DaemonSet is used to deploy resident background programs in the cluster. For example, it can collect logs for a node. DaemonSet ensures that specified Pods are running on all or certain nodes. When you add new nodes to a cluster, Pods are deployed automatically. When nodes are removed from the cluster, Pods are recovered automatically.
Notes on Scheduling
If nodeSelector or affinity parameters are configured on the Pod, the Pod managed by DaemonSet is scheduled based on the specified rules. If the nodeSelector or affinity parameters are not configured on the Pod, the Pod will be deployed on all nodes.
Operation Guide for DaemonSet in the Console
Creating a DaemonSet
1. Log in to the TKE console and select Cluster in the left sidebar.
2. Click the ID of the cluster where DaemonSet needs to be created to enter the cluster management page.
3. Select Workload > DaemonSet to go to the DaemonSet information page. See the figure below:
4. Click Create to open the Create Workload page.
Set DaemonSet parameters as needed. The key parameters are as follows:
Workload: enter the customized name.
Label: a key-value pair, which is used for classified management of resources.
Namespace: select a namespace based on your requirements.
Type: select DaemonSet (run the Pod on each server).
Volume (optional): provides storage for the container. It can be a temp path, CVM path, CBS volume, file storage NFS, configuration file and PVC, and it must be mounted to the specified path of the container.
Containers in the Pod: set one or more different containers for a Pod of the DaemonSet based on actual needs.
Name: custom.
Image: select as needed.
Image Tag: fill as needed.
Image Pull Policy: the following three policies are available. Select as needed.
If you do not set any image pull policy and Image Tag is left empty or latest, the Always policy is used. Otherwise, the IfNotPresent policy is used.
Always: always pull the image from the remote end.
IfNotPresent: a local image is used by default. If no local image is available, the image is pulled remotely.
Never: only use a local image. If no local image is available, an exception occurs.
CPU/Memory Limit: set the CPU and memory limit according to Kubernetes' resource limits to improve the robustness of the business.
GPU Resource: you can configure the least GPU resource used by the workload.
Advanced Settings: you can set the parameters such as Working Directory, Running Command, Running Parameter, Container Health Check, and Privileged Container.
Image Access Credential: a container image is private by default. You need to select the image access credential for the TCR instance when creating a workload.
Node Scheduling Policy: the Pod can be scheduled to the node of the Label that meets the expectation according to the scheduling rules.
5. Click Create Workload to complete the process.
Updating a DaemonSet
Updating YAML
1. Log in to the TKE console and select Cluster in the left sidebar.
2. Click the ID of the cluster for which to update the YAML to go to the management page of the cluster.
3. Select Workload > DaemonSet to go to the DaemonSet information page. See the figure below:
4. In the row of DaemonSet for which YAML is to be updated, click More > Edit YAML to go to the DaemonSet updating page.
5. On this page, edit the YAML and click Done to update the YAML.
Updating Pod configuration
Note:
Rolling update of DaemonSet is only supported in Kubernetes v1.6 or higher.
1. On the cluster management page, click the ID of the cluster for which Pod configuration should be updated, and go to the management page of the cluster.
2. In the DaemonSet row for which Pod configuration needs to be updated, click Update Pod Configuration, as shown below:
3. On the Update Pod Configuration page, modify the updating method and set parameters as needed, as shown below:
4. Click Done to update the Pod configuration.
Using kubectl to Manipulate DaemonSet
YAML sample
apiVersion: apps/v1
kind: DaemonSet
metadata:
name: fluentd-elasticsearch
namespace: kube-system
labels:
k8s-app: fluentd-logging
spec:
selector:
matchLabels:
name: fluentd-elasticsearch
template:
metadata:
labels:
name: fluentd-elasticsearch
spec:
tolerations:
- key: node-role.kubernetes.io/master
effect: NoSchedule
containers:
- name: fluentd-elasticsearch
image: k8s.gcr.io/fluentd-elasticsearch:1.20
resources:
limits:
memory: 200Mi
requests:
cpu: 100m
memory: 200Mi
volumeMounts:
- name: varlog
mountPath: /var/log
- name: varlibdockercontainers
mountPath: /var/lib/docker/containers
readOnly: true
terminationGracePeriodSeconds: 30
volumes:
- name: varlog
hostPath:
path: /var/log
- name: varlibdockercontainers
hostPath:
path: /var/lib/docker/containers
Note:
Note: The YAML sample described above comes from https://kubernetes.io/docs/concepts/workloads/controllers/daemonset. The container image may not be got during creation. The sample is only used to describe the composition of DaemonSet.
kind: this identifies the DaemonSet resource type.
metadata: basic information such as the DaemonSet name and label.
metadata.annotations: an additional description of the DaemonSet. You can set additional enhancements to TKE through this parameter.
spec.template: detailed template configuration of the Pod managed by the DaemonSet.
1. Prepare the StatefulSet YAML file as instructed by YAML sample.
2. Install kubectl and connect to a cluster. For detailed operations, see Connecting to a Cluster.
3. Run the following command to create the DaemonSet YAML file.
kubectl create -f <DaemonSet YAML filename>
For example, to create a StatefulSet YAML file named fluentd-elasticsearch.yaml, run the following command:
kubectl create -f fluentd-elasticsearch.yaml
4. Run the following command to check whether the Job is successfully created.
kubectl get DaemonSet
If a message similar to the following is returned, the creation is successful.
NAME DESIRED CURRENT READY UP-TO-DATE AVAILABLE NODE SELECTOR AGE
frontend 00000app=frontend-node 16d
Using kubectl to update a DaemonSet
Run the following command to view the update policy type of the DaemonSet.
kubectl get ds/<daemonset-name> -o go-template='{{.spec.updateStrategy.type}}{{"\\n"}}'
DaemonSet has the following two update policy types:
OnDelete: default update policy. With this policy, after the DaemonSet is updated, you have to manually delete the old DaemonSet Pod to create a new one.
RollingUpdate: Kubernetes 1.6 or later is supported. With this policy, after the DaemonSet template is updated, the old DaemonSet Pod will be killed, and a new one will be created in a rolling update manner.
Method 1
Run the following command to update a DaemonSet.
kubectl edit DaemonSet/[name]
This method applies to simple debug verification. It is not recommended to use it in production environments. You can update any DaemonSet parameters in this way.
Method 2
Run the following command to update the image of the specified container.
kubectl set image ds/[daemonset-name][container-name]=[container-new-image]
It is recommended to keep other DaemonSet parameters unchanged and only update the container image when the business is updated.
Using kubectl to rollback a DaemonSet
1. Run the following command to view the update history of the DaemonSet.
kubectl rollout history daemonset /[name]
2. Run the following command to view the details of the specified version.
kubectl rollout history daemonset /[name] --revision=[REVISION]
3. Run the following command to roll back to the earlier version.
kubectl rollout undo daemonset /[name]
To specify the rollback version, run the following command.
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