Kubernetes: Web UI (Dashboard)

Dashboard is a web-based Kubernetes user interface. You can use Dashboard to deploy containerized applications to a Kubernetes cluster, troubleshoot your containerized application, and manage the cluster resources. You can use Dashboard to get an overview of applications running on your cluster, as well as for creating or modifying individual Kubernetes resources (such as Deployments, Jobs, DaemonSets, etc). For example, you can scale a Deployment, initiate a rolling update, restart a pod or deploy new applications using a deploy wizard.

Dashboard also provides information on the state of Kubernetes resources in your cluster and on any errors that may have occurred.

• Deploying the Dashboard UI
• Accessing the Dashboard UI
• Welcome view
• Deploying containerized applications
• Using Dashboard

Deploying the Dashboard UI

The Dashboard UI is not deployed by default. To deploy it, run the following command:

kubectl apply -f https://raw.githubusercontent.com/kubernetes/dashboard/v2.0.0-beta8/aio/deploy/recommended.yaml

Accessing the Dashboard UI

To protect your cluster data, Dashboard deploys with a minimal RBAC configuration by default. Currently, Dashboard only supports logging in with a Bearer Token. To create a token for this demo, you can follow our guide on creating a sample user.

Warning: The sample user created in the tutorial will have administrative privileges and is for educational purposes only.

Command line proxy

You can access Dashboard using the kubectl command-line tool by running the following command:

kubectl proxy

Kubectl will make Dashboard available at http://localhost:8001/api/v1/namespaces/kubernetes-dashboard/services/https:kubernetes-dashboard:/proxy/.

The UI can only be accessed from the machine where the command is executed. See kubectl proxy --help for more options.

Note: Kubeconfig Authentication method does NOT support external identity providers or x509 certificate-based authentication.

Welcome view

When you access Dashboard on an empty cluster, you’ll see the welcome page. This page contains a link to this document as well as a button to deploy your first application. In addition, you can view which system applications are running by default in the kube-system namespace of your cluster, for example the Dashboard itself.

Deploying containerized applications

Dashboard lets you create and deploy a containerized application as a Deployment and optional Service with a simple wizard. You can either manually specify application details, or upload a YAML or JSON file containing application configuration.

Click the CREATE button in the upper right corner of any page to begin.

Specifying application details

The deploy wizard expects that you provide the following information:

• App name (mandatory): Name for your application. A label with the name will be added to the Deployment and Service, if any, that will be deployed.

The application name must be unique within the selected Kubernetes namespace. It must start with a lowercase character, and end with a lowercase character or a number, and contain only lowercase letters, numbers and dashes (-). It is limited to 24 characters. Leading and trailing spaces are ignored.

• Container image (mandatory): The URL of a public Docker container image on any registry, or a private image (commonly hosted on the Google Container Registry or Docker Hub). The container image specification must end with a colon.
• Number of pods (mandatory): The target number of Pods you want your application to be deployed in. The value must be a positive integer.

A Deployment will be created to maintain the desired number of Pods across your cluster.

• Service (optional): For some parts of your application (e.g. frontends) you may want to expose a Service onto an external, maybe public IP address outside of your cluster (external Service). For external Services, you may need to open up one or more ports to do so. Find more details here.

Other Services that are only visible from inside the cluster are called internal Services.

Irrespective of the Service type, if you choose to create a Service and your container listens on a port (incoming), you need to specify two ports. The Service will be created mapping the port (incoming) to the target port seen by the container. This Service will route to your deployed Pods. Supported protocols are TCP and UDP. The internal DNS name for this Service will be the value you specified as application name above.

If needed, you can expand the Advanced options section where you can specify more settings:

• Description: The text you enter here will be added as an annotation to the Deployment and displayed in the application’s details.
• Labels: Default labels to be used for your application are application name and version. You can specify additional labels to be applied to the Deployment, Service (if any), and Pods, such as release, environment, tier, partition, and release track.

