Node-pressure eviction is the process by which the kubelet proactively terminates pods to reclaim resources on nodes.
The kubelet monitors resources like CPU, memory, disk space, and filesystem inodes on your cluster's nodes. When one or more of these resources reach specific consumption levels, the kubelet can proactively fail one or more pods on the node to reclaim resources and prevent starvation.
During a node-pressure eviction, the kubelet sets the
PodPhase for the
selected pods to
Failed. This terminates the pods.
Node-pressure eviction is not the same as API-initiated eviction.
The kubelet does not respect your configured
PodDisruptionBudget or the pod's
terminationGracePeriodSeconds. If you use soft eviction thresholds,
the kubelet respects your configured
eviction-max-pod-grace-period. If you use
hard eviction thresholds, it uses a
0s grace period for termination.
If the pods are managed by a workload
resource (such as StatefulSet
or Deployment) that
replaces failed pods, the control plane or
kube-controller-manager creates new
pods in place of the evicted pods.
Note: The kubelet attempts to reclaim node-level resources before it terminates end-user pods. For example, it removes unused container images when disk resources are starved.
The kubelet uses various parameters to make eviction decisions, like the following:
- Eviction signals
- Eviction thresholds
- Monitoring intervals
Eviction signals are the current state of a particular resource at a specific point in time. Kubelet uses eviction signals to make eviction decisions by comparing the signals to eviction thresholds, which are the minimum amount of the resource that should be available on the node.
Kubelet uses the following eviction signals:
In this table, the
Description column shows how kubelet gets the value of the
signal. Each signal supports either a percentage or a literal value. Kubelet
calculates the percentage value relative to the total capacity associated with
The value for
memory.available is derived from the cgroupfs instead of tools
free -m. This is important because
free -m does not work in a
container, and if users use the node
allocatable feature, out of resource decisions
are made local to the end user Pod part of the cgroup hierarchy as well as the
root node. This script
reproduces the same set of steps that the kubelet performs to calculate
memory.available. The kubelet excludes inactive_file (i.e. # of bytes of
file-backed memory on inactive LRU list) from its calculation as it assumes that
memory is reclaimable under pressure.
The kubelet supports the following filesystem partitions:
nodefs: The node's main filesystem, used for local disk volumes, emptyDir, log storage, and more. For example,
imagefs: An optional filesystem that container runtimes use to store container images and container writable layers.
Kubelet auto-discovers these filesystems and ignores other filesystems. Kubelet does not support other configurations.
Note: Some kubelet garbage collection features are deprecated in favor of eviction. For a list of the deprecated features, see kubelet garbage collection deprecation.
You can specify custom eviction thresholds for the kubelet to use when it makes eviction decisions.
Eviction thresholds have the form
eviction-signalis the eviction signal to use.
operatoris the relational operator you want, such as
quantityis the eviction threshold amount, such as
1Gi. The value of
quantitymust match the quantity representation used by Kubernetes. You can use either literal values or percentages (
For example, if a node has
10Gi of total memory and you want trigger eviction if
the available memory falls below
1Gi, you can define the eviction threshold as
memory.available<1Gi. You cannot use both.
You can configure soft and hard eviction thresholds.
Soft eviction thresholds
A soft eviction threshold pairs an eviction threshold with a required administrator-specified grace period. The kubelet does not evict pods until the grace period is exceeded. The kubelet returns an error on startup if there is no specified grace period.
You can specify both a soft eviction threshold grace period and a maximum allowed pod termination grace period for kubelet to use during evictions. If you specify a maximum allowed grace period and the soft eviction threshold is met, the kubelet uses the lesser of the two grace periods. If you do not specify a maximum allowed grace period, the kubelet kills evicted pods immediately without graceful termination.
You can use the following flags to configure soft eviction thresholds:
eviction-soft: A set of eviction thresholds like
memory.available<1.5Githat can trigger pod eviction if held over the specified grace period.
eviction-soft-grace-period: A set of eviction grace periods like
memory.available=1m30sthat define how long a soft eviction threshold must hold before triggering a Pod eviction.
eviction-max-pod-grace-period: The maximum allowed grace period (in seconds) to use when terminating pods in response to a soft eviction threshold being met.
