Configure Out of Resource Handling
This page explains how to configure out of resource handling with kubelet
.
The kubelet
needs to preserve node stability when available compute resources are low. This is especially important when dealing with incompressible compute resources, such as memory or disk space. If such resources are exhausted, nodes become unstable.
Eviction Signals
The kubelet
supports eviction decisions based on the signals described in the following table. The value of each signal is described in the Description column, which is based on the kubelet
summary API.
Eviction Signal | Description |
---|---|
memory.available | memory.available := node.status.capacity[memory] - node.stats.memory.workingSet |
nodefs.available | nodefs.available := node.stats.fs.available |
nodefs.inodesFree | nodefs.inodesFree := node.stats.fs.inodesFree |
imagefs.available | imagefs.available := node.stats.runtime.imagefs.available |
imagefs.inodesFree | imagefs.inodesFree := node.stats.runtime.imagefs.inodesFree |
pid.available | pid.available := node.stats.rlimit.maxpid - node.stats.rlimit.curproc |
Each of the above signals supports either a literal or percentage based value. The percentage based value is calculated relative to the total capacity associated with each 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.
kubelet
supports only two filesystem partitions.
- The
nodefs
filesystem that kubelet uses for volumes, daemon logs, etc. - The
imagefs
filesystem that container runtimes uses for storing images and container writable layers.
imagefs
is optional. kubelet
auto-discovers these filesystems using cAdvisor. kubelet
does not care about any other filesystems. Any other types of configurations are not currently supported by the kubelet. For example, it is not OK to store volumes and logs in a dedicated filesystem
.
In future releases, the kubelet
will deprecate the existing garbage collection support in favor of eviction in response to disk pressure.
Eviction Thresholds
The kubelet
supports the ability to specify eviction thresholds that trigger the kubelet
to reclaim resources.
Each threshold has the following form:
[eviction-signal][operator][quantity]
where:
eviction-signal
is an eviction signal token as defined in the previous table.operator
is the desired relational operator, such as<
(less than).quantity
is the eviction threshold quantity, such as1Gi
. These tokens must match the quantity representation used by Kubernetes. An eviction threshold can also be expressed as a percentage using the%
token.
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 either memory.available<10%
or memory.available<1Gi
. You cannot use both.
Soft Eviction Thresholds
A soft eviction threshold pairs an eviction threshold with a required administrator-specified grace period. No action is taken by the kubelet
to reclaim resources associated with the eviction signal until that grace period has been exceeded. If no grace period is provided, the kubelet
returns an error on startup.
In addition, if a soft eviction threshold has been met, an operator can specify a maximum allowed Pod termination grace period to use when evicting pods from the node. If specified, the kubelet
uses the lesser value among the pod.Spec.TerminationGracePeriodSeconds
and the max allowed grace period. If not specified, the kubelet
kills Pods immediately with no graceful termination.
To configure soft eviction thresholds, the following flags are supported:
eviction-soft
describes a set of eviction thresholds (e.g.memory.available<1.5Gi
) that if met over a corresponding grace period would trigger a Pod eviction.eviction-soft-grace-period
describes a set of eviction grace periods (e.g.memory.available=1m30s
) that correspond to how long a soft eviction threshold must hold before triggering a Pod eviction.eviction-max-pod-grace-period
describes 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, and if observed, the kubelet
will take immediate action to reclaim the associated starved resource. If a hard eviction threshold is met, the kubelet
kills the Pod immediately with no graceful termination.
To configure hard eviction thresholds, the following flag is supported:
eviction-hard
describes a set of eviction thresholds (e.g.memory.available<1Gi
) that if met would trigger a Pod eviction.
The kubelet
has the following default hard eviction threshold:
memory.available<100Mi
nodefs.available<10%
imagefs.available<15%
On a Linux node, the default value also includes nodefs.inodesFree<5%
.
Eviction Monitoring Interval
The kubelet
evaluates eviction thresholds per its configured housekeeping interval.
housekeeping-interval
is the interval between container housekeepings which defaults to10s
.
Node Conditions
The kubelet
maps one or more eviction signals to a corresponding node condition.
If a hard eviction threshold has been met, or a soft eviction threshold has been met independent of its associated grace period, the kubelet
reports a condition that reflects the node is under pressure.
The following node conditions are defined that correspond to the specified eviction signal.
