Reading Time: 4 Minutes
In this post, We’ll show how you can launch Kotlin Application in Kubernetes.
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.
To know more about Kotlin Language, you may Love to read our Blog Overview of Kotlin Language & Comparison Between Kotlin & Java
To follow this guide you need
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 Kotlin application.
Container-Registry - The Container Registry is an online image store for container images.
Below mentioned options are few most popular registries.
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.
The below mentioned command will build your application 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 Docker Hub registry to publish images to the Kubernetes cluster.
Create an account on Docker Hub and create a Public/Private Repository of you application name.
To login to your docker hub account, Execute below-mentioned command.
Now we need to retag Kotlin application image and push them to docker hub container registry.
To Retag application container image
To Push application container Images
Similarly, we can push images to any of above-mentioned container registry like Docker Hub, AWS ECR, Google Container Registry, Private Docker Registry etc.
Deploying application on kubernetes with ease using deployment and service files either in JSON or YAML format.
Following Content is for “<name of application>.deployment.yml” file of python container application.
Following Content is for “<name of application>.service.yml” file of python container application.
Kotlin Application Container can be deployed either by kubernetes Dashboard or Kubectl (Command line).
I`m explaining command line that you can use in production Kubernetes cluster.
Now we have successfully deployed Kotlin Application on Kubernetes.
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.
Result of above command
Get the External Node Port using the below-mentioned command. External Node Port are in the range from 30000 to 65000.
Launch 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>
Your Kotlin application should be a stateless application before your application scaling.
You can scale out an application by so many ways.Here I have mentioned two of them which are mostly used.
kubectl scale --current-replicas=1 --replicas=3 deployment/<name of your application>
Update your deployment from kubernetes dashboard
Check Status of Pods.
Check Logs of Pods/Containers.
Check Service Port Status.
Check requirements/dependencies of application.
At XenonStack we have specialized professionals that can help you in starting with Microservices Architecture, NoSQL and SQL Database, Docker & Kubernetes. Reach Us for Development, Deployment, and Consulting for MicroServices, Kubernetes, and Docker Technology Solutions.
Product NexaStack - Unified DevOps Platform Provides monitoring of Kubernetes, Docker, OpenStack infrastructure, Big Data Infrastructure and uses advanced machine learning techniques for Log Mining and Log Analytics.
Product ElixirData - Modern Data Integration Platform Enables enterprises and Different agencies for Log Analytics and Log Mining.
Product Akira.AI is an Automated & Knowledge Drive Artificial Intelligence Platform that enables you to automate the Infrastructure to train and deploy Deep Learning Models on Public Cloud as well as On-Premises.