Node-pressure Eviction

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.

The kubelet uses various parameters to make eviction decisions, like the following:

• Eviction signals
• Eviction thresholds
• Monitoring intervals

Eviction signals

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 signal.

The value for memory.available is derived from the cgroupfs instead of tools like 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:

1. nodefs: The node's main filesystem, used for local disk volumes, emptyDir, log storage, and more. For example, nodefs contains /var/lib/kubelet/.
2. 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.

Eviction thresholds

You can specify custom eviction thresholds for the kubelet to use when it makes eviction decisions.

Eviction thresholds have the form [eviction-signal][operator][quantity], where:

• eviction-signal is the eviction signal to use.
• operator is the you want, such as < (less than).
• quantity is the eviction threshold amount, such as 1Gi. The value of quantity must match the quantity representation used by Kubernetes. You can use either literal values or percentages (%).

1. Whether the pod's resource usage exceeds requests
2. Pod Priority
3. The pod's resource usage relative to requests

As a result, kubelet ranks and evicts pods in the following order:

1. BestEffort or Burstable pods where the usage exceeds requests. These pods are evicted based on their Priority and then by how much their usage level exceeds the request.
2. Guaranteed pods and Burstable pods where the usage is less than requests are evicted last, based on their Priority.

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 kubelet and journald) is consuming more resources than were reserved via system-reserved or kube-reserved allocations, and the node only has Guaranteed or 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 inode or PID starvation, it uses the Priority to determine the eviction order, because inodes and PIDs have no requests.

The kubelet sorts pods differently based on whether the node has a dedicated imagefs filesystem:

With imagefs

If nodefs is triggering evictions, the kubelet sorts pods based on nodefs usage (local volumes + logs of all containers).

If imagefs is triggering evictions, the kubelet sorts pods based on the writable layer usage of all containers.

Without imagefs

If 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 1Gi, and then continues to reclaim the minimum amount of 500Mi it until the signal reaches 1.5Gi.

Similarly, the kubelet reclaims the imagefs resource until the imagefs.available signal reaches 102Gi.

The default eviction-minimum-reclaim is 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.

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 oom_score 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 RestartPolicy.

Best practices

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: 10Gi
• Operator wants to reserve 10% of memory capacity for system daemons (kernel, kubelet, etc.)
• 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:

--eviction-hard=memory.available<500Mi
--system-reserved=memory=1.5Gi

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 memory.available signal fall below 500Mi and triggers the threshold.

DaemonSet

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 enough priorityClass in the pod spec. You can also use a lower priorityClass or the default to only allow DaemonSet pods to run when there are enough resources.

Known issues

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 OOMKiller will still be invoked.

You can use the --kernel-memcg-notification flag to enable the memcg notification API on the kubelet to get notified immediately when a threshold is crossed.

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 --kube-reserved and --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 active_file memory 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 counted as 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

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