Example:

release=1.0
tier=frontend
environment=pod
track=stable

• Namespace: Kubernetes supports multiple virtual clusters backed by the same physical cluster. These virtual clusters are called namespaces. They let you partition resources into logically named groups.

Dashboard offers all available namespaces in a dropdown list, and allows you to create a new namespace. The namespace name may contain a maximum of 63 alphanumeric characters and dashes (-) but can not contain capital letters. Namespace names should not consist of only numbers. If the name is set as a number, such as 10, the pod will be put in the default namespace.

In case the creation of the namespace is successful, it is selected by default. If the creation fails, the first namespace is selected.

• Image Pull Secret: In case the specified Docker container image is private, it may require pull secret credentials.

Dashboard offers all available secrets in a dropdown list, and allows you to create a new secret. The secret name must follow the DNS domain name syntax, for example new.image-pull.secret. The content of a secret must be base64-encoded and specified in a .dockercfg file. The secret name may consist of a maximum of 253 characters.

In case the creation of the image pull secret is successful, it is selected by default. If the creation fails, no secret is applied.

• CPU requirement (cores) and Memory requirement (MiB): You can specify the minimum resource limits for the container. By default, Pods run with unbounded CPU and memory limits.
• Run command and Run command arguments: By default, your containers run the specified Docker image’s default entrypoint command. You can use the command options and arguments to override the default.
• Run as privileged: This setting determines whether processes in privileged containers are equivalent to processes running as root on the host. Privileged containers can make use of capabilities like manipulating the network stack and accessing devices.
• Environment variables: Kubernetes exposes Services through environment variables. You can compose environment variable or pass arguments to your commands using the values of environment variables. They can be used in applications to find a Service. Values can reference other variables using the $(VAR_NAME) syntax.

Uploading a YAML or JSON file

Kubernetes supports declarative configuration. In this style, all configuration is stored in YAML or JSON configuration files using the Kubernetes API resource schemas.

As an alternative to specifying application details in the deploy wizard, you can define your application in YAML or JSON files, and upload the files using Dashboard.

Using Dashboard

Following sections describe views of the Kubernetes Dashboard UI; what they provide and how can they be used.

Navigation

When there are Kubernetes objects defined in the cluster, Dashboard shows them in the initial view. By default only objects from the default namespace are shown and this can be changed using the namespace selector located in the navigation menu.

Dashboard shows most Kubernetes object kinds and groups them in a few menu categories.

Admin Overview

For cluster and namespace administrators, Dashboard lists Nodes, Namespaces and Persistent Volumes and has detail views for them. Node list view contains CPU and memory usage metrics aggregated across all Nodes. The details view shows the metrics for a Node, its specification, status, allocated resources, events and pods running on the node.

Workloads

Shows all applications running in the selected namespace. The view lists applications by workload kind (e.g., Deployments, Replica Sets, Stateful Sets, etc.) and each workload kind can be viewed separately. The lists summarize actionable information about the workloads, such as the number of ready pods for a Replica Set or current memory usage for a Pod.

Detail views for workloads show status and specification information and surface relationships between objects. For example, Pods that Replica Set is controlling or New Replica Sets and Horizontal Pod Autoscalers for Deployments.

Services

Shows Kubernetes resources that allow for exposing services to external world and discovering them within a cluster. For that reason, Service and Ingress views show Pods targeted by them, internal endpoints for cluster connections and external endpoints for external users.

Storage

Storage view shows Persistent Volume Claim resources which are used by applications for storing data.

Config Maps and Secrets

Shows all Kubernetes resources that are used for live configuration of applications running in clusters. The view allows for editing and managing config objects and displays secrets hidden by default.

Logs viewer

Pod lists and detail pages link to a logs viewer that is built into Dashboard. The viewer allows for drilling down logs from containers belonging to a single Pod.

Reference:

• Kubernetes.io - Web UI (Dashboard)

Kubernetes - Kubectl Commands

Kubectl controls the Kubernetes Cluster. It is one of the key components of Kubernetes which runs on the workstation on any machine when the setup is done. It has the capability to manage the nodes in the cluster.