Hard eviction thresholds
A hard eviction threshold has no grace period. When a hard eviction threshold is met, the kubelet kills pods immediately without graceful termination to reclaim the starved resource.
You can use the
eviction-hard flag to configure a set of hard eviction
The kubelet has the following default hard eviction thresholds:
Eviction monitoring interval
The kubelet evaluates eviction thresholds based on its configured
which defaults to
The kubelet reports node conditions to reflect that the node is under pressure because hard or soft eviction threshold is met, independent of configured grace periods.
The kubelet maps eviction signals to node conditions as follows:
|Node Condition||Eviction Signal||Description|
||Available memory on the node has satisfied an eviction threshold|
||Available disk space and inodes on either the node's root filesystem or image filesystem has satisfied an eviction threshold|
||Available processes identifiers on the (Linux) node has fallen below an eviction threshold|
The kubelet updates the node conditions based on the configured
--node-status-update-frequency, which defaults to
Node condition oscillation
In some cases, nodes oscillate above and below soft eviction thresholds without
holding for the defined grace periods. This causes the reported node condition
to constantly switch between
false, leading to bad eviction decisions.
To protect against oscillation, you can use the
flag, which controls how long the kubelet must wait before transitioning a node
condition to a different state. The transition period has a default value of
Reclaiming node level resources
The kubelet tries to reclaim node-level resources before it evicts end-user pods.
DiskPressure node condition is reported, the kubelet reclaims node-level
resources based on the filesystems on the node.
If the node has a dedicated
imagefs filesystem for container runtimes to use,
the kubelet does the following:
- If the
nodefsfilesystem meets the eviction threshlds, the kubelet garbage collects dead pods and containers.
- If the
imagefsfilesystem meets the eviction thresholds, the kubelet deletes all unused images.
If the node only has a
nodefs filesystem that meets eviction thresholds,
the kubelet frees up disk space in the following order:
- Garbage collect dead pods and containers
- Delete unused images
Pod selection for kubelet eviction
If the kubelet's attempts to reclaim node-level resources don't bring the eviction signal below the threshold, the kubelet begins to evict end-user pods.
The kubelet uses the following parameters to determine pod eviction order:
- Whether the pod's resource usage exceeds requests
- Pod Priority
- The pod's resource usage relative to requests
As a result, kubelet ranks and evicts pods in the following order:
Burstablepods where the usage exceeds requests. These pods are evicted based on their Priority and then by how much their usage level exceeds the request.
Burstablepods where the usage is less than requests are evicted last, based on their Priority.
Note: The kubelet does not use the pod's QoS class to determine the eviction order. You can use the QoS class to estimate the most likely pod eviction order when reclaiming resources like memory. QoS does not apply to EphemeralStorage requests, so the above scenario will not apply if the node is, for example, under
Guaranteed pods are guaranteed only when requests and limits are specified for
all the containers and they are equal. These pods will never be evicted because
of another pod's resource consumption. If a system daemon (such as
journald) is consuming more resources than were reserved via
kube-reserved allocations, and the node only has
Burstable pods using less resources than requests left on it,
then the kubelet must choose to evict one of these pods to preserve node stability
and to limit the impact of resource starvation on other pods. In this case, it
will choose to evict pods of lowest Priority first.
When the kubelet evicts pods in response to
PID starvation, it uses
the Priority to determine the eviction order, because
PIDs have no
The kubelet sorts pods differently based on whether the node has a dedicated
nodefs is triggering evictions, the kubelet sorts pods based on
local volumes + logs of all containers).
imagefs is triggering evictions, the kubelet sorts pods based on the
writable layer usage of all containers.
nodefs is triggering evictions, the kubelet sorts pods based on their total
disk usage (
local volumes + logs & writable layer of all containers)
Minimum eviction reclaim
In some cases, pod eviction only reclaims a small amount of the starved resource. This can lead to the kubelet repeatedly hitting the configured eviction thresholds and triggering multiple evictions.
You can use the
--eviction-minimum-reclaim flag or a kubelet config file
to configure a minimum reclaim amount for each resource. When the kubelet notices
that a resource is starved, it continues to reclaim that resource until it
reclaims the quantity you specify.