Node Condition | Eviction Signal | Description |
---|---|---|
MemoryPressure | memory.available | Available memory on the node has satisfied an eviction threshold |
DiskPressure | nodefs.available , nodefs.inodesFree , imagefs.available , or imagefs.inodesFree | Available disk space and inodes on either the node’s root filesystem or image filesystem has satisfied an eviction threshold |
PIDPressure | pid.available | Available processes identifiers on the (Linux) node has fallen below an eviction threshold |
The kubelet
continues to report node status updates at the frequency specified by --node-status-update-frequency
which defaults to 10s
.
Oscillation of node conditions
If a node is oscillating above and below a soft eviction threshold, but not exceeding its associated grace period, it would cause the corresponding node condition to constantly oscillate between true and false, and could cause poor scheduling decisions as a consequence.
To protect against this oscillation, the following flag is defined to control how long the kubelet
must wait before transitioning out of a pressure condition.
eviction-pressure-transition-period
is the duration for which thekubelet
has to wait before transitioning out of an eviction pressure condition.
The kubelet
would ensure that it has not observed an eviction threshold being met for the specified pressure condition for the period specified before toggling the condition back to false
.
Reclaiming node level resources
If an eviction threshold has been met and the grace period has passed, the kubelet
initiates the process of reclaiming the pressured resource until it has observed the signal has gone below its defined threshold.
The kubelet
attempts to reclaim node level resources prior to evicting end-user Pods. If disk pressure is observed, the kubelet
reclaims node level resources differently if the machine has a dedicated imagefs
configured for the container runtime.
With imagefs
If nodefs
filesystem has met eviction thresholds, kubelet
frees up disk space by deleting the dead Pods and their containers.
If imagefs
filesystem has met eviction thresholds, kubelet
frees up disk space by deleting all unused images.
Without imagefs
If nodefs
filesystem has met eviction thresholds, kubelet
frees up disk space in the following order:
- Delete dead Pods and their containers
- Delete all unused images
Evicting end-user Pods
If the kubelet
is unable to reclaim sufficient resource on the node, kubelet
begins evicting Pods.
The kubelet
ranks Pods for eviction first by whether or not their usage of the starved resource exceeds requests, then by Priority, and then by the consumption of the starved compute resource relative to the Pods’ scheduling requests.
As a result, kubelet
ranks and evicts Pods in the following order:
BestEffort
orBurstable
Pods whose usage of a starved resource exceeds its request. Such pods are ranked by Priority, and then usage above request.Guaranteed
pods andBurstable
pods whose usage is beneath requests are evicted last.Guaranteed
Pods are guaranteed only when requests and limits are specified for all the containers and they are equal. Such pods are guaranteed to never be evicted because of another Pod’s resource consumption. If a system daemon (such askubelet
,docker
, andjournald
) is consuming more resources than were reserved viasystem-reserved
orkube-reserved
allocations, and the node only hasGuaranteed
orBurstable
Pods using less than requests remaining, then the node must choose to evict such a Pod in order to preserve node stability and to limit the impact of the unexpected consumption to other Pods. In this case, it will choose to evict pods of Lowest Priority first.
If necessary, kubelet
evicts Pods one at a time to reclaim disk when DiskPressure
is encountered. If the kubelet
is responding to inode
starvation, it reclaims inodes
by evicting Pods with the lowest quality of service first. If the kubelet
is responding to lack of available disk, it ranks Pods within a quality of service that consumes the largest amount of disk and kills those first.
With imagefs
If nodefs
is triggering evictions, kubelet
sorts Pods based on the usage on nodefs
- local volumes + logs of all its containers.
If imagefs
is triggering evictions, kubelet
sorts Pods based on the writable layer usage of all its containers.
Without imagefs
If nodefs
is triggering evictions, kubelet
sorts Pods based on their total disk usage
- local volumes + logs & writable layer of all its containers.
Minimum eviction reclaim
In certain scenarios, eviction of Pods could result in reclamation of small amount of resources. This can result in kubelet
hitting eviction thresholds in repeated successions. In addition to that, eviction of resources like disk
, is time consuming.
To mitigate these issues, kubelet
can have a per-resource minimum-reclaim
. Whenever kubelet
observes resource pressure, kubelet
attempts to reclaim at least minimum-reclaim
amount of resource below the configured eviction threshold.
