mirror of https://github.com/docker/docs.git
Add Java get started guide (#12725)
* Adg Java get started guide Signed-off-by: Usha Mandya <usha.mandya@docker.com> * Address review comments Signed-off-by: Usha Mandya <usha.mandya@docker.com> * Fix alignment issues Signed-off-by: Usha Mandya <usha.mandya@docker.com> * Fix style issues Signed-off-by: Usha Mandya <usha.mandya@docker.com>
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Usha Mandya
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@ -85,6 +85,18 @@ guides:
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section:
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- title: "Overview"
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path: /language/java/
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- title: "Build images"
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path: /language/java/build-images/
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- title: "Run containers"
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path: /language/java/run-containers/
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- title: "Develop your app"
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path: /language/java/develop/
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- title: "Run your tests"
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path: /language/java/run-tests/
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- title: "Configure CI/CD"
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path: /language/java/configure-ci-cd/
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- title: "Deploy your app"
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path: /language/java/deploy/
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- sectiontitle: Develop with Docker
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section:
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- path: /develop/
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@ -0,0 +1,239 @@
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---
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title: "Build your Java image"
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keywords: Java, build, images, dockerfile
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description: Learn how to build your first Docker image by writing a Dockerfile
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---
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{% include_relative nav.html selected="1" %}
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## Prerequisites
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Work through the orientation and setup in Get started [Part 1](../../get-started/index.md){:target="_blank" rel="noopener" class="_"} to understand Docker concepts. Refer to the following section for Java prerequisites.
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## Overview
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Now that we have a good overview of containers and the Docker platform, let’s take a look at building our first image. An image includes everything needed to run an application - the code or binary, runtime, dependencies, and any other file system objects required.
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To complete this tutorial, you need the following:
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- Java OpenJDK version 15 or later. [Download and install Java](https://jdk.java.net/){: target="_blank" rel="noopener" class="_"}
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- Docker running locally. Follow the instructions to [download and install Docker](../../get-docker.md)
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- A Git client
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- An IDE or a text editor to edit files. We recommend using [IntelliJ Community Edition](https://www.jetbrains.com/idea/download/){: target="_blank" rel="noopener" class="_"}.
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## Sample application
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Let’s clone the sample application that we'll be using in this module to our local development machine. Run the following commands in a terminal to clone the repo.
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```console
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$ cd /path/to/working/directory
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$ git clone https://github.com/spring-projects/spring-petclinic.git
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$ cd spring-petclinic
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```
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## Test the application
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Let’s start our application and make sure it is running properly. Maven will manage all the project processes (compiling, tests, packaging, etc). The **Spring Pets Clinic** project we cloned earlier contains an embedded version of Maven. Therefore, we don't need to install Maven separately on your local machine.
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Open your terminal and navigate to the working directory we created and run the following command:
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```console
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$ ./mvnw spring-boot:run
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```
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This downloads the dependencies, builds the project, and starts it.
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To test that the application is working properly, open a new browser and navigate to `http://localhost:8080`.
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Switch back to the terminal where our server is running and you should see the following requests in the server logs. The data will be different on your machine.
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```console
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o.s.s.petclinic.PetClinicApplication : Started
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PetClinicApplication in 11.743 seconds (JVM running for 12.364)
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```
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## Create a Dockerfile for Java
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Now that our application is running properly, let’s take a look at creating a Dockerfile.
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A Dockerfile is a text document that contains all the commands a user could call on the command line to assemble an image. When we tell Docker to build our image by executing the `docker build` command, Docker reads these instructions and execute them sequentially and creates a Docker image.
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Let’s walk through the steps on creating a Dockerfile for our application. In the root of your working directory, create a file named `Dockerfile` and open this file in your text editor.
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> **Note**
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>
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> The name of the Dockerfile is not important but the default filename for many commands is simply `Dockerfile`. Therefore, we’ll use that as our filename throughout this series.
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The first line to add to the Dockerfile is a [`# syntax` parser directive](/engine/reference/builder/#syntax).
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While _optional_, this directive instructs the Docker builder what syntax to use
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when parsing the Dockerfile, and allows older Docker versions with BuildKit enabled
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to upgrade the parser before starting the build. Parser directives
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must appear before any other comment, whitespace, or Dockerfile instruction in
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your Dockerfile, and should be the first line in Dockerfiles.
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```dockerfile
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# syntax=docker/dockerfile:1
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```
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We recommend using `docker/dockerfile:1`, which always points to the latest release
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of the version 1 syntax. BuildKit automatically checks for updates of the syntax
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before building, making sure you are using the most current version.
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Next, we need to add a line in our Dockerfile that tells Docker what base image
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we would like to use for our application.
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```dockerfile
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# syntax=docker/dockerfile:1
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FROM openjdk:16-alpine3.13
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```
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Docker images can be inherited from other images. Therefore, instead of creating our own base image, we’ll use the official Maven image with Java JDK that already has all the tools and packages that we need to run a Java application.
