Runtime Class
Kubernetes v1.20 [stable]
This page describes the RuntimeClass resource and runtime selection mechanism.
RuntimeClass is a feature for selecting the container runtime configuration. The container runtime configuration is used to run a Pod's containers.
Motivation
You can set a different RuntimeClass between different Pods to provide a balance of performance versus security. For example, if part of your workload deserves a high level of information security assurance, you might choose to schedule those Pods so that they run in a container runtime that uses hardware virtualization. You'd then benefit from the extra isolation of the alternative runtime, at the expense of some additional overhead.
You can also use RuntimeClass to run different Pods with the same container runtime but with different settings.
Setup
- Configure the CRI implementation on nodes (runtime dependent)
- Create the corresponding RuntimeClass resources
1. Configure the CRI implementation on nodes
The configurations available through RuntimeClass are Container Runtime Interface (CRI) implementation dependent. See the corresponding documentation (below) for your CRI implementation for how to configure.
The configurations have a corresponding handler
name, referenced by the RuntimeClass. The
handler must be a valid DNS label name.
2. Create the corresponding RuntimeClass resources
The configurations setup in step 1 should each have an associated handler
name, which identifies
the configuration. For each handler, create a corresponding RuntimeClass object.
The RuntimeClass resource currently only has 2 significant fields: the RuntimeClass name
(metadata.name
) and the handler (handler
). The object definition looks like this:
apiVersion: node.k8s.io/v1 # RuntimeClass is defined in the node.k8s.io API group
kind: RuntimeClass
metadata:
name: myclass # The name the RuntimeClass will be referenced by
# RuntimeClass is a non-namespaced resource
handler: myconfiguration # The name of the corresponding CRI configuration
The name of a RuntimeClass object must be a valid DNS subdomain name.
Usage
Once RuntimeClasses are configured for the cluster, using them is very simple. Specify a
runtimeClassName
in the Pod spec. For example:
apiVersion: v1
kind: Pod
metadata:
name: mypod
spec:
runtimeClassName: myclass
# ...
This will instruct the kubelet to use the named RuntimeClass to run this pod. If the named
RuntimeClass does not exist, or the CRI cannot run the corresponding handler, the pod will enter the
Failed
terminal phase. Look for a
corresponding event for an
error message.
If no runtimeClassName
is specified, the default RuntimeHandler will be used, which is equivalent
to the behavior when the RuntimeClass feature is disabled.
CRI Configuration
For more details on setting up CRI runtimes, see CRI installation.
dockershim
RuntimeClasses with dockershim must set the runtime handler to docker
. Dockershim does not support
custom configurable runtime handlers.
containerd
Runtime handlers are configured through containerd's configuration at
/etc/containerd/config.toml
. Valid handlers are configured under the runtimes section:
[plugins."io.containerd.grpc.v1.cri".containerd.runtimes.${HANDLER_NAME}]
See containerd's config documentation for more details: https://github.com/containerd/cri/blob/master/docs/config.md
CRI-O
Runtime handlers are configured through CRI-O's configuration at /etc/crio/crio.conf
. Valid
handlers are configured under the crio.runtime
table:
[crio.runtime.runtimes.${HANDLER_NAME}]
runtime_path = "${PATH_TO_BINARY}"
See CRI-O's config documentation for more details.
Scheduling
Kubernetes v1.16 [beta]
By specifying the scheduling
field for a RuntimeClass, you can set constraints to
ensure that Pods running with this RuntimeClass are scheduled to nodes that support it.
If scheduling
is not set, this RuntimeClass is assumed to be supported by all nodes.
To ensure pods land on nodes supporting a specific RuntimeClass, that set of nodes should have a
common label which is then selected by the runtimeclass.scheduling.nodeSelector
field. The
RuntimeClass's nodeSelector is merged with the pod's nodeSelector in admission, effectively taking
the intersection of the set of nodes selected by each. If there is a conflict, the pod will be
rejected.
If the supported nodes are tainted to prevent other RuntimeClass pods from running on the node, you
can add tolerations
to the RuntimeClass. As with the nodeSelector
, the tolerations are merged
with the pod's tolerations in admission, effectively taking the union of the set of nodes tolerated
by each.
To learn more about configuring the node selector and tolerations, see Assigning Pods to Nodes.
Pod Overhead
Kubernetes v1.18 [beta]
You can specify overhead resources that are associated with running a Pod. Declaring overhead allows the cluster (including the scheduler) to account for it when making decisions about Pods and resources. To use Pod overhead, you must have the PodOverhead feature gate enabled (it is on by default).
Pod overhead is defined in RuntimeClass through the overhead
fields. Through the use of these fields,
you can specify the overhead of running pods utilizing this RuntimeClass and ensure these overheads
are accounted for in Kubernetes.
What's next
- RuntimeClass Design
- RuntimeClass Scheduling Design
- Read about the Pod Overhead concept
- PodOverhead Feature Design