DaemonSet
A DaemonSet ensures that all (or some) Nodes run a copy of a Pod. As nodes are added to the cluster, Pods are added to them. As nodes are removed from the cluster, those Pods are garbage collected. Deleting a DaemonSet will clean up the Pods it created.
Some typical uses of a DaemonSet are:
- running a cluster storage daemon, such as
glusterd
,ceph
, on each node. - running a logs collection daemon on every node, such as
fluentd
orfilebeat
. - running a node monitoring daemon on every node, such as Prometheus Node Exporter, Flowmill, Sysdig Agent,
collectd
, Dynatrace OneAgent, AppDynamics Agent, Datadog agent, New Relic agent, Gangliagmond
, Instana Agent or Elastic Metricbeat.
In a simple case, one DaemonSet, covering all nodes, would be used for each type of daemon. A more complex setup might use multiple DaemonSets for a single type of daemon, but with different flags and/or different memory and cpu requests for different hardware types.
- Writing a DaemonSet Spec
- How Daemon Pods are Scheduled
- Communicating with Daemon Pods
- Updating a DaemonSet
- Alternatives to DaemonSet
Writing a DaemonSet Spec
Create a DaemonSet
You can describe a DaemonSet in a YAML file. For example, the daemonset.yaml
file below describes a DaemonSet that runs the fluentd-elasticsearch Docker image:
controllers/daemonset.yaml
|
---|
|
Create a DaemonSet based on the YAML file:
kubectl apply -f https://k8s.io/examples/controllers/daemonset.yaml
Required Fields
As with all other Kubernetes config, a DaemonSet needs apiVersion
, kind
, and metadata
fields. For
general information about working with config files, see deploying applications,
configuring containers, and object management using kubectl documents.
The name of a DaemonSet object must be a valid DNS subdomain name.
A DaemonSet also needs a .spec
section.
Pod Template
The .spec.template
is one of the required fields in .spec
.
The .spec.template
is a pod template. It has exactly the same schema as a Pod, except it is nested and does not have an apiVersion
or kind
.
In addition to required fields for a Pod, a Pod template in a DaemonSet has to specify appropriate labels (see pod selector).
A Pod Template in a DaemonSet must have a RestartPolicy
equal to Always
, or be unspecified, which defaults to Always
.
Pod Selector
The .spec.selector
field is a pod selector. It works the same as the .spec.selector
of
a Job.
As of Kubernetes 1.8, you must specify a pod selector that matches the labels of the
.spec.template
. The pod selector will no longer be defaulted when left empty. Selector
defaulting was not compatible with kubectl apply
. Also, once a DaemonSet is created,
its .spec.selector
can not be mutated. Mutating the pod selector can lead to the
unintentional orphaning of Pods, and it was found to be confusing to users.
The .spec.selector
is an object consisting of two fields:
matchLabels
- works the same as the.spec.selector
of a ReplicationController.matchExpressions
- allows to build more sophisticated selectors by specifying key, list of values and an operator that relates the key and values.
When the two are specified the result is ANDed.
If the .spec.selector
is specified, it must match the .spec.template.metadata.labels
. Config with these not matching will be rejected by the API.
Also you should not normally create any Pods whose labels match this selector, either directly, via another DaemonSet, or via another workload resource such as ReplicaSet. Otherwise, the DaemonSet ControllerA control loop that watches the shared state of the cluster through the apiserver and makes changes attempting to move the current state towards the desired state. will think that those Pods were created by it. Kubernetes will not stop you from doing this. One case where you might want to do this is manually create a Pod with a different value on a node for testing.
Running Pods on Only Some Nodes
If you specify a .spec.template.spec.nodeSelector
, then the DaemonSet controller will
create Pods on nodes which match that node
selector. Likewise if you specify a .spec.template.spec.affinity
,
then DaemonSet controller will create Pods on nodes which match that node affinity.
If you do not specify either, then the DaemonSet controller will create Pods on all nodes.
How Daemon Pods are Scheduled
Scheduled by default scheduler
Kubernetes v1.18
stable
- The version name is vX where X is an integer.
- Stable versions of features will appear in released software for many subsequent versions.
A DaemonSet ensures that all eligible nodes run a copy of a Pod. Normally, the node that a Pod runs on is selected by the Kubernetes scheduler. However, DaemonSet pods are created and scheduled by the DaemonSet controller instead. That introduces the following issues:
- Inconsistent Pod behavior: Normal Pods waiting to be scheduled are created
and in
Pending
state, but DaemonSet pods are not created inPending
state. This is confusing to the user. - Pod preemption is handled by default scheduler. When preemption is enabled, the DaemonSet controller will make scheduling decisions without considering pod priority and preemption.
