Overview of Kotlin Language

In this post, We’ll show how you can launch a Kotlin Application in Kubernetes.

Kotlin is a new programming language from JetBrains. It first appeared in 2011 when JetBrains unveiled their project named “Kotlin”. Kotlin is an Open-Source Language.

Basically like Java, C and C++ – Kotlin is also “statically typed programming language”. Statically typed programming languages are those languages in which variables need not be defined before they are used.

Continuous delivery is a branch of continuous integration. It also concentrates on automating the software delivery process so that teams can quickly and confidently deploy their code to production at any point.

Prerequisites

To follow this guide you need

Kubernetes – Kubernetes is an open-source platform that automates container operations and Minikube is best for testing Kubernetes.

Kubectl – Kubectl is a command-line interface to manage Kubernetes cluster either remotely or locally. To configure kubectl in your machine follow this link.

Shared Persistent Storage – Shared Persistent Storage is permanent storage that we can attach to the Kubernetes container so that we don`t lose our data even container died. We will be using GlusterFS as a persistent data store for Kubernetes container applications.

Kotlin Application Source Code – Application Source Code is source code that we want to run inside a kubernetes container.

Dockerfile – Dockerfile contains a bunch of commands to build a Kotlin application.

Container-Registry – The Container Registry is an online image store for container images.

Below mentioned options are the few most popular registries.

Create a Dockerfile

The below-mentioned code is sample dockerfile for Kotlin applications. In which we are using Maven 3 as a builder for Kotlin applications and OpenJDK 8 as a base development environment. Alpine Linux is used due to its very compact size.

FROM maven: 3 - alpine MAINTAINER XenonStack # Creating Application Source Code Directory RUN mkdir - p / usr / src / app # Setting Home Directory for containers WORKDIR / usr / src / app # Copying src code to Container COPY. / usr / src / app # Building From Source Code RUN mvn clean package # Setting Persistent drive VOLUME["/kotlin-data"] # Exposing Port EXPOSE 8082 # Running Kotlin Application CMD["java", "-jar", "target/<name jar="" kotlin="" of="" your="">.jar"]

Building Kotlin Application Image

The below-mentioned command will build your application container image.

$ docker build - t < name of your Kotlin application > : < version of application >

Publishing Container Image

Now, we publish our Kotlin application container images to any container registry like Docker Hub, AWS ECR, Google Container Registry, Private Docker Registry.

I am using the Docker Hub registry to publish images to the Kubernetes cluster.

To begin with, create an account on Docker Hub and create a Public/Private Repository of your application name.

Now, to login to your docker hub account, Execute the below-mentioned command.

$ docker login

Now, we need to retag Kotlin’s application image and push them to the docker hub container registry.

To Retag application container image

$ docker tag < name of your application > : < version of your application > < your docker hub account > /<name of="" repository="" your="">:<version application="" of="" your="">

To Push application container Images

$ docker push < your docker account > /<name of="" repository="" your="">:<version application="" of="" your="">

Similarly, we can push images to any of the above-mentioned container registries like Docker Hub, AWS ECR, Google Container Registry, Private Docker Registry, etc.

Creating Deployment files for Kubernetes

Deploying application on kubernetes with ease using deployment and service files either in JSON or YAML format.

Deployment File

The following content is for the “<name of application>.deployment.yml” file of the python container application.

apiVersion: extensions / v1beta1 kind: Deployment metadata: name: < name of application > namespace: < namespace of Kubernetes > spec: replicas: 1 template: metadata: labels: k8s - app: < name of application > spec: containers: -name: < name of application > image: < image name > : < version tag > imagePullPolicy: "IfNotPresent" ports: -containerPort: 8082 volumeMounts: -mountPath: /kotlin-data name: < name of application > volumes: -name: < name of application > emptyDir: {}

Service File

The following content is for “<name of application>.service.yml” file of the python container application.

apiVersion: v1 kind: Service metadata: labels: k8s - app: < name of application > name: < name of application > namespace: < namespace of Kubernetes > spec: type: NodePort ports: -port: 7102 selector: k8s - app: < name of application >

Running Kotlin Application on Kubernetes

Kotlin Application Container can be deployed either by kubernetes Dashboard or Kubectl (Command line).

I`m explaining the command line that you can use in production Kubernetes cluster.

$ kubectl create - f < name of application > .deployment.yml $ kubectl create - f < name of application > .service.yml

Now we have successfully deployed Kotlin Application on Kubernetes.

Verification

We can verify application deployment either by using Kubectl or Kubernetes Dashboard.

The below-mentioned command will show you running pods of your application with status running/terminated/stop/created.

$ kubectl get po--namespace = < namespace of kubernetes > | grep < application name >

The result of the above command

< name of your application > -1349584344 - uah2u 1 / 1 Running 0 22 d 10.233 .84 .18 k8 - master

Testing

Get the External Node Port using the below-mentioned command. External Node Port is in the range from 30000 to 65000.

$ kubectl get svc--namespace = < namespace of kubernetes > | grep < application name >

Launch a web browser and open any of the below-mentioned URLs.

HTTP://<kubernetes master IP address >: <application service port number>

HTTP://<cluster IP address >: <application port number>

Application Scaling

Your Kotlin application should be a stateless application before your application scaling.

You can scale out an application in so many ways. Here I have mentioned two of them which are mostly used.

Kubectl

kubectl scale –current-replicas=1 –replicas=3 deployment/<name of your application>

Kubernetes Dashboard

Update your deployment from the kubernetes dashboard

Troubleshooting

Check Status of Pods.

Check Logs of Pods/Containers.

Check Service Port Status.

Check requirements/dependencies of the application.

Conclusion

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