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> **Note**
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>
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> To learn more about creating your own base images, see [Creating base images](https://docs.docker.com/develop/develop-images/baseimages/).
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To make things easier when running the rest of our commands, let’s create a working directory. This instructs Docker to use this path as the default location for all subsequent commands. By doing this, we do not have to type out full file paths but can use relative paths based on the working directory.
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```dockerfile
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WORKDIR /app
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```
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Usually, the very first thing you do once you’ve downloaded a project written in Java which is using Maven for project management is to install dependencies.
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Before we can run `mvnw dependency`, we need to get the Maven wrapper and our `pom.xml` file into our image. We’ll use the `COPY` command to do this. The `COPY` command takes two parameters. The first parameter tells Docker what file(s) you would like to copy into the image. The second parameter tells Docker where you want that file(s) to be copied to. We’ll copy all those files and directories into our working directory - `/app`.
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```dockerfile
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COPY .mvn/ .mvn
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COPY mvnw pom.xml ./
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```
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Once we have our `pom.xml` file inside the image, we can use the `RUN` command to execute the command `mvnw dependency:go-offline`. This works exactly the same way as if we were running `mvnw` (or mvn) dependency locally on our machine, but this time the dependencies will be installed into the image.
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```dockerfile
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RUN ./mvnw dependency:go-offline
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```
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At this point, we have an Alpine version 3.13 image that is based on OpenJDK version 16, and we have also installed our dependencies. The next thing we need to do is to add our source code into the image. We’ll use the `COPY` command just like we did with our `pom.xml` file above.
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```dockerfile
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COPY src ./src
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```
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This `COPY` command takes all the files located in the current directory and copies them into the image. Now, all we have to do is to tell Docker what command we want to run when our image is executed inside a container. We do this using the `CMD` command.
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```dockerfile
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CMD ["./mvnw", "spring-boot:run"]
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```
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Here's the complete Dockerfile.
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```dockerfile
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# syntax=docker/dockerfile:1
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FROM openjdk:16-alpine3.13
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WORKDIR /app
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COPY .mvn/ .mvn
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COPY mvnw pom.xml ./
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RUN ./mvnw dependency:go-offline
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COPY src ./src
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CMD ["./mvnw", "spring-boot:run"]
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```
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### Create a `.dockerignore` file
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To use a file in the build context, the Dockerfile refers to the file specified in an instruction, for example, a `COPY` instruction. To increase the performance of the build, and to exclude files and directories, we recommend that you create a `.dockerignore` file to the context directory. To improve the context load time, add a `target` directory within the `.dockerignore` file.
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## Build an image
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Now that we’ve created our Dockerfile, let’s build our image. To do this, we use the `docker build` command. The `docker build` command builds Docker images from a Dockerfile and a “context”. A build’s context is the set of files located in the specified PATH or URL. The Docker build process can access any of the files located in this context.
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The build command optionally takes a `--tag` flag. The tag is used to set the name of the image and an optional tag in the format `name:tag`. We’ll leave off the optional `tag` for now to help simplify things. If we do not pass a tag, Docker uses “latest” as its default tag. You can see this in the last line of the build output.
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Let’s build our first Docker image.
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```console
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$ docker build --tag java-docker .
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```
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```console
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Sending build context to Docker daemon 5.632kB
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Step 1/7 : FROM java:3.7-alpine
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Step 2/7 : WORKDIR /app
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...
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Successfully built a0bb458aabd0
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Successfully tagged java-docker:latest
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```
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## View local images
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To see a list of images we have on our local machine, we have two options. One is to use the CLI and the other is to use [Docker Desktop](../../desktop/dashboard.md#explore-your-images). As we are currently working in the terminal let’s take a look at listing images using the CLI.
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To list images, simply run the `docker images` command.
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```console
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$ docker images
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REPOSITORY TAG IMAGE ID CREATED SIZE
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java-docker latest b1b5f29f74f0 47 minutes ago 567MB
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```
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You should see at least the we just built `java-docker:latest`.
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## Tag images
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An image name is made up of slash-separated name components. Name components may contain lowercase letters, digits, and separators. A separator is defined as a period, one or two underscores, or one or more dashes. A name component may not start or end with a separator.
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An image is made up of a manifest and a list of layers. Do not worry too much about manifests and layers at this point other than a “tag” points to a combination of these artifacts. You can have multiple tags for an image. Let’s create a second tag for the image we built and take a look at its layers.
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To create a new tag for the image we’ve built above, run the following command:
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```console
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$ docker tag java-docker:latest java-docker:v1.0.0
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```
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The `docker tag` command creates a new tag for an image. It does not create a new image. The tag points to the same image and is just another way to reference the image.
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Now, run the `docker images` command to see a list of our local images.