ScheduleDaemonSetPods
allows you to schedule DaemonSets using the default
scheduler instead of the DaemonSet controller, by adding the NodeAffinity
term
to the DaemonSet pods, instead of the .spec.nodeName
term. The default
scheduler is then used to bind the pod to the target host. If node affinity of
the DaemonSet pod already exists, it is replaced. The DaemonSet controller only
performs these operations when creating or modifying DaemonSet pods, and no
changes are made to the spec.template
of the DaemonSet.
nodeAffinity:
requiredDuringSchedulingIgnoredDuringExecution:
nodeSelectorTerms:
- matchFields:
- key: metadata.name
operator: In
values:
- target-host-name
In addition, node.kubernetes.io/unschedulable:NoSchedule
toleration is added
automatically to DaemonSet Pods. The default scheduler ignores
unschedulable
Nodes when scheduling DaemonSet Pods.
Taints and Tolerations
Although Daemon Pods respect taints and tolerations, the following tolerations are added to DaemonSet Pods automatically according to the related features.
Toleration Key | Effect | Version | Description |
---|---|---|---|
node.kubernetes.io/not-ready |
NoExecute | 1.13+ | DaemonSet pods will not be evicted when there are node problems such as a network partition. |
node.kubernetes.io/unreachable |
NoExecute | 1.13+ | DaemonSet pods will not be evicted when there are node problems such as a network partition. |
node.kubernetes.io/disk-pressure |
NoSchedule | 1.8+ | |
node.kubernetes.io/memory-pressure |
NoSchedule | 1.8+ | |
node.kubernetes.io/unschedulable |
NoSchedule | 1.12+ | DaemonSet pods tolerate unschedulable attributes by default scheduler. |
node.kubernetes.io/network-unavailable |
NoSchedule | 1.12+ | DaemonSet pods, who uses host network, tolerate network-unavailable attributes by default scheduler. |
Communicating with Daemon Pods
Some possible patterns for communicating with Pods in a DaemonSet are:
- Push: Pods in the DaemonSet are configured to send updates to another service, such as a stats database. They do not have clients.
- NodeIP and Known Port: Pods in the DaemonSet can use a
hostPort
, so that the pods are reachable via the node IPs. Clients know the list of node IPs somehow, and know the port by convention. - DNS: Create a headless service with the same pod selector,
and then discover DaemonSets using the
endpoints
resource or retrieve multiple A records from DNS. - Service: Create a service with the same Pod selector, and use the service to reach a daemon on a random node. (No way to reach specific node.)
Updating a DaemonSet
If node labels are changed, the DaemonSet will promptly add Pods to newly matching nodes and delete Pods from newly not-matching nodes.
You can modify the Pods that a DaemonSet creates. However, Pods do not allow all fields to be updated. Also, the DaemonSet controller will use the original template the next time a node (even with the same name) is created.
You can delete a DaemonSet. If you specify --cascade=false
with kubectl
, then the Pods
will be left on the nodes. If you subsequently create a new DaemonSet with the same selector,
the new DaemonSet adopts the existing Pods. If any Pods need replacing the DaemonSet replaces
them according to its updateStrategy
.
You can perform a rolling update on a DaemonSet.
Alternatives to DaemonSet
Init Scripts
It is certainly possible to run daemon processes by directly starting them on a node (e.g. using
init
, upstartd
, or systemd
). This is perfectly fine. However, there are several advantages to
running such processes via a DaemonSet:
- Ability to monitor and manage logs for daemons in the same way as applications.
- Same config language and tools (e.g. Pod templates,
kubectl
) for daemons and applications. - Running daemons in containers with resource limits increases isolation between daemons from app containers. However, this can also be accomplished by running the daemons in a container but not in a Pod (e.g. start directly via Docker).
Bare Pods
It is possible to create Pods directly which specify a particular node to run on. However, a DaemonSet replaces Pods that are deleted or terminated for any reason, such as in the case of node failure or disruptive node maintenance, such as a kernel upgrade. For this reason, you should use a DaemonSet rather than creating individual Pods.
Static Pods
It is possible to create Pods by writing a file to a certain directory watched by Kubelet. These are called static pods. Unlike DaemonSet, static Pods cannot be managed with kubectl or other Kubernetes API clients. Static Pods do not depend on the apiserver, making them useful in cluster bootstrapping cases. Also, static Pods may be deprecated in the future.
Deployments
DaemonSets are similar to Deployments in that they both create Pods, and those Pods have processes which are not expected to terminate (e.g. web servers, storage servers).
Use a Deployment for stateless services, like frontends, where scaling up and down the number of replicas and rolling out updates are more important than controlling exactly which host the Pod runs on. Use a DaemonSet when it is important that a copy of a Pod always run on all or certain hosts, and when it needs to start before other Pods.
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