For example, with the following configuration:
--eviction-hard=memory.available<500Mi,nodefs.available<1Gi,imagefs.available<100Gi
--eviction-minimum-reclaim="memory.available=0Mi,nodefs.available=500Mi,imagefs.available=2Gi"`
If an eviction threshold is triggered for memory.available
, the kubelet
works to ensure that memory.available
is at least 500Mi
. For nodefs.available
, the kubelet
works to ensure that nodefs.available
is at least 1.5Gi
, and for imagefs.available
it works to ensure that imagefs.available
is at least 102Gi
before no longer reporting pressure on their associated resources.
The default eviction-minimum-reclaim
is 0
for all resources.
Scheduler
The node reports a condition when a compute resource is under pressure. The scheduler views that condition as a signal to dissuade placing additional pods on the node.
Node Condition | Scheduler Behavior |
---|---|
MemoryPressure | No new BestEffort Pods are scheduled to the node. |
DiskPressure | No new Pods are scheduled to the node. |
Node OOM Behavior
If the node experiences a system OOM (out of memory) event prior to the kubelet
being able to reclaim memory, the node depends on the oom_killer to respond.
The kubelet
sets a oom_score_adj
value for each container based on the quality of service for the Pod.
Quality of Service | oom_score_adj |
---|---|
Guaranteed | -998 |
BestEffort | 1000 |
Burstable | min(max(2, 1000 - (1000 * memoryRequestBytes) / machineMemoryCapacityBytes), 999) |
If the kubelet
is unable to reclaim memory prior to a node experiencing system OOM, the oom_killer
calculates an oom_score
based on the percentage of memory it’s using on the node, and then add the oom_score_adj
to get an effective oom_score
for the container, and then kills the container with the highest score.
The intended behavior should be that containers with the lowest quality of service that are consuming the largest amount of memory relative to the scheduling request should be killed first in order to reclaim memory.
Unlike Pod eviction, if a Pod container is OOM killed, it may be restarted by the kubelet
based on its RestartPolicy
.
Best Practices
The following sections describe best practices for out of resource handling.
Schedulable resources and eviction policies
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.
To facilitate this scenario, the kubelet
would be launched as follows:
--eviction-hard=memory.available<500Mi
--system-reserved=memory=1.5Gi
Implicit in this configuration is the understanding that “System reserved” should include the amount of memory covered by the eviction threshold.
To reach that capacity, either some Pod is using more than its request, or the system is using more than 1.5Gi - 500Mi = 1Gi
.
This configuration ensures that the scheduler does not place Pods on a node that immediately induce memory pressure and trigger eviction assuming those Pods use less than their configured request.
DaemonSet
As Priority
is a key factor in the eviction strategy, if you do not want pods belonging to a DaemonSet
to be evicted, specify a sufficiently high priorityClass in the pod spec template. If you want pods belonging to a DaemonSet
to run only if there are sufficient resources, specify a lower or default priorityClass.
Deprecation of existing feature flags to reclaim disk
kubelet
has been freeing up disk space on demand to keep the node stable.
As disk based eviction matures, the following kubelet
flags are marked for deprecation in favor of the simpler configuration supported around eviction.
Existing Flag | New Flag |
---|---|
—image-gc-high-threshold | —eviction-hard or eviction-soft |
—image-gc-low-threshold | —eviction-minimum-reclaim |
—maximum-dead-containers | deprecated |
—maximum-dead-containers-per-container | deprecated |
—minimum-container-ttl-duration | deprecated |
—low-diskspace-threshold-mb | —eviction-hard or eviction-soft |
—outofdisk-transition-frequency | —eviction-pressure-transition-period |
Known issues
The following sections describe known issues related to out of resource handling.
kubelet may not observe memory pressure right away
The kubelet
currently 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. We intend to integrate with the memcg
notification API in a future release to reduce this latency, and instead have the kernel tell us when a threshold has been crossed immediately.
If you are not trying to achieve extreme utilization, but a sensible measure of overcommit, a viable workaround for this issue is to set eviction thresholds at approximately 75% capacity. This increases the ability of this feature to prevent system OOMs, and promote eviction of workloads so cluster state can rebalance.
kubelet may evict more Pods than needed
The Pod eviction may evict more Pods than needed due to stats collection timing gap. This can be mitigated by adding the ability to get root container stats on an on-demand basis (https://github.com/google/cadvisor/issues/1247) in the future.
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 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.