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```console
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$ docker images
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REPOSITORY TAG IMAGE ID CREATED SIZE
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java-docker latest b1b5f29f74f0 59 minutes ago 567MB
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java-docker v1.0.0 b1b5f29f74f0 59 minutes ago 567MB
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```
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You can see that we have two images that start with `java-docker`. We know they are the same image because if you take a look at the `IMAGE ID` column, you can see that the values are the same for the two images.
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Let’s remove the tag that we just created. To do this, we’ll use the `rmi` command. The `rmi` command stands for “remove image”.
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```console
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$ docker rmi java-docker:v1.0.0
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Untagged: java-docker:v1.0.0
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```
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Note that the response from Docker tells us that the image has not been removed but only “untagged”. You can check this by running the `docker images` command.
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```console
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$ docker images
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REPOSITORY TAG IMAGE ID CREATED SIZE
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java-docker latest b1b5f29f74f0 59 minutes ago 567MB
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```
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Our image that was tagged with `:v1.0.0` has been removed, but we still have the `java-docker:latest` tag available on our machine.
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## Next steps
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In this module, we took a look at setting up our example Java application that we'll use for the rest of the tutorial. We also created a Dockerfile that we used to build our Docker image. Then, we took a look at tagging our images and removing images. In the next module, we’ll take a look at how to:
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[Run your image as a container](run-containers.md){: .button .primary-btn}
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## Feedback
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Help us improve this topic by providing your feedback. Let us know what you think by creating an issue in the [Docker Docs](https://github.com/docker/docker.github.io/issues/new?title=[Java%20docs%20feedback]){:target="_blank" rel="noopener" class="_"} GitHub repository. Alternatively, [create a PR](https://github.com/docker/docker.github.io/pulls){:target="_blank" rel="noopener" class="_"} to suggest updates.
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<br />
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@ -0,0 +1,300 @@
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---
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title: "Configure CI/CD for your application"
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keywords: Java, CI/CD, local, development
|
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description: Learn how to Configure CI/CD for your application
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---
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{% include_relative nav.html selected="5" %}
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This page guides you through the process of setting up a GitHub Action CI/CD pipeline with Docker containers. Before setting up a new pipeline, we recommend that you take a look at [Ben's blog](https://www.docker.com/blog/best-practices-for-using-docker-hub-for-ci-cd/){:target="_blank" rel="noopener" class="_"} on CI/CD best practices .
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This guide contains instructions on how to:
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1. Use a sample Docker project as an example to configure GitHub Actions
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2. Set up the GitHub Actions workflow
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3. Optimize your workflow to reduce the number of pull requests and the total build time
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4. Push only specific versions to Docker Hub
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5. Optimize your image using multi-stage builds
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## Set up a Docker project
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Let’s get started. This guide uses a simple Docker project as an example. The [SimpleWhaleDemo](https://github.com/usha-mandya/SimpleWhaleDemo){:target="_blank" rel="noopener" class="_"} repository contains an Ngnix alpine image. You can either clone this repository, or use your own Docker project.
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{:width="500px"}
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Before we start, ensure you can access [Docker Hub](https://hub.docker.com/) from any workflows you create. To do this:
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1. Add your Docker ID as a secret to GitHub. Navigate to your GitHub repository and click **Settings** > **Secrets** > **New secret**.
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2. Create a new secret with the name `DOCKER_HUB_USERNAME` and your Docker ID as value.
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3. Create a new Personal Access Token (PAT). To create a new token, go to [Docker Hub Settings](https://hub.docker.com/settings/security) and then click **New Access Token**.
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4. Let’s call this token **simplewhaleci**.
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{:width="500px"}
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5. Now, add this Personal Access Token (PAT) as a second secret into the GitHub secrets UI with the name `DOCKER_HUB_ACCESS_TOKEN`.
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{:width="500px"}
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## Set up the GitHub Actions workflow
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In the previous section, we created a PAT and added it to GitHub to ensure we can access Docker Hub from any workflow. Now, let’s set up our GitHub Actions workflow to build and store our images in Hub. We can achieve this by creating two Docker actions:
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1. The first action enables us to log in to Docker Hub using the secrets we stored in the GitHub Repository.
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2. The second one is the build and push action.
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In this example, let us set the push flag to `true` as we also want to push. We’ll then add a tag to specify to always go to the latest version. Lastly, we’ll echo the image digest to see what was pushed.
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To set up the workflow:
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1. Go to your repository in GitHub and then click **Actions** > **New workflow**.