Kubectl commands are used to interact and manage Kubernetes objects and the cluster. In this chapter, we will discuss a few commands used in Kubernetes via kubectl.

kubectl annotate − It updates the annotation on a resource.

$kubectl annotate [--overwrite] (-f FILENAME | TYPE NAME) KEY_1=VAL_1 ...
KEY_N = VAL_N [--resource-version = version]

For example,

kubectl annotate pods tomcat description = 'my frontend'

kubectl api-versions − It prints the supported versions of API on the cluster.

$ kubectl api-version;

kubectl apply − It has the capability to configure a resource by file or stdin.

$ kubectl apply –f <filename>

kubectl attach − This attaches things to the running container.

$ kubectl attach <pod> –c <container>
$ kubectl attach 123456-7890 -c tomcat-conatiner

kubectl autoscale − This is used to auto scale pods which are defined such as Deployment, replica set, Replication Controller.

$ kubectl autoscale (-f FILENAME | TYPE NAME | TYPE/NAME) [--min = MINPODS] --
max = MAXPODS [--cpu-percent = CPU] [flags]
$ kubectl autoscale deployment foo --min = 2 --max = 10

kubectl cluster-info − It displays the cluster Info.

$ kubectl cluster-info

kubectl cluster-info dump − It dumps relevant information regarding cluster for debugging and diagnosis.

$ kubectl cluster-info dump
$ kubectl cluster-info dump --output-directory = /path/to/cluster-state

kubectl config − Modifies the kubeconfig file.

$ kubectl config <SUBCOMMAD>
$ kubectl config –-kubeconfig <String of File name>

kubectl config current-context − It displays the current context.

$ kubectl config current-context
#deploys the current context

kubectl config delete-cluster − Deletes the specified cluster from kubeconfig.

$ kubectl config delete-cluster <Cluster Name>

kubectl config delete-context − Deletes a specified context from kubeconfig.

$ kubectl config delete-context <Context Name>

kubectl config get-clusters − Displays cluster defined in the kubeconfig.

$ kubectl config get-cluster
$ kubectl config get-cluster <Cluser Name>

kubectl config get-contexts − Describes one or many contexts.

$ kubectl config get-context <Context Name>

kubectl config set-cluster − Sets the cluster entry in Kubernetes.

$ kubectl config set-cluster NAME [--server = server] [--certificateauthority =
path/to/certificate/authority] [--insecure-skip-tls-verify = true]

kubectl config set-context − Sets a context entry in kubernetes entrypoint.

$ kubectl config set-context NAME [--cluster = cluster_nickname] [--
user = user_nickname] [--namespace = namespace]
$ kubectl config set-context prod –user = vipin-mishra

kubectl config set-credentials − Sets a user entry in kubeconfig.

$ kubectl config set-credentials cluster-admin --username = vipin --
password = uXFGweU9l35qcif

kubectl config set − Sets an individual value in kubeconfig file.

$ kubectl config set PROPERTY_NAME PROPERTY_VALUE

kubectl config unset − It unsets a specific component in kubectl.

$ kubectl config unset PROPERTY_NAME PROPERTY_VALUE

kubectl config use-context − Sets the current context in kubectl file.

$ kubectl config use-context <Context Name>

kubectl config view

$ kubectl config view
$ kubectl config view –o jsonpath='{.users[?(@.name == "e2e")].user.password}'

kubectl cp − Copy files and directories to and from containers.

$ kubectl cp <Files from source> <Files to Destinatiion>
$ kubectl cp /tmp/foo <some-pod>:/tmp/bar -c <specific-container>

kubectl create − To create resource by filename of or stdin. To do this, JSON or YAML formats are accepted.

$ kubectl create –f <File Name>
$ cat <file name> | kubectl create –f -

In the same way, we can create multiple things as listed using the create command along with kubectl.

