Reserve Compute Resources for System Daemons
Kubernetes nodes can be scheduled to Capacity
. Pods can consume all the
available capacity on a node by default. This is an issue because nodes
typically run quite a few system daemons that power the OS and Kubernetes
itself. Unless resources are set aside for these system daemons, pods and system
daemons compete for resources and lead to resource starvation issues on the
node.
The kubelet
exposes a feature named 'Node Allocatable' that helps to reserve
compute resources for system daemons. Kubernetes recommends cluster
administrators to configure 'Node Allocatable' based on their workload density
on each node.
Before you begin
You need to have a Kubernetes cluster, and the kubectl command-line tool must be configured to communicate with your cluster. It is recommended to run this tutorial on a cluster with at least two nodes that are not acting as control plane hosts. If you do not already have a cluster, you can create one by using minikube or you can use one of these Kubernetes playgrounds:
Your Kubernetes server must be at or later than version 1.8. To check the version, enterkubectl version
.
Your Kubernetes server must be at or later than version 1.17 to use
the kubelet command line option --reserved-cpus
to set an
explicitly reserved CPU list.
Node Allocatable
'Allocatable' on a Kubernetes node is defined as the amount of compute resources that are available for pods. The scheduler does not over-subscribe 'Allocatable'. 'CPU', 'memory' and 'ephemeral-storage' are supported as of now.
Node Allocatable is exposed as part of v1.Node
object in the API and as part
of kubectl describe node
in the CLI.
Resources can be reserved for two categories of system daemons in the kubelet
.
Enabling QoS and Pod level cgroups
To properly enforce node allocatable constraints on the node, you must
enable the new cgroup hierarchy via the --cgroups-per-qos
flag. This flag is
enabled by default. When enabled, the kubelet
will parent all end-user pods
under a cgroup hierarchy managed by the kubelet
.
Configuring a cgroup driver
The kubelet
supports manipulation of the cgroup hierarchy on
the host using a cgroup driver. The driver is configured via the
--cgroup-driver
flag.
The supported values are the following:
cgroupfs
is the default driver that performs direct manipulation of the cgroup filesystem on the host in order to manage cgroup sandboxes.systemd
is an alternative driver that manages cgroup sandboxes using transient slices for resources that are supported by that init system.
Depending on the configuration of the associated container runtime,
operators may have to choose a particular cgroup driver to ensure
proper system behavior. For example, if operators use the systemd
cgroup driver provided by the docker
runtime, the kubelet
must
be configured to use the systemd
cgroup driver.
Kube Reserved
- Kubelet Flag:
--kube-reserved=[cpu=100m][,][memory=100Mi][,][ephemeral-storage=1Gi][,][pid=1000]
- Kubelet Flag:
--kube-reserved-cgroup=
kube-reserved
is meant to capture resource reservation for kubernetes system
daemons like the kubelet
, container runtime
, node problem detector
, etc.
It is not meant to reserve resources for system daemons that are run as pods.
kube-reserved
is typically a function of pod density
on the nodes.
In addition to cpu
, memory
, and ephemeral-storage
, pid
may be
specified to reserve the specified number of process IDs for
kubernetes system daemons.
To optionally enforce kube-reserved
on kubernetes system daemons, specify the parent
control group for kube daemons as the value for --kube-reserved-cgroup
kubelet
flag.
It is recommended that the kubernetes system daemons are placed under a top
level control group (runtime.slice
on systemd machines for example). Each
system daemon should ideally run within its own child control group. Refer to
the design proposal
for more details on recommended control group hierarchy.
Note that Kubelet does not create --kube-reserved-cgroup
if it doesn't
exist. Kubelet will fail if an invalid cgroup is specified.
System Reserved
- Kubelet Flag:
--system-reserved=[cpu=100m][,][memory=100Mi][,][ephemeral-storage=1Gi][,][pid=1000]
- Kubelet Flag:
--system-reserved-cgroup=
system-reserved
is meant to capture resource reservation for OS system daemons
like sshd
, udev
, etc. system-reserved
should reserve memory
for the
kernel
too since kernel
memory is not accounted to pods in Kubernetes at this time.
Reserving resources for user login sessions is also recommended (user.slice
in
systemd world).
In addition to cpu
, memory
, and ephemeral-storage
, pid
may be
specified to reserve the specified number of process IDs for OS system
daemons.
To optionally enforce system-reserved
on system daemons, specify the parent
control group for OS system daemons as the value for --system-reserved-cgroup
kubelet flag.
It is recommended that the OS system daemons are placed under a top level
control group (system.slice
on systemd machines for example).
Note that kubelet
does not create --system-reserved-cgroup
if it doesn't
exist. kubelet
will fail if an invalid cgroup is specified.