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2. Click **set up a workflow yourself** and add the following content:
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First, we will name this workflow:
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|
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```yaml
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name: CI to Docker Hub
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```
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Then, we will choose when we run this workflow. In our example, we are going to do it for every push against the main branch of our project:
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```yaml
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on:
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push:
|
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branches: [ main ]
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```
|
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|
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Now, we need to specify what we actually want to happen within our action (what jobs), we are going to add our build one and select that it runs on the latest Ubuntu instances available:
|
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|
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```yaml
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jobs:
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|
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build:
|
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runs-on: ubuntu-latest
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```
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|
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Now, we can add the steps required. The first one checks-out our repository under `$GITHUB_WORKSPACE`, so our workflow can access it. The second is to use our PAT and username to log into Docker Hub. The third is the Builder, the action uses BuildKit under the hood through a simple Buildx action which we will also setup
|
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|
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{% raw %}
|
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```yaml
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steps:
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|
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- name: Check Out Repo
|
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uses: actions/checkout@v2
|
||||
|
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- name: Login to Docker Hub
|
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uses: docker/login-action@v1
|
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with:
|
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username: ${{ secrets.DOCKER_HUB_USERNAME }}
|
||||
password: ${{ secrets.DOCKER_HUB_ACCESS_TOKEN }}
|
||||
|
||||
- name: Set up Docker Buildx
|
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id: buildx
|
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uses: docker/setup-buildx-action@v1
|
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|
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- name: Build and push
|
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id: docker_build
|
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uses: docker/build-push-action@v2
|
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with:
|
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context: ./
|
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file: ./Dockerfile
|
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push: true
|
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tags: ${{ secrets.DOCKER_HUB_USERNAME }}/simplewhale:latest
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|
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- name: Image digest
|
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run: echo ${{ steps.docker_build.outputs.digest }}
|
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```
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{% endraw %}
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|
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Now, let the workflow run for the first time and then tweak the Dockerfile to make sure the CI is running and pushing the new image changes:
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|
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{:width="500px"}
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|
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## Optimize the workflow
|
||||
|
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Next, let’s look at how we can optimize the GitHub Actions workflow through build cache. This has two main advantages:
|
||||
|
||||
1. Build cache reduces the build time as it will not have to re-download all of the images, and
|
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2. It also reduces the number of pulls we complete against Docker Hub. We need to make use of GitHub cache to make use of this.
|
||||
|
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Let us set up a Builder with a build cache. First, we need to set up cache for the builder. In this example, let us add the path and keys to store this under using GitHub cache for this.
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|
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{% raw %}
|
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```yaml
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|
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- name: Cache Docker layers
|
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uses: actions/cache@v2
|
||||
with:
|
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path: /tmp/.buildx-cache
|
||||
key: ${{ runner.os }}-buildx-${{ github.sha }}
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restore-keys: |
|
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${{ runner.os }}-buildx-
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```
|
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{% endraw %}
|
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|
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And lastly, after adding the builder and build cache snippets to the top of the Actions file, we need to add some extra attributes to the build and push step. This involves:
|
||||
|
||||
Setting up the builder to use the output of the buildx step, and then
|
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Using the cache we set up earlier for it to store to and to retrieve
|
||||
|
||||
{% raw %}
|
||||
```yaml
|
||||
- name: Login to Docker Hub
|
||||
uses: docker/login-action@v1
|
||||
with:
|
||||
username: ${{ secrets.DOCKER_HUB_USERNAME }}
|
||||
password: ${{ secrets.DOCKER_HUB_ACCESS_TOKEN }}
|
||||
- name: Build and push
|
||||
id: docker_build
|
||||
uses: docker/build-push-action@v2
|
||||
with:
|
||||
context: ./
|
||||
file: ./Dockerfile
|
||||
builder: ${{ steps.buildx.outputs.name }}
|
||||
push: true
|
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tags: ${{ secrets.DOCKER_HUB_USERNAME }}/simplewhale:latest
|
||||
cache-from: type=local,src=/tmp/.buildx-cache
|
||||
cache-to: type=local,dest=/tmp/.buildx-cache
|
||||
- name: Image digest
|
||||
run: echo ${{ steps.docker_build.outputs.digest }}
|
||||
```
|
||||
{% endraw %}
|
||||
|
||||
Now, run the workflow again and verify that it uses the build cache.
|
||||
|
||||
## Push tagged versions to Docker Hub
|
||||
|
||||
Earlier, we learnt how to set up a GitHub Actions workflow to a Docker project, how to optimize the workflow by setting up a builder with build cache. Let’s now look at how we can improve it further. We can do this by adding the ability to have tagged versions behave differently to all commits to master. This means, only specific versions are pushed, instead of every commit updating the latest version on Docker Hub.
|
||||
|
||||
You can consider this approach to have your commits go to a local registry to then use in nightly tests. By doing this, you can always test what is latest while reserving your tagged versions for release to Docker Hub.