• deployment
• namespace
• quota
• secret docker-registry
• secret
• secret generic
• secret tls
• serviceaccount
• service clusterip
• service loadbalancer
• service nodeport

kubectl delete − Deletes resources by file name, stdin, resource and names.

$ kubectl delete –f ([-f FILENAME] | TYPE [(NAME | -l label | --all)])

kubectl describe − Describes any particular resource in kubernetes. Shows details of resource or a group of resources.

$ kubectl describe <type> <type name>
$ kubectl describe pod tomcat

kubectl drain − This is used to drain a node for maintenance purpose. It prepares the node for maintenance. This will mark the node as unavailable so that it should not be assigned with a new container which will be created.

$ kubectl drain tomcat –force

kubectl edit − It is used to end the resources on the server. This allows to directly edit a resource which one can receive via the command line tool.

$ kubectl edit <Resource/Name | File Name)
Ex.
$ kubectl edit rc/tomcat

kubectl exec − This helps to execute a command in the container.

$ kubectl exec POD <-c CONTAINER > -- COMMAND < args...>
$ kubectl exec tomcat 123-5-456 date

kubectl expose − This is used to expose the Kubernetes objects such as pod, replication controller, and service as a new Kubernetes service. This has the capability to expose it via a running container or from a yaml file.

$ kubectl expose (-f FILENAME | TYPE NAME) [--port=port] [--protocol = TCP|UDP]
[--target-port = number-or-name] [--name = name] [--external-ip = external-ip-ofservice]
[--type = type]
$ kubectl expose rc tomcat –-port=80 –target-port = 30000
$ kubectl expose –f tomcat.yaml –port = 80 –target-port =

kubectl get − This command is capable of fetching data on the cluster about the Kubernetes resources.

$ kubectl get [(-o|--output=)json|yaml|wide|custom-columns=...|custom-columnsfile=...|
go-template=...|go-template-file=...|jsonpath=...|jsonpath-file=...]
(TYPE [NAME | -l label] | TYPE/NAME ...) [flags]

For example,

$ kubectl get pod <pod name>
$ kubectl get service <Service name>

kubectl logs − They are used to get the logs of the container in a pod. Printing the logs can be defining the container name in the pod. If the POD has only one container there is no need to define its name.

$ kubectl logs [-f] [-p] POD [-c CONTAINER]
Example
$ kubectl logs tomcat.
$ kubectl logs –p –c tomcat.8

kubectl port-forward − They are used to forward one or more local port to pods.

$ kubectl port-forward POD [LOCAL_PORT:]REMOTE_PORT
[...[LOCAL_PORT_N:]REMOTE_PORT_N]
$ kubectl port-forward tomcat 3000 4000
$ kubectl port-forward tomcat 3000:5000

kubectl replace − Capable of replacing a resource by file name or stdin.

$ kubectl replace -f FILENAME
$ kubectl replace –f tomcat.yml
$ cat tomcat.yml | kubectl replace –f -

kubectl rolling-update − Performs a rolling update on a replication controller. Replaces the specified replication controller with a new replication controller by updating a POD at a time.

$ kubectl rolling-update OLD_CONTROLLER_NAME ([NEW_CONTROLLER_NAME] --
image = NEW_CONTAINER_IMAGE | -f NEW_CONTROLLER_SPEC)
$ kubectl rolling-update frontend-v1 –f freontend-v2.yaml

kubectl rollout − It is capable of managing the rollout of deployment.

$ Kubectl rollout <Sub Command>
$ kubectl rollout undo deployment/tomcat

Apart from the above, we can perform multiple tasks using the rollout such as −

• rollout history
• rollout pause
• rollout resume
• rollout status
• rollout undo

kubectl run − Run command has the capability to run an image on the Kubernetes cluster.

$ kubectl run NAME --image = image [--env = "key = value"] [--port = port] [--
replicas = replicas] [--dry-run = bool] [--overrides = inline-json] [--command] --
[COMMAND] [args...]
$ kubectl run tomcat --image = tomcat:7.0
$ kubectl run tomcat –-image = tomcat:7.0 –port = 5000

kubectl scale − It will scale the size of Kubernetes Deployments, ReplicaSet, Replication Controller, or job.

