Docker / Kubernetes - DaemonSet
DaemonSets try to adhere to a one-Pod-per-node model, either across the entire cluster or a subset of nodes. So, when we add nodes to a node pool, DaemonSets automatically add Pods to the new nodes as needed.
DaemonSets are useful for deploying ongoing background tasks that we need to run on all or certain nodes, and which do not require user intervention.
Examples of such tasks include storage daemons like ceph or glusterd, log collection daemons like fluentd or logstash, and node monitoring daemons like collectd, Prometheus (node_exporter), or Datadog agent.
The following is an example of a DaemonSet manifest file (fluentd-daemonset.yaml):
# fluentd-daemonset.yaml apiVersion: apps/v1 kind: DaemonSet metadata: name: fluentd-daemonset spec: template: metadata: labels: name: fluentd # Pod template's label selector spec: containers: - name: fluentd image: gcr.io/google-containers/fluentd-elasticsearch:1.20 selector: matchLabels: name: fluentd # Label selector that determines which Pods belong to the DaemonSet
In the manifest:
- A DaemonSet named fluentd-daemonset is created, indicated by the metadata: name field.
- DaemonSet's Pod is labelled fluentd in the .spec.template which is a pod template that requires to have labels in place.
- The Pod's container pulls the fluentd-elasticsearch image at version 1.20. The container image is hosted by Container Registry.
- The .spec.selector field is a label selector. These are the labels used to identify potential Pods to acquire.
On GKE, we have 3 nodes running in the cluster:
$ kubectl get node NAME STATUS ROLES AGE VERSION gke-bogotobogo-default-pool-abee3b7e-cbgv Ready <none> 2h v1.11.7-gke.12 gke-bogotobogo-default-pool-abee3b7e-jjnt Ready <none> 2h v1.11.7-gke.12 gke-bogotobogo-default-pool-abee3b7e-qp86 Ready <none> 2h v1.11.7-gke.12
Let's deploy the DaemeonSet controller to the cluster:
$ kubectl create -f fluentd-daemonset.yaml daemonset.apps/fluentd-daemonset created
Let's check our pods, especially, in which node they are running on:
$ kubectl get po -o wide NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE fluentd-daemonset-dzp2n 1/1 Running 0 5m 10.40.2.8 gke-bogotobogo-default-pool-abee3b7e-qp86 <none> fluentd-daemonset-rllk5 1/1 Running 0 5m 10.40.0.4 gke-bogotobogo-default-pool-abee3b7e-cbgv <none> fluentd-daemonset-swhzg 1/1 Running 0 5m 10.40.1.11 gke-bogotobogo-default-pool-abee3b7e-jjnt <none>
Currently, 3 pods are running, one per node.
Let's display DaemonSet:
$ kubectl get ds NAME DESIRED CURRENT READY UP-TO-DATE AVAILABLE NODE SELECTOR AGE fluentd-daemonset 3 3 3 3 3 <none> 7m $ kubectl describe ds fluentd-daemonset Name: fluentd-daemonset Selector: name=fluentd Node-Selector: <none> Labels: name=fluentd Annotations: <none> Desired Number of Nodes Scheduled: 3 Current Number of Nodes Scheduled: 3 Number of Nodes Scheduled with Up-to-date Pods: 3 Number of Nodes Scheduled with Available Pods: 3 Number of Nodes Misscheduled: 0 Pods Status: 3 Running / 0 Waiting / 0 Succeeded / 0 Failed Pod Template: Labels: name=fluentd Containers: fluentd: Image: gcr.io/google-containers/fluentd-elasticsearch:1.20 Port: <none> Host Port: <none> Environment: <none> Mounts: <none> Volumes: <none> Events: Type Reason Age From Message ---- ------ ---- ---- ------- Normal SuccessfulCreate 9m daemonset-controller Created pod: fluentd-daemonset-dzp2n Normal SuccessfulCreate 9m daemonset-controller Created pod: fluentd-daemonset-swhzg Normal SuccessfulCreate 9m daemonset-controller Created pod: fluentd-daemonset-rllk5
We created one object which is DeamonSet which in turn created the pods based on the pod manifest. Let's delete the DaemonSet:
$ kubectl delete ds fluentd-daemonset daemonset.extensions "fluentd-daemonset" deleted $ kubectl get ds No resources found.
So, the DeamonSet has been deleted. But what happened to the pods it created?
$ kubectl get po No resources found.
No pods!
Note that if we delete the pods while keeping the DaemonSet, our pods will be created automatically by the DeamonSet!
Docker & K8s
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- Docker install on EC2 Ubuntu 14.04
- Docker container vs Virtual Machine
- Docker install on Ubuntu 14.04
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- Working with Docker images : brief introduction
- Docker image and container via docker commands (search, pull, run, ps, restart, attach, and rm)
- More on docker run command (docker run -it, docker run --rm, etc.)
- Docker Networks - Bridge Driver Network
- Docker Persistent Storage
- File sharing between host and container (docker run -d -p -v)
- Linking containers and volume for datastore
- Dockerfile - Build Docker images automatically I - FROM, MAINTAINER, and build context
- Dockerfile - Build Docker images automatically II - revisiting FROM, MAINTAINER, build context, and caching
- Dockerfile - Build Docker images automatically III - RUN
- Dockerfile - Build Docker images automatically IV - CMD
- Dockerfile - Build Docker images automatically V - WORKDIR, ENV, ADD, and ENTRYPOINT
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- Docker - NodeJS
- Docker - NodeJS with hostname
- Docker Compose - NodeJS with MongoDB
- Docker - Prometheus and Grafana with Docker-compose
- Docker - StatsD/Graphite/Grafana
- Docker - Deploying a Java EE JBoss/WildFly Application on AWS Elastic Beanstalk Using Docker Containers
- Docker : NodeJS with GCP Kubernetes Engine
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- Docker Compose - Hashicorp's Vault and Consul Part B (EaaS, dynamic secrets, leases, and revocation)
- Docker Compose - Hashicorp's Vault and Consul Part C (Consul)
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- Docker & Kubernetes : Ambassador - Envoy API Gateway on Kubernetes
- Docker Packer
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- Docker Q & A #1
- Kubernetes Q & A - Part I
- Kubernetes Q & A - Part II
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- Docker - Run a React app in a docker II (snapshot app with nginx)
- Docker - NodeJS and MySQL app with React in a docker
- Docker - Step by Step NodeJS and MySQL app with React - I
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- Docker install via Puppet
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Ph.D. / Golden Gate Ave, San Francisco / Seoul National Univ / Carnegie Mellon / UC Berkeley / DevOps / Deep Learning / Visualization