|
||||
|
||||
This involves two steps:
|
||||
|
||||
1. Modifying the GitHub workflow to only push commits with specific tags to Docker Hub
|
||||
2. Setting up a GitHub Actions file to store the latest commit as an image in the GitHub registry
|
||||
|
||||
First, let us modify our existing GitHub workflow to only push to Hub if there’s a particular tag. For example:
|
||||
|
||||
{% raw %}
|
||||
```yaml
|
||||
on:
|
||||
push:
|
||||
tags:
|
||||
- "v*.*.*"
|
||||
```
|
||||
{% endraw %}
|
||||
|
||||
This ensures that the main CI will only trigger if we tag our commits with `V.n.n.n.` Let’s test this. For example, run the following command:
|
||||
|
||||
```bash
|
||||
git tag -a v1.0.2
|
||||
git push origin v1.0.2
|
||||
```
|
||||
|
||||
Now, go to GitHub and check your Actions
|
||||
|
||||
{:width="500px"}
|
||||
|
||||
Now, let’s set up a second GitHub action file to store our latest commit as an image in the GitHub registry. You may want to do this to:
|
||||
|
||||
1. Run your nightly tests or recurring tests, or
|
||||
2. To share work in progress images with colleagues.
|
||||
|
||||
Let’s clone our previous GitHub action and add back in our previous logic for all pushes. This will mean we have two workflow files, our previous one and our new one we will now work on.
|
||||
Next, change your Docker Hub login to a GitHub container registry login:
|
||||
|
||||
{% raw %}
|
||||
```yaml
|
||||
if: github.event_name != 'pull_request'
|
||||
uses: docker/login-action@v1
|
||||
with:
|
||||
registry: ghcr.io
|
||||
username: ${{ github.repository_owner }}
|
||||
password: ${{ secrets.GHCR_TOKEN }}
|
||||
```
|
||||
{% endraw %}
|
||||
|
||||
Remember to change how the image is tagged. The following example keeps ‘latest’ as the only tag. However, you can add any logic to this if you prefer:
|
||||
|
||||
{% raw %}
|
||||
```yaml
|
||||
tags: ghcr.io/${{ github.repository_owner }}/simplewhale:latest
|
||||
```
|
||||
{% endraw %}
|
||||
|
||||
{:width="500px"}
|
||||
|
||||
Now, we will have two different flows: one for our changes to master, and one for our pull requests. Next, we need to modify what we had before to ensure we are pushing our PRs to the GitHub registry rather than to Docker Hub.
|
||||
|
||||
## Optimize your image using multi-stage builds
|
||||
|
||||
Now, let’s take a look at the Dockerfile and see how we can optimize it to work in development, as well as get smaller images to run containers in production. As this is the last step in the file, it will be used by default to build the image when you run a docker build without specifying the target:
|
||||
|
||||
```console
|
||||
$ docker build --tag java-docker .
|
||||
docker build --tag java-docker .
|
||||
|
||||
[+] Building 1.2s (15/15) FINISHED
|
||||
=> [internal] load build definition from Dockerfile
|
||||
=> => transferring dockerfile: 37B
|
||||
=> [internal] load .dockerignore
|
||||
=> => transferring context: 2B
|
||||
=> [internal] load metadata for docker.io/library/openjdk:11-jre-slim
|
||||
=> [internal] load metadata for docker.io/library/openjdk:16-alpine3.13
|
||||
=> [internal] load build context
|
||||
=> => transferring context: 11.48kB
|
||||
=> [production 1/2] FROM docker.io/library/openjdk:11-jre-slim@sha256:85795599f4c765182c414a1eb4e272841e18e2f267ce5010ea6a266f7f26e7f6
|
||||
=> [base 1/6] FROM docker.io/library/openjdk:16-alpine3.13@sha256:49d822f4fa4deb5f9d0201ffeec9f4d113bcb4e7e49bd6bc063d3ba93aacbcae
|
||||
=> CACHED [base 2/6] WORKDIR /app
|
||||
=> CACHED [base 3/6] COPY .mvn/ .mvn
|
||||
=> CACHED [base 4/6] COPY mvnw pom.xml ./
|
||||
=> CACHED [base 5/6] RUN ./mvnw dependency:go-offline
|
||||
=> CACHED [base 6/6] COPY src ./src
|
||||
=> CACHED [build 1/1] RUN ./mvnw package
|
||||
=> CACHED [production 2/2] COPY --from=build /app/target/spring-petclinic-*.jar /spring-petclinic.jar
|
||||
=> exporting to image
|
||||
=> => exporting layers
|
||||
=> => writing image sha256:c17469b9e2f30537060f48bbe5d9d22003dd35edef7092348824a2438101ab3a
|
||||
=> => naming to docker.io/library/java-docker
|
||||
```
|
||||
|
||||
The second interesting point is that this step doesn’t take the base target or a JDK image as reference. Instead, it uses a Java Runtime Environment image.
|
||||
Note that you don’t need a large image with all the development dependencies to run your application in production. Limiting the number of dependencies in production images can significantly limit the attack surface.
|
||||
|
||||
```dockerfile
|
||||
FROM openjdk:11-jre-slim as production
|
||||
EXPOSE 8080
|
||||
|
||||
COPY --from=build /app/target/spring-petclinic-*.jar /spring-petclinic.jar
|
||||
|
||||
CMD ["java", "-Djava.security.egd=file:/dev/./urandom", "-jar", "/spring-petclinic.jar"]
|
||||
```
|
||||
|
||||
The container will also automatically expose its 8080 port and copies the Java Archive produced in build step to use it at container startup.