$ kubectl scale [--resource-version = version] [--current-replicas = count] --
replicas = COUNT (-f FILENAME | TYPE NAME )
$ kubectl scale –-replica = 3 rs/tomcat
$ kubectl scale –replica = 3 tomcat.yaml

kubectl set image − It updates the image of a pod template.

$ kubectl set image (-f FILENAME | TYPE NAME)
CONTAINER_NAME_1 = CONTAINER_IMAGE_1 ... CONTAINER_NAME_N = CONTAINER_IMAGE_N
$ kubectl set image deployment/tomcat busybox = busybox ngnix = ngnix:1.9.1
$ kubectl set image deployments, rc tomcat = tomcat6.0 --all

kubectl set resources − It is used to set the content of the resource. It updates resource/limits on object with pod template.

$ kubectl set resources (-f FILENAME | TYPE NAME) ([--limits = LIMITS & --
requests = REQUESTS]
$ kubectl set resources deployment tomcat -c = tomcat --
limits = cpu = 200m,memory = 512Mi

kubectl top node − It displays CPU/Memory/Storage usage. The top command allows you to see the resource consumption for nodes.

$ kubectl top node [node Name]

The same command can be used with a pod as well.

Reference:

• TutorialsPoint.com - Kubernetes Kubectl Commands

Kubernetes + Python (Flask) Example

So, you know you want to run your application in Kubernetes but don’t know where to start. Or maybe you’re getting started but still don’t know what you don’t know. In this blog you’ll walk through how to containerize an application and get it running in Kubernetes.

This walk-through assumes you are a developer or at least comfortable with the command line (preferably bash shell).

What we’ll do

1. Get the code and run the application locally
2. Create an image and run the application in Docker
3. Create a deployment and run the application in Kubernetes

Prerequisites

• A Kubernetes service - I’m using Docker Desktop with Kubernetes in this walkthrough, but you can use one of the others. See Getting Started for a full listing.
• Python 3.7 installed
• Git installed

Containerizing an application

In this section you’ll take some source code, verify it runs locally, and then create a Docker image of the application. The sample application used is a very simple Flask web application; if you want to test it locally, you’ll need Python installed. Otherwise, you can skip to the “Create a Dockerfile” section.

Get the application code

Use git to clone the repository to your local machine:

git clone https://github.com/JasonHaley/hello-python.git

Change to the app directory:

cd hello-python/app

There are only two files in this directory. If you look at the main.py file, you’ll see the application prints out a hello message. You can learn more about Flask on the Flask website.

from flask import Flask
app = Flask(__name__)

@app.route("/")
def hello():
    return "Hello from Python!"

if __name__ == "__main__":
    app.run(host='0.0.0.0')

The requirements.txt file contains the list of packages needed by the main.py and will be used by pip to install the Flask library.

Note: When you start writing more advanced Python, you’ll find it’s not always recommended to use pip install and may want to use virtualenv (or pyenv) to install your dependencies in a virtual environment.

Run locally

Manually run the installer and application using the following commands:

pip install -r requirements.txt
python main.py

This will start a development web server hosting your application, which you will be able to see by navigating to http://localhost:5000. Because port 5000 is the default port for the development server, we didn’t need to specify it.

Create a Dockerfile

Now that you have verified the source code works, the first step in containerizing the application is to create a Dockerfile.

In the hello-python/app directory, create a file named Dockerfile with the following contents and save it:

FROM python:3.7

RUN mkdir /app
WORKDIR /app
ADD . /app/
RUN pip install -r requirements.txt

EXPOSE 5000
CMD ["python", "/app/main.py"]

This file is a set of instructions Docker will use to build the image. For this simple application, Docker is going to:

1. Get the official Python Base Image for version 3.7 from Docker Hub.
2. In the image, create a directory named app.
3. Set the working directory to that new app directory.
4. Copy the local directory’s contents to that new folder into the image.
5. Run the pip installer (just like we did earlier) to pull the requirements into the image.
6. Inform Docker the container listens on port 5000.
7. Configure the starting command to use when the container starts.