Explicitly Reserved CPU List
Kubernetes v1.17 [stable]
Kubelet Flag: --reserved-cpus=0-3
reserved-cpus
is meant to define an explicit CPU set for OS system daemons and
kubernetes system daemons. reserved-cpus
is for systems that do not intend to
define separate top level cgroups for OS system daemons and kubernetes system daemons
with regard to cpuset resource.
If the Kubelet does not have --system-reserved-cgroup
and --kube-reserved-cgroup
,
the explicit cpuset provided by reserved-cpus
will take precedence over the CPUs
defined by --kube-reserved
and --system-reserved
options.
This option is specifically designed for Telco/NFV use cases where uncontrolled interrupts/timers may impact the workload performance. you can use this option to define the explicit cpuset for the system/kubernetes daemons as well as the interrupts/timers, so the rest CPUs on the system can be used exclusively for workloads, with less impact from uncontrolled interrupts/timers. To move the system daemon, kubernetes daemons and interrupts/timers to the explicit cpuset defined by this option, other mechanism outside Kubernetes should be used. For example: in Centos, you can do this using the tuned toolset.
Eviction Thresholds
Kubelet Flag: --eviction-hard=[memory.available<500Mi]
Memory pressure at the node level leads to System OOMs which affects the entire
node and all pods running on it. Nodes can go offline temporarily until memory
has been reclaimed. To avoid (or reduce the probability of) system OOMs kubelet
provides out of resource
management. Evictions are
supported for memory
and ephemeral-storage
only. By reserving some memory via
--eviction-hard
flag, the kubelet
attempts to evict pods whenever memory
availability on the node drops below the reserved value. Hypothetically, if
system daemons did not exist on a node, pods cannot use more than capacity - eviction-hard
. For this reason, resources reserved for evictions are not
available for pods.
Enforcing Node Allocatable
Kubelet Flag: --enforce-node-allocatable=pods[,][system-reserved][,][kube-reserved]
The scheduler treats 'Allocatable' as the available capacity
for pods.
kubelet
enforce 'Allocatable' across pods by default. Enforcement is performed
by evicting pods whenever the overall usage across all pods exceeds
'Allocatable'. More details on eviction policy can be found
on the node pressure eviction
page. This enforcement is controlled by
specifying pods
value to the kubelet flag --enforce-node-allocatable
.
Optionally, kubelet
can be made to enforce kube-reserved
and
system-reserved
by specifying kube-reserved
& system-reserved
values in
the same flag. Note that to enforce kube-reserved
or system-reserved
,
--kube-reserved-cgroup
or --system-reserved-cgroup
needs to be specified
respectively.
General Guidelines
System daemons are expected to be treated similar to 'Guaranteed' pods. System
daemons can burst within their bounding control groups and this behavior needs
to be managed as part of kubernetes deployments. For example, kubelet
should
have its own control group and share kube-reserved
resources with the
container runtime. However, Kubelet cannot burst and use up all available Node
resources if kube-reserved
is enforced.
Be extra careful while enforcing system-reserved
reservation since it can lead
to critical system services being CPU starved, OOM killed, or unable
to fork on the node. The
recommendation is to enforce system-reserved
only if a user has profiled their
nodes exhaustively to come up with precise estimates and is confident in their
ability to recover if any process in that group is oom-killed.
- To begin with enforce 'Allocatable' on
pods
. - Once adequate monitoring and alerting is in place to track kube system
daemons, attempt to enforce
kube-reserved
based on usage heuristics. - If absolutely necessary, enforce
system-reserved
over time.
The resource requirements of kube system daemons may grow over time as more and
more features are added. Over time, kubernetes project will attempt to bring
down utilization of node system daemons, but that is not a priority as of now.
So expect a drop in Allocatable
capacity in future releases.
Example Scenario
Here is an example to illustrate Node Allocatable computation:
- Node has
32Gi
ofmemory
,16 CPUs
and100Gi
ofStorage
--kube-reserved
is set tocpu=1,memory=2Gi,ephemeral-storage=1Gi
--system-reserved
is set tocpu=500m,memory=1Gi,ephemeral-storage=1Gi
--eviction-hard
is set tomemory.available<500Mi,nodefs.available<10%
Under this scenario, 'Allocatable' will be 14.5 CPUs, 28.5Gi of memory and
88Gi
of local storage.
Scheduler ensures that the total memory requests
across all pods on this node does
not exceed 28.5Gi and storage doesn't exceed 88Gi.
Kubelet evicts pods whenever the overall memory usage across pods exceeds 28.5Gi,
or if overall disk usage exceeds 88Gi If all processes on the node consume as
much CPU as they can, pods together cannot consume more than 14.5 CPUs.
If kube-reserved
and/or system-reserved
is not enforced and system daemons
exceed their reservation, kubelet
evicts pods whenever the overall node memory
usage is higher than 31.5Gi or storage
is greater than 90Gi.