|
||||
|
||||
The production image built in this way only contains a runtime environment with the final application archive, just what you need to start your Spring Pet Clinic application.
|
||||
|
||||
```console
|
||||
$ docker build --tag java-docker:jdk . --target development
|
||||
$ docker build --tag java-docker:jre .
|
||||
$ docker images
|
||||
REPOSITORY TAG IMAGE ID CREATED SIZE
|
||||
java-docker jre c17469b9e2f3 3 hours ago 270MB
|
||||
java-docker jdk 4c15436d8ab7 5 hours ago 567MB
|
||||
```
|
||||
|
||||
## Next steps
|
||||
|
||||
In this module, you have learnt how to set up GitHub Actions workflow to an existing Docker project, optimize your workflow to improve build times and reduce the number of pull requests, and finally, we learnt how to push only specific versions to Docker Hub. You can also set up nightly tests against the latest tag, test each PR, or do something more elegant with the tags we are using and make use of the Git tag for the same tag in our image.
|
||||
|
||||
You can also consider deploying your application to the cloud. For detailed instructions, see:
|
||||
|
||||
[Deploy your application to the cloud](deploy.md){: .button .primary-btn}
|
||||
|
||||
## Feedback
|
||||
|
||||
Help us improve this topic by providing your feedback. Let us know what you think by creating an issue in the [Docker Docs](https://github.com/docker/docker.github.io/issues/new?title=[Java%20docs%20feedback]){:target="_blank" rel="noopener" class="_"} GitHub repository. Alternatively, [create a PR](https://github.com/docker/docker.github.io/pulls){:target="_blank" rel="noopener" class="_"} to suggest updates.
|
||||
|
||||
<br />
|
||||
|
|
@ -0,0 +1,29 @@
|
|||
---
|
||||
title: "Deploy your app to the cloud"
|
||||
keywords: deploy, ACI, ECS, Java, local, development
|
||||
description: Learn how to deploy your application to the cloud.
|
||||
---
|
||||
|
||||
{% include_relative nav.html selected="6" %}
|
||||
|
||||
Now, that we have configured a CI/CD pipleline, let's look at how we can deploy the application to cloud. Docker supports deploying containers on Azure ACI and AWS ECS.
|
||||
|
||||
## Docker and ACI
|
||||
|
||||
The Docker Azure Integration enables developers to use native Docker commands to run applications in Azure Container Instances (ACI) when building cloud-native applications. The new experience provides a tight integration between Docker Desktop and Microsoft Azure allowing developers to quickly run applications using the Docker CLI or VS Code extension, to switch seamlessly from local development to cloud deployment.
|
||||
|
||||
For detailed instructions, see [Deploying Docker containers on Azure](../../cloud/aci-integration.md).
|
||||
|
||||
## Docker and ECS
|
||||
|
||||
The Docker ECS Integration enables developers to use native Docker commands in Docker Compose CLI to run applications in Amazon EC2 Container Service (ECS) when building cloud-native applications.
|
||||
|
||||
The integration between Docker and Amazon ECS allows developers to use the Docker Compose CLI to set up an AWS context in one Docker command, allowing you to switch from a local context to a cloud context and run applications quickly and easily simplify multi-container application development on Amazon ECS using Compose files.
|
||||
|
||||
For detailed instructions, see [Deploying Docker containers on ECS](../../cloud/ecs-integration.md).
|
||||
|
||||
## Feedback
|
||||
|
||||
Help us improve this topic by providing your feedback. Let us know what you think by creating an issue in the [Docker Docs](https://github.com/docker/docker.github.io/issues/new?title=[Java%20docs%20feedback]){:target="_blank" rel="noopener" class="_"} GitHub repository. Alternatively, [create a PR](https://github.com/docker/docker.github.io/pulls){:target="_blank" rel="noopener" class="_"} to suggest updates.
|
||||
|
||||
<br />
|
||||
|
|
@ -0,0 +1,198 @@
|
|||
---
|
||||
title: "Use containers for development"
|
||||
keywords: Java, local, development, run,
|
||||
description: Learn how to develop your application locally.
|
||||
---
|
||||
|
||||
{% include_relative nav.html selected="3" %}
|
||||
|
||||
## Prerequisites
|
||||
|
||||
Work through the steps to build an image and run it as a containerized application in [Run your image as a container](run-containers.md).
|
||||
|
||||
## Introduction
|
||||
|
||||
In this module, we’ll walk through setting up a local development environment for the application we built in the previous modules. We’ll use Docker to build our images and Docker Compose to make everything a whole lot easier.
|
||||
|
||||
## Run a database in a container
|
||||
|
||||
First, we’ll take a look at running a database in a container and how we use volumes and networking to persist our data and allow our application to talk with the database. Then we’ll pull everything together into a Compose file which allows us to setup and run a local development environment with one command. Finally, we’ll take a look at connecting a debugger to our application running inside a container.
