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Balance similar node groups between zones

Author: MaciekPytel

Introduction

We have multiple requests from people who want to use node groups with the same instance type, but located in multiple zones for redundancy / HA. Currently Cluster Autoscaler is randomly adding and deleting nodes in those node groups, which results in uneven node distribution across different zones. The goal of this proposal is to introduce mechanism to balance the number of nodes in similar node groups.

Constraints

We want this feature to work reasonably well with any currently supported CA configuration. In particular we want to support both homogenous and heterogenous clusters, allowing the user to easily choose or implement strategy for defining what kind of node should be added (i.e. large instance vs several small instances, etc).

Those goals imply a few more specific constraints that we want to keep:

  • We want to avoid balancing size of node groups composed of different instances (there is no point in trying to balance the number of 2-CPU and 32-CPU machines).
  • We want to respect size limits of each node group. In particular we shouldn't expect that the limits will be the same for corresponding node groups.
  • Some pods may require to run on a specific node group due to using labelSelector on zone label, or anti-affinity. In such cases we must scale the correct node group.
  • Preferably we should avoid implementing this using existing expansion.Strategy interface, as that would likely require non-backward compatible refactor of the interface and we want to allow using this feature with different strategies.
  • User must be able to disable this logic using a flag.

General idea

The general idea behind this proposal is to introduce a concept of "Node Group Set", consisting of one or more of "similar" node groups (the definition of "similar" is provided in separate section). When scaling up we would split the nodes between node groups in the same set to make their size as similar as possible. For example assume node group set made of node groups A (currently 1 node), B (3 nodes), and C (6 nodes). If we needed to add a new node to the cluster it would go to group A. If we needed to add 4 nodes, 3 of them would go to group A and 1 to group B.

Note that this does not guarantee that node groups will always have the same size. Cluster Autoscaler will add exactly as many nodes as are required for pending pods, which may not be divisible by number of node groups in node group set. Additionally we scale down underutilized nodes, which may happen to be in the same node group. Including relative sizes of similar node groups in scale down logic will be covered by a different proposal later on.

Implementation proposal

There will be no change to how expansion options are generated in ScaleUp function. Instead the balancing will be executed after expansion option is chosen by expansion.Strategy and before node group is resized. The high-level algorithm will be as follows:

  1. During loop generating expansion options create a map {node group -> set of pods that pass predicates for this node group}. We already calculate that, just need to store it.
  2. Take expansion option chosen by expansion.Strategy and call it E. Let NG be node group chosen by strategy and K be the number of nodes that need to be added. Let P be the set of all pods that will be scheduled thanks to E.
  3. Find all node groups "similar" to NG and call them NGS.
  4. Check if every pod in P passes scheduler predicates for sample node in every node group in NGS (by checking if P is a subset of set we stored in step 1). Remove from NGS any node group on which at least one pod from P can't be scheduled.
  5. Add NG to NGS.
  6. Get current and maximum size of all node groups in NGS. Split K between node groups as described in example above.
  7. Resize all groups in NGS as per result of step 6.

If the user sets the corresponding flag to 'false' we skip step 3, resulting in a single element in NGS (this makes step 4 no-op and step 6 trivial).

Similar node groups

We will balance size of similar node groups. We want similar groups to consist of machine with the same instance type and with the same set of custom labels. In particular we define "similar" node groups as having:

  • The same Capacity for every resource.
  • Allocatable for each resource within 5% of each other (this number can depend on a few different factors and so it's good to have some minor slack).
  • "Free" resources (defined as Allocatable minus resources used by daemonsets and kube-proxy) for each resource within 5% of each other (this number can depend on a few different factors and so it's good to have some minor slack).
  • The same set of labels, except for zone and hostname labels (defined in https://github.com/kubernetes/kube-state-metrics/blob/master/vendor/k8s.io/api/core/v1/well_known_labels.go)

Other possible solutions and discussion

There are other ways to implement the general idea than the proposed solution. This section lists other options that were considered and discusses pros and cons of each one. Feel free to skip it.

[S1]Split selected expansion option

This is the solution described in "Implementation proposal" section.

Pros:

  • Simplest solution.

Cons:

  • If at least a single pending pod uses zone-based scheduling features the whole scale-up will likely go to a single node group.
  • We add slightly different nodes than those chosen by expansion.Strategy. In particular any zone-based choices made by expansion.Strategy will be discarded.
  • We operate on single node groups when creating expansion options, so maximum scale-up size is limited by maximum size of a single group.

[S2]Update expansion options before choosing them

This idea is somewhat similar to [S1], but the new method would be called on a set of expansion options before expansion.Strategy chooses one. The new method could either modify each option to contain a set of scale-ups on similar node groups.

Pros:

  • Addresses some issues of [S1], but not the issues related to pods using zone-based scheduling.

Cons:

  • To fix issues of [S1] the function processing expansion strategies need to be more complex.
  • Need to update expansion.Option to be based on multiple NodeGroups, not just one. This will make expansion.Strategy considerably more complex and difficult to implement.

[S3]Make a wrapper for cloudeprovider.CloudProvider

This solution would work by implementing a NodeGroupSet wrapper implementing cloudprovider.NodeGroup interface. It would consist of one or more NodeGroups and internally load balance their sizes.

Pros:

  • We could use an aggregated maximum size for all node groups when creating expansion options.
  • We could add additional methods to NodeGroupSet to split pending pods between underlying NodeGroups in a smart way, allowing to deal with pod antiaffinity and zone based label selectors without completely skipping size balancing.

Cons:

  • NodeGroup contract assumes all nodes in NodeGroup are identical. However we want to allow at least different zone labels between node groups in node group set.
  • Actually doing the smart stuff with labelSelectors, etc. will be complex and hard to implement.

[S4]Refactor scale-up logic to include balancing similar node groups

This solution would change how expansion options are generated in core/scale_up.go. The main ScaleUp function could be largely rewritten to take balancing node groups into account.

Pros:

  • Most benefits of [S3].
  • Avoids problems caused by breaking NodeGroup interface contract.

Cons:

  • Complex.
  • Large changes to critical parts of code, most likely to cause regression.

Discussion

A lot of difficulty of the problem comes from the fact that we can have pods who can only schedule on some of the node groups in a given node group set. Such pods require specific config by user (zone-based labelSelector or antiaffinity) and are likely not very common in most clusters. Additionally one can argue that having a majority of pods explicitly specify the zone they want to run in defies the purpose of automatically balancing the size of node groups between zones in the first place.

If we treat those pods as edge case options [S3] and [S4] don't seem very attractive. Their main benefit of options [S3] and [S4] is allowing to deal with such edge cases at the cost of significantly increased complexity.

That leaves options [S1] and [S2]. Once again this is a decision between better handling of difficult cases versus complexity. This time this tradeoff applies mostly to expansion.Strategy interface. So far there are no implementations of this interface that make zone-based decisions and making expansion options more complex (by consisting of a set of NodeGroups) will make all existing strategies more complex as well, for no benefit. So it seems that [S1] is the best available option by virtue of its relative simplicity.