![]() ![]() In the next session of this post we will look at deploying our container to MiniKube - a local simulation of a Kubernetes cluster. However, Kubernetes is becoming a defacto runtime platform for containers as it offers a lot of useful features, especially if you are running more than 1 container. Now that the application process is exposed via the port 8080 we can use our command line or another application such as a browser to interact with the app.īeing able to run our containers off our Docker host is great and it entirely possible to run on on public cloud environments such as AWS EC2 without an orcahastrator. It can be built with the following command:ĭocker run -it -p 8080:8080 opsian/proglang:v1 The above Dockerfile assumes that the libopsian binary and assembled jar in the root of the codebase and you have changed OPSIAN_SECRET to your opsian API key. The final line, the line starting with CMD, executes our process when we create a container from our image and start it. We move our generated proglang.jar built with gradle into / in the containers OS and rename it app.jar for simplicity. The next 2 lines which begin with COPY move the resources from our local machine to the container. This is considered a good practice in the Docker community. The next 2 lines add a user to the containers images environment so it is not run as root. The openjdk:8-jre is a amd64 Linux distribution which ships with a Java 8 JRE - more information on the base image can be seen in DockerHub. As the jar we built via the gradle:assemble command in the last section requires a JRE to run we need to install an OS with a JRE installed. ![]() The first line specifies the base image which we will deploy our application onto. It's worth taking a couple of minutes to study the Dockerfile. Package import .annotation.GetMapping import .annotation.RestController import import import public class ProgLangController ,applicationVersion=1", "-jar", "/app.jar" ] The code for the build script is as follows: By adding the Gradle plugin for we can ommit the need to put a version on our dependency declaration. ![]() Once the project setup has completed your IDE should have a similar directory structure.īefore the application is built out, we need to add our dependency on the Spring Boot framework. On a side note I am running a Java v1.8.0_171 JDK, but any Java 8 or Java 11 should also work without issues. Start off by creating a new Gradle project with Java language support. However, any good modern IDE with Gradle support should suffice. In this walkthough I will use IntelliJ IDEA Community Edition. As we are demonstrating the power of containerization and orchastration it will be a simple example which will omit the need for cross-service networking or configuration management with tools such as Consul.įirst, start up your favourite IDE. ![]() This tutorial will also work fine with Kotlin or Groovy as the programming language - however, the gradle build specification may look slightly different. For the sake of getting stuff done quickly we will use the Spring Boot JVM framework to build out our application process. In order to deploy something we will create a simple application that returns a programming language from a RESTful endpoint. This is great if you are learning the ins-and-outs of Kubernetes. Instead of using Kubernetes on a public cloud such as GCP or AWS this post will focus on deploying to Minikube which can be installed on Windows, Mac and Linux operating systems. We keep it simple and build an application that returns a programming language name from a REST endpoint, containerize it with Docker, deploy it to Kubernetes and profile it with Opsian's continuous profiler. This blog post aims to show you how to make that easier by continuously profiling using Docker and Kubernetes. One downside to Kubernetes from a performance optimisation perspective is that it can be harder for developers to get profiling data from their production environment. Existing software products that have hit scalability issues tend to undergo change and transformation projects where monolithic codebases are shifted to a micro or nano-service architecture and these have a natural fit to something like Kubernetes. Encapsulting the application runtime in a container and managing through an orchestrator has numerous benefits including lowering the bar for developers managing insfrastructure and simplifying continuous deployment compared to a traditional setup. There are numerous success stories coming out of large companies like Google and distruptive start-ups including Robinhood and Monzo. The use of Docker and Kubernetes has been growing in the JVM community over the past couple of years. ![]()
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