|
||||
|
||||
Instead of downloading MySQL, installing, configuring, and then running the MySQL database as a service, we can use the Docker Official Image for MySQL and run it in a container.
|
||||
|
||||
Before we run MySQL in a container, we'll create a couple of volumes that Docker can manage to store our persistent data and configuration. Let’s use the managed volumes feature that Docker provides instead of using bind mounts. You can read all about [Using volumes](../../storage/volumes.md) in our documentation.
|
||||
|
||||
Let’s create our volumes now. We’ll create one for the data and one for configuration of MySQL.
|
||||
|
||||
```console
|
||||
$ docker volume create mysql
|
||||
$ docker volume create mysql_config
|
||||
```
|
||||
|
||||
Now we’ll create a network that our application and database will use to talk to each other. The network is called a user-defined bridge network and gives us a nice DNS lookup service which we can use when creating our connection string.
|
||||
|
||||
```console
|
||||
$ docker network create mysqlnet
|
||||
```
|
||||
|
||||
Now, let's run MySQL in a container and attach to the volumes and network we created above. Docker pulls the image from Hub and runs it locally.
|
||||
|
||||
```console
|
||||
$ docker run -it --rm -d -v mysql_data:/var/lib/mysql \
|
||||
-v mysql_config:/etc/mysql/conf.d \
|
||||
--network mysqlnet \
|
||||
--name mysqlserver \
|
||||
-e MYSQL_USER=petclinic -e MYSQL_PASSWORD=petclinic \
|
||||
-e MYSQL_ROOT_PASSWORD=root -e MYSQL_DATABASE=petclinic \
|
||||
-p 3306:3306 mysql:8.0.23
|
||||
```
|
||||
|
||||
Okay, now that we have a running MySQL, let’s update our Dockerfile to activate the MySQL Spring profile defined in the application and switch from an in-memory H2 database to the MySQL server we just created.
|
||||
|
||||
We only need to add the MySQL profil as an argument to the `CMD` definition.
|
||||
|
||||
```dockerfile
|
||||
CMD ["./mvnw", "spring-boot:run", "-Dspring-boot.run.profiles=mysql"]
|
||||
```
|
||||
|
||||
Let's build our image
|
||||
|
||||
```console
|
||||
$ docker build --tag java-docker .
|
||||
```
|
||||
|
||||
Now, let’s run our container. This time, we need to set the `MYSQL_URL` environment variable so that our application knows what connection string to use to access the database. We’ll do this using the `docker run` command.
|
||||
|
||||
```console
|
||||
$ docker run --rm -d \
|
||||
--name springboot-server \
|
||||
--network mysqlnet \
|
||||
-e MYSQL_URL=jdbc:mysql://mysqlserver/petclinic \
|
||||
-p 8080:8080 java-docker
|
||||
```
|
||||
|
||||
Let’s test that our application is connected to the database and is able to list Veterinarians.
|
||||
|
||||
```console
|
||||
$ curl --request GET \
|
||||
--url http://localhost:8080/vets \
|
||||
--header 'content-type: application/json'
|
||||
```
|
||||
|
||||
You should receive the following json back from our service.
|
||||
|
||||
```json
|
||||
{"vetList":[{"id":1,"firstName":"James","lastName":"Carter","specialties":[],"nrOfSpecialties":0,"new":false},{"id":2,"firstName":"Helen","lastName":"Leary","specialties":[{"id":1,"name":"radiology","new":false}],"nrOfSpecialties":1,"new":false},{"id":3,"firstName":"Linda","lastName":"Douglas","specialties":[{"id":3,"name":"dentistry","new":false},{"id":2,"name":"surgery","new":false}],"nrOfSpecialties":2,"new":false},{"id":4,"firstName":"Rafael","lastName":"Ortega","specialties":[{"id":2,"name":"surgery","new":false}],"nrOfSpecialties":1,"new":false},{"id":5,"firstName":"Henry","lastName":"Stevens","specialties":[{"id":1,"name":"radiology","new":false}],"nrOfSpecialties":1,"new":false},{"id":6,"firstName":"Sharon","lastName":"Jenkins","specialties":[],"nrOfSpecialties":0,"new":false}]}
|
||||
```
|
||||
|
||||
## Use Compose to develop locally
|
||||
|
||||
In this section, we’ll create a Compose file to start our `java-docker` and the MySQL database using a single command. We’ll also set up the Compose file to start the `java-docker` application in debug mode so that we can connect a debugger to the running Java process.
|
||||
|
||||
Open the `petclinic` in your IDE or a text editor and create a new file named `docker-compose.dev.yml`. Copy and paste the following commands into the file.
|
||||
|
||||
```yaml
|
||||
version: '3.8'
|
||||
services:
|
||||
petclinic:
|
||||
build:
|
||||
context: .