For example, the following configuration sets minimum reclaim amounts:
apiVersion: kubelet.config.k8s.io/v1beta1 kind: KubeletConfiguration evictionHard: memory.available: "500Mi" nodefs.available: "1Gi" imagefs.available: "100Gi" evictionMinimumReclaim: memory.available: "0Mi" nodefs.available: "500Mi" imagefs.available: "2Gi"
In this example, if the
nodefs.available signal meets the eviction threshold,
the kubelet reclaims the resource until the signal reaches the threshold of
and then continues to reclaim the minimum amount of
500Mi it until the signal
Similarly, the kubelet reclaims the
imagefs resource until the
0 for all resources.
Node out of memory behavior
If the node experiences an out of memory (OOM) event prior to the kubelet being able to reclaim memory, the node depends on the oom_killer to respond.
The kubelet sets an
oom_score_adj value for each container based on the QoS for the pod.
|Quality of Service||oom_score_adj|
||min(max(2, 1000 - (1000 * memoryRequestBytes) / machineMemoryCapacityBytes), 999)|
Note: The kubelet also sets an
-997for containers in Pods that have
If the kubelet can't reclaim memory before a node experiences OOM, the
oom_killer calculates an
oom_score based on the percentage of memory it's
using on the node, and then adds the
oom_score_adj to get an effective
for each container. It then kills the container with the highest score.
This means that containers in low QoS pods that consume a large amount of memory relative to their scheduling requests are killed first.
Unlike pod eviction, if a container is OOM killed, the
kubelet can restart it
based on its
The following sections describe best practices for eviction configuration.
Schedulable resources and eviction policies
When you configure the kubelet with an eviction policy, you should make sure that the scheduler will not schedule pods if they will trigger eviction because they immediately induce memory pressure.
Consider the following scenario:
- Node memory capacity:
- Operator wants to reserve 10% of memory capacity for system daemons (kernel,
- Operator wants to evict Pods at 95% memory utilization to reduce incidence of system OOM.
For this to work, the kubelet is launched as follows:
In this configuration, the
--system-reserved flag reserves
1.5Gi of memory
for the system, which is
10% of the total memory + the eviction threshold amount.
The node can reach the eviction threshold if a pod is using more than its request,
or if the system is using more than
1Gi of memory, which makes the
signal fall below
500Mi and triggers the threshold.
Pod Priority is a major factor in making eviction decisions. If you do not want
the kubelet to evict pods that belong to a
DaemonSet, give those pods a high
priorityClass in the pod spec. You can also use a lower
or the default to only allow
DaemonSet pods to run when there are enough
The following sections describe known issues related to out of resource handling.
kubelet may not observe memory pressure right away
By default, the kubelet polls
cAdvisor to collect memory usage stats at a
regular interval. If memory usage increases within that window rapidly, the
kubelet may not observe
MemoryPressure fast enough, and the
will still be invoked.
You can use the
--kernel-memcg-notification flag to enable the
notification API on the kubelet to get notified immediately when a threshold
If you are not trying to achieve extreme utilization, but a sensible measure of
overcommit, a viable workaround for this issue is to use the
--system-reserved flags to allocate memory for the system.
active_file memory is not considered as available memory
On Linux, the kernel tracks the number of bytes of file-backed memory on active
LRU list as the
active_file statistic. The kubelet treats
areas as not reclaimable. For workloads that make intensive use of block-backed
local storage, including ephemeral local storage, kernel-level caches of file
and block data means that many recently accessed cache pages are likely to be
active_file. If enough of these kernel block buffers are on the
active LRU list, the kubelet is liable to observe this as high resource use and
taint the node as experiencing memory pressure - triggering pod eviction.
For more more details, see https://github.com/kubernetes/kubernetes/issues/43916
You can work around that behavior by setting the memory limit and memory request the same for containers likely to perform intensive I/O activity. You will need to estimate or measure an optimal memory limit value for that container.
- Learn about API-initiated Eviction
- Learn about Pod Priority and Preemption
- Learn about PodDisruptionBudgets
- Learn about Quality of Service (QoS)
- Check out the Eviction API