claster autoscaler 降低群集(ie)删除节点)
- 我不清楚是否可以使用多个
策略
descheduler
(如果是的,则是什么优先级),
- 我应该使用
HighnoDeutilization
>或集群Autoscaler
用于缩小的尺寸?
对这种方法(或任何其他建议)的任何评论/反馈都将受到赞赏。
So here's a sample scenario I'm trying to utilize in terms of K8s node resources.
Let's say we have 3 (worker) nodes - same type - with these resource requests allocated:
I'd like to ideally rebalance the nodes (pods on the node) so it I can delete N3 (or any one of them):
- N1: 70% + 20% from N3
- N2: 60% + 30% from N3
- N3: to be deleted
(all numbers are hypothetical and simplified, I just wanna get to the least waste
/least number of nodes required for this)
I'm looking at the descheduler which could potentially help to utilize the nodes/cluster.
I'm thinking to set the threshold
= targetThresholds
= 90% (or something similar) in LowNodeUtilization policy, and then use either HighNodeUtilization or Cluster Autoscaler to downsize the cluster (i.e. remove the node)
- I'm not clear if I can use multiple
strategies
for descheduler
(if so, what's the precedence)
- Should I use the
HighNodeUtilization
or Cluster Autoscaler
for downsizing?
Any comment/feedback on this approach (or any other suggestion) is appreciated.
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