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Scheduling Framework

FEATURE STATE: Kubernetes v1.15 [alpha]

The scheduling framework is a pluggable architecture for Kubernetes Scheduler that makes scheduler customizations easy. It adds a new set of "plugin" APIs to the existing scheduler. Plugins are compiled into the scheduler. The APIs allow most scheduling features to be implemented as plugins, while keeping the scheduling "core" simple and maintainable. Refer to the design proposal of the scheduling framework for more technical information on the design of the framework.

Framework workflow

The Scheduling Framework defines a few extension points. Scheduler plugins register to be invoked at one or more extension points. Some of these plugins can change the scheduling decisions and some are informational only.

Each attempt to schedule one Pod is split into two phases, the scheduling cycle and the binding cycle.

Scheduling Cycle & Binding Cycle

The scheduling cycle selects a node for the Pod, and the binding cycle applies that decision to the cluster. Together, a scheduling cycle and binding cycle are referred to as a "scheduling context".

Scheduling cycles are run serially, while binding cycles may run concurrently.

A scheduling or binding cycle can be aborted if the Pod is determined to be unschedulable or if there is an internal error. The Pod will be returned to the queue and retried.

Extension points

The following picture shows the scheduling context of a Pod and the extension points that the scheduling framework exposes. In this picture "Filter" is equivalent to "Predicate" and "Scoring" is equivalent to "Priority function".

One plugin may register at multiple extension points to perform more complex or stateful tasks.

scheduling framework extension points


These plugins are used to sort Pods in the scheduling queue. A queue sort plugin essentially provides a Less(Pod1, Pod2) function. Only one queue sort plugin may be enabled at a time.


These plugins are used to pre-process info about the Pod, or to check certain conditions that the cluster or the Pod must meet. If a PreFilter plugin returns an error, the scheduling cycle is aborted.


These plugins are used to filter out nodes that cannot run the Pod. For each node, the scheduler will call filter plugins in their configured order. If any filter plugin marks the node as infeasible, the remaining plugins will not be called for that node. Nodes may be evaluated concurrently.


These plugins are called after Filter phase, but only when no feasible nodes were found for the node. Plugins are called in their configured order. If any postFilter plugin marks the node as Schedulable, the remaining plugins will not be called. A typical PostFilter implementation is preemption, which tries to make the pod schedulable by preempting other Pods.


These plugins are used to perform "pre-scoring" work, which generates a sharable state for Score plugins to use. If a PreScore plugin returns an error, the scheduling cycle is aborted.


These plugins are used to rank nodes that have passed the filtering phase. The scheduler will call each scoring plugin for each node. There will be a well defined range of integers representing the minimum and maximum scores. After the NormalizeScore phase, the scheduler will combine node scores from all plugins according to the configured plugin weights.


These plugins are used to modify scores before the scheduler computes a final ranking of Nodes. A plugin that registers for this extension point will be called with the Score results from the same plugin. This is called once per plugin per scheduling cycle.

For example, suppose a plugin BlinkingLightScorer ranks Nodes based on how many blinking lights they have.

func ScoreNode(_ *v1.pod, n *v1.Node) (int, error) {
    return getBlinkingLightCount(n)

However, the maximum count of blinking lights may be small compared to NodeScoreMax. To fix this, BlinkingLightScorer should also register for this extension point.

func NormalizeScores(scores map[string]int) {
    highest := 0
    for _, score := range scores {
        highest = max(highest, score)
    for node, score := range scores {
        scores[node] = score*NodeScoreMax/highest

If any NormalizeScore plugin returns an error, the scheduling cycle is aborted.

Note: Plugins wishing to perform "pre-reserve" work should use the NormalizeScore extension point.


A plugin that implements the Reserve extension has two methods, namely Reserve and Unreserve, that back two informational scheduling phases called Reserve and Unreserve, respectively. Plugins which maintain runtime state (aka "stateful plugins") should use these phases to be notified by the scheduler when resources on a node are being reserved and unreserved for a given Pod.

The Reserve phase happens before the scheduler actually binds a Pod to its designated node. It exists to prevent race conditions while the scheduler waits for the bind to succeed. The Reserve method of each Reserve plugin may succeed or fail; if one Reserve method call fails, subsequent plugins are not executed and the Reserve phase is considered to have failed. If the Reserve method of all plugins succeed, the Reserve phase is considered to be successful and the rest of the scheduling cycle and the binding cycle are executed.

The Unreserve phase is triggered if the Reserve phase or a later phase fails. When this happens, the Unreserve method of all Reserve plugins will be executed in the reverse order of Reserve method calls. This phase exists to clean up the state associated with the reserved Pod.

Caution: The implementation of the Unreserve method in Reserve plugins must be idempotent and may not fail.


Permit plugins are invoked at the end of the scheduling cycle for each Pod, to prevent or delay the binding to the candidate node. A permit plugin can do one of the three things:

  1. approve
    Once all Permit plugins approve a Pod, it is sent for binding.

  2. deny
    If any Permit plugin denies a Pod, it is returned to the scheduling queue. This will trigger the Unreserve phase in Reserve plugins.

  3. wait (with a timeout)
    If a Permit plugin returns "wait", then the Pod is kept in an internal "waiting" Pods list, and the binding cycle of this Pod starts but directly blocks until it gets approved. If a timeout occurs, wait becomes deny and the Pod is returned to the scheduling queue, triggering the Unreserve phase in Reserve plugins.

Note: While any plugin can access the list of "waiting" Pods and approve them (see FrameworkHandle), we expect only the permit plugins to approve binding of reserved Pods that are in "waiting" state. Once a Pod is approved, it is sent to the PreBind phase.


These plugins are used to perform any work required before a Pod is bound. For example, a pre-bind plugin may provision a network volume and mount it on the target node before allowing the Pod to run there.

If any PreBind plugin returns an error, the Pod is rejected and returned to the scheduling queue.


These plugins are used to bind a Pod to a Node. Bind plugins will not be called until all PreBind plugins have completed. Each bind plugin is called in the configured order. A bind plugin may choose whether or not to handle the given Pod. If a bind plugin chooses to handle a Pod, the remaining bind plugins are skipped.


This is an informational extension point. Post-bind plugins are called after a Pod is successfully bound. This is the end of a binding cycle, and can be used to clean up associated resources.

Plugin API

There are two steps to the plugin API. First, plugins must register and get configured, then they use the extension point interfaces. Extension point interfaces have the following form.

type Plugin interface {
    Name() string

type QueueSortPlugin interface {
    Less(*v1.pod, *v1.pod) bool

type PreFilterPlugin interface {
    PreFilter(context.Context, *framework.CycleState, *v1.pod) error

// ...

Plugin configuration

You can enable or disable plugins in the scheduler configuration. If you are using Kubernetes v1.18 or later, most scheduling plugins are in use and enabled by default.

In addition to default plugins, you can also implement your own scheduling plugins and get them configured along with default plugins. You can visit scheduler-plugins for more details.

If you are using Kubernetes v1.18 or later, you can configure a set of plugins as a scheduler profile and then define multiple profiles to fit various kinds of workload. Learn more at multiple profiles.