Create an image

At your command line or shell, in the hello-python/app directory, build the image with the following command:

docker build -f Dockerfile -t hello-python:latest .

Note: I’m using the :latest tag in this example, if you are not familiar with what it is you may want to read Docker: The latest Confusion.

This will perform those seven steps listed above and create the image. To verify the image was created, run the following command:

docker image ls

The application is now containerized, which means it can now run in Docker and Kubernetes!

Running in Docker

Before jumping into Kubernetes, let’s verify it works in Docker. Run the following command to have Docker run the application in a container and map it to port 5001:

docker run -p 5001:5000 hello-python

Now navigate to http://localhost:5001, and you should see the “Hello form Python!” message.

More info

• Get started with Docker
• Best practices for writing Dockerfiles
• Docker Cheat Sheet (pdf)

Running in Kubernetes

You are finally ready to get the application running in Kubernetes. Because you have a web application, you will create a service and a deployment.

First verify your kubectl is configured. At the command line, type the following:

kubectl version

If you don’t see a reply with a Client and Server version, you’ll need to install and configure it.

If you are running on Windows or Mac, make sure it is using the Docker for Desktop context by running the following:

kubectl config use-context docker-for-desktop

Now you are working with Kubernetes! You can see the node by typing:

kubectl get nodes

Now let’s have it run the application. Create a file named deployment.yaml and add the following contents to it and then save it:

apiVersion: v1
kind: Service
metadata:
  name: hello-python-service
spec:
  selector:
    app: hello-python
  ports:
  - protocol: "TCP"
    port: 6000
    targetPort: 5000
  type: LoadBalancer

---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: hello-python
spec:
  selector:
    matchLabels:
      app: hello-python
  replicas: 4
  template:
    metadata:
      labels:
        app: hello-python
    spec:
      containers:
      - name: hello-python
        image: hello-python:latest
        imagePullPolicy: Never
        ports:
        - containerPort: 5000

This YAML file is the instructions to Kubernetes for what you want running. It is telling Kubernetes the following: * You want a load-balanced service exposing port 6000 * You want four instances of the hello-python container running

Use kubectl to send the YAML file to Kubernetes by running the following command:

kubectl apply -f deployment.yaml

You can see the pods are running if you execute the following command:

kubectl get pods

Now navigate to http://localhost:6000, and you should see the “Hello form Python!” message.

That’s it! The application is now running in Kubernetes!

More Info

• Learn Kubernetes Basics
• kubectl Cheat Sheet
• kubectl for Docker Users

Summary

In this walk-through, we containerized an application, and got it running in Docker and in Kubernetes. This simple application only scratches the surface of what’s possible (and what you’ll need to learn).

Next steps

If you are just getting started and this walk-through was useful to you, then the following resources should be good next steps for you to further expand your Kubernetes knowledge:

• Introduction to Microservices, Docker, and Kubernetes - 55-minute video by James Quigley
  • This is a great place to start because it provides more information than I could here.
• Containerize your Apps with Docker and Kubernetes - free e-book by Dr Gabriel N Schenker
  • This is my favorite book on Docker and Kubernetes.
• Kubernetes Learning Path: 50 days from zero to hero with Kubernetes - on Microsoft’s site
  • This is a 10-page pdf that has tons of links to videos (with Brendan Burns), documentation sites, and a really good workshop for Azure Kubernetes Service.

How to enable Kubernetes in Docker Desktop

Once you have Docker Desktop installed, open the Settings:

Select the Kubernetes menu item on the left and verify that the Enable Kubernetes is checked. If it isn’t, check it and click the Apply button at the bottom right:

Reference:

• Kubernetes.io - Get Started with Kubernetes using Python
• Github.com - JasonHaley/hello-python