|
||||
ports:
|
||||
- 8000:8000
|
||||
- 8080:8080
|
||||
environment:
|
||||
- SERVER_PORT=8080
|
||||
- MYSQL_URL=jdbc:mysql://mysqlserver/petclinic
|
||||
volumes:
|
||||
- ./:/app
|
||||
command: ./mvnw spring-boot:run -Dspring-boot.run.profiles=mysql -Dspring-boot.run.jvmArguments="-agentlib:jdwp=transport=dt_socket,server=y,suspend=n,address=*:8000"
|
||||
|
||||
mysqlserver:
|
||||
image: mysql:8.0.23
|
||||
ports:
|
||||
- 3306:3306
|
||||
environment:
|
||||
- MYSQL_ROOT_PASSWORD=
|
||||
- MYSQL_ALLOW_EMPTY_PASSWORD=true
|
||||
- MYSQL_USER=petclinic
|
||||
- MYSQL_PASSWORD=petclinic
|
||||
- MYSQL_DATABASE=petclinic
|
||||
volumes:
|
||||
- mysql_data:/var/lib/mysql
|
||||
- mysql_config:/etc/mysql/conf.d
|
||||
volumes:
|
||||
mysql_data:
|
||||
mysql_config:
|
||||
```
|
||||
|
||||
This Compose file is super convenient as we do not have to type all the parameters to pass to the `docker run` command. We can declaratively do that using a Compose file.
|
||||
|
||||
We expose port 8000 and declare the debug configuration for the JVM so that we can attach a debugger.
|
||||
|
||||
Another really cool feature of using a Compose file is that we have service resolution set up to use the service names. Therefore, we are now able to use `mysqlserver` in our connection string. The reason we use `mysqlserver` is because that is what we've named our MySQL service as in the Compose file.
|
||||
|
||||
Now, to start our application and to confirm that it is running properly.
|
||||
|
||||
```console
|
||||
$ docker-compose -f docker-compose.dev.yml up --build
|
||||
```
|
||||
|
||||
We pass the `--build` flag so Docker will compile our image and then starts the containers. You should see similar output if it runs successfully:
|
||||
|
||||
|
||||
|
||||
Now let’s test our API endpoint. Run the following curl commands:
|
||||
|
||||
```console
|
||||
$ curl --request GET \
|
||||
--url http://localhost:8080/vets \
|
||||
--header 'content-type: application/json'
|
||||
```
|
||||
|
||||
You should receive the following response:
|
||||
|
||||
```json
|
||||
{"vetList":[{"id":1,"firstName":"James","lastName":"Carter","specialties":[],"nrOfSpecialties":0,"new":false},{"id":2,"firstName":"Helen","lastName":"Leary","specialties":[{"id":1,"name":"radiology","new":false}],"nrOfSpecialties":1,"new":false},{"id":3,"firstName":"Linda","lastName":"Douglas","specialties":[{"id":3,"name":"dentistry","new":false},{"id":2,"name":"surgery","new":false}],"nrOfSpecialties":2,"new":false},{"id":4,"firstName":"Rafael","lastName":"Ortega","specialties":[{"id":2,"name":"surgery","new":false}],"nrOfSpecialties":1,"new":false},{"id":5,"firstName":"Henry","lastName":"Stevens","specialties":[{"id":1,"name":"radiology","new":false}],"nrOfSpecialties":1,"new":false},{"id":6,"firstName":"Sharon","lastName":"Jenkins","specialties":[],"nrOfSpecialties":0,"new":false}]}
|
||||
```
|
||||
|
||||
## Connect a Debugger
|
||||
|
||||
We’ll use the debugger that comes with the IntelliJ IDEA. You can use the community version of this IDE. Open your project in IntelliJ IDEA and then go to the **Run** menu > **Edit Configuration**. Add a new Remote JVM Debug configuration similar to the following:
|
||||
|
||||
|
||||
|
||||
Let's set a breakpoint
|
||||
|
||||
Open the following file `src/main/java/org/springframework/samples/petclinic/vet/VetController.java` and add a breakpoint inside the `showResourcesVetList` function, line 54 for example.
|
||||
|
||||
Start your debug session, **Run** menu and then **Debug _NameOfYourConfiguration_**
|
||||
|
||||
|
||||
|
||||
You should now see the connection in the logs of your Compose application.
|
||||
|
||||
|
||||
|
||||
We can now call the server endpoint.
|
||||
|
||||
```console
|
||||
$ curl --request GET --url http://localhost:8080/vets
|
||||
```
|
||||
|
||||
You should have seen the code break on line 54 and now you are able to use the debugger just like you would normally. You can also inspect and watch variables, set conditional breakpoints, view stack traces and a do bunch of other stuff.
|
||||
|
||||
|
||||
|
||||
You can also activate the live reload option provided by SpringBoot Dev Tools. Check out the [SpringBoot documentation](https://docs.spring.io/spring-boot/docs/current/reference/html/using-spring-boot.html#using-boot-devtools-remote){:target="_blank" