What is the optimal scheduling strategy for K8s pods?

4/24/2020

Here is what I am working with. I have 3 nodepools on GKE

  1. n1s1 (3.75GB)
  2. n1s2 (7.5GB)
  3. n1s4 (15GB)

I have pods that will require any of the following memory requests. Assume limits are very close to requests.

1GB, 2GB, 4GB, 6GB, 8GB, 10GB, 12GB, 14GB

How best can I associate a pod to a nodepool for max efficiency?

So far I have 3 strategies.

For each pod config, determine the “rightful nodepool”. This is the smallest nodepool that can accommodate the pod config in an ideal world. So for 2GB pod it's n1s1 but for 4GB pod it'd be n1s2.

  1. Schedule a pod only on its rightful nodepool.
  2. Schedule a pod only on its rightful nodepool or one nodepool higher than that.
  3. Schedule a pod only on any nodepool where it can currently go.

Which of these or any other strategies will minimize wasting resources?

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-- crossvalidator
kubernetes
scheduling

2 Answers

4/24/2020

Why would you have 3 pools like that in the first place? You generally want to use the largest instance type you can that gets you under 110 pods per node (which is the default hard cap). The job of the scheduler is to optimize the packing for you, and it's pretty good at that with the default settings.

-- coderanger
Source: StackOverflow

4/27/2020

I would use a mix of Taints and Tolerations and Node affinity.

Taints and tolerations work together to ensure that pods are not scheduled onto inappropriate nodes. One or more taints are applied to a node; this marks that the node should not accept any pods that do not tolerate the taints. Tolerations are applied to pods, and allow (but do not require) the pods to schedule onto nodes with matching taints.

You can set a taint on a node kubectl taint nodes node1 key=value:NoSchedule

The taint has key key, value value, and taint effect NoSchedule. This means that no pod will be able to schedule onto node1 unless it has a matching toleration.

While you are writing a pod yaml you can specify PodSpec and add toleration which will match the taint created on node1 which will allow pod with either toleration to be scheduled onto node1

tolerations:
- key: "key"
  operator: "Equal"
  value: "value"
  effect: "NoSchedule"

or

tolerations:
- key: "key"
  operator: "Exists"
  effect: "NoSchedule"

Taints and tolerations are a flexible way to steer pods away from nodes or evict pods that shouldn’t be running. A few of the use cases are

  • Dedicated Nodes: If you want to dedicate a set of nodes for exclusive use by a particular set of users, you can add a taint to those nodes (say, kubectl taint nodes nodename dedicated=groupName:NoSchedule) and then add a corresponding toleration to their pods (this would be done most easily by writing a custom admission controller). The pods with the tolerations will then be allowed to use the tainted (dedicated) nodes as well as any other nodes in the cluster. If you want to dedicate the nodes to them and ensure they only use the dedicated nodes, then you should additionally add a label similar to the taint to the same set of nodes (e.g. dedicated=groupName), and the admission controller should additionally add a node affinity to require that the pods can only schedule onto nodes labeled with dedicated=groupName.

  • Nodes with Special Hardware: In a cluster where a small subset of nodes have specialized hardware (for example GPUs), it is desirable to keep pods that don’t need the specialized hardware off of those nodes, thus leaving room for later-arriving pods that do need the specialized hardware. This can be done by tainting the nodes that have the specialized hardware (e.g. kubectl taint nodes nodename special=true:NoSchedule or kubectl taint nodes nodename special=true:PreferNoSchedule) and adding a corresponding toleration to pods that use the special hardware. As in the dedicated nodes use case, it is probably easiest to apply the tolerations using a custom admission controller. For example, it is recommended to use Extended Resources to represent the special hardware, taint your special hardware nodes with the extended resource name and run the ExtendedResourceToleration admission controller. Now, because the nodes are tainted, no pods without the toleration will schedule on them. But when you submit a pod that requests the extended resource, the ExtendedResourceToleration admission controller will automatically add the correct toleration to the pod and that pod will schedule on the special hardware nodes. This will make sure that these special hardware nodes are dedicated for pods requesting such hardware and you don’t have to manually add tolerations to your pods.

  • Taint based Evictions: A per-pod-configurable eviction behavior when there are node problems, which is described in the next section.

As for node affinity:

is conceptually similar to nodeSelector – it allows you to constrain which nodes your pod is eligible to be scheduled on, based on labels on the node.

There are currently two types of node affinity, called requiredDuringSchedulingIgnoredDuringExecution and preferredDuringSchedulingIgnoredDuringExecution. You can think of them as “hard” and “soft” respectively, in the sense that the former specifies rules that must be met for a pod to be scheduled onto a node (just like nodeSelector but using a more expressive syntax), while the latter specifies preferences that the scheduler will try to enforce but will not guarantee. The “IgnoredDuringExecution” part of the names means that, similar to how nodeSelector works, if labels on a node change at runtime such that the affinity rules on a pod are no longer met, the pod will still continue to run on the node. In the future we plan to offer requiredDuringSchedulingRequiredDuringExecution which will be just like requiredDuringSchedulingIgnoredDuringExecution except that it will evict pods from nodes that cease to satisfy the pods’ node affinity requirements.

Thus an example of requiredDuringSchedulingIgnoredDuringExecution would be “only run the pod on nodes with Intel CPUs” and an example preferredDuringSchedulingIgnoredDuringExecution would be “try to run this set of pods in failure zone XYZ, but if it’s not possible, then allow some to run elsewhere”.

Node affinity is specified as field nodeAffinity of field affinity in the PodSpec.

...

The new node affinity syntax supports the following operators: In, NotIn, Exists, DoesNotExist, Gt, Lt. You can use NotIn and DoesNotExist to achieve node anti-affinity behavior, or use node taints to repel pods from specific nodes.

If you specify both nodeSelector and nodeAffinity, both must be satisfied for the pod to be scheduled onto a candidate node.

If you specify multiple nodeSelectorTerms associated with nodeAffinity types, then the pod can be scheduled onto a node only if all nodeSelectorTerms can be satisfied.

If you specify multiple matchExpressions associated with nodeSelectorTerms, then the pod can be scheduled onto a node if one of the matchExpressions is satisfied.

-- Crou
Source: StackOverflow