How to Run Aspose.3D for Java in Docker

Microservices, in conjunction with containerization make it possible to easily combine technologies. Docker allows you to easily integrate Aspose.3D functionality into your application, regardless of what technology is in your development stack.

In case you are targeting microservices, or if the main technology in your stack is not .NET, C++ or Java, but you need Aspose.3D functionality, or if you already use Docker in your stack, then you may be interested in utilizing Aspose.3D for Java in a Docker container.

Prerequisites

  • Docker must be installed on your system.

Create a Java Application

In this example, you create a Java application that makes a simple 3d file, saves it and reads it. The application can then be built and run in Docker.

Creating the Java Application

Create a Java application in Eclipse using the following code. In this example, we use Aspose.3D for Java to create a plane in the 3d scene and set the vector and then save it in obj format.

Make the Java Application into a jar package

The following figure shows a way to make a jar package using “Export” menu in Eclipse.

Make Jar using Eclipse

Now that we wrote a Java program using Aspose.3D for Java, we got a jar package. Next we’ll make a dockerfile.

Configuring a Dockerfile

The next step is to create and configure the Dockerfile.

  1. Create the Dockerfile and place it next to the jar package. Keep this file name without extension (the default).
  2. In the Dockerfile, specify:
   FROM williamyeh/java8:latest

   VOLUME /tmp

   ADD TestDocker.jar app.jar

   ENTRYPOINT ["java","-Djava.security.egd=file:/dev/./urandom","-jar","/app.jar"]

Building and Running the Application in Docker

Now the application can be built and run in Docker. Open your favorite command prompt, change directory to the folder with the Dockerfile and run the following command:

docker build -t java-app .

After executing the above command, you will get the output of 3D file. At this point, a Java program has been successfully run in Linux Docker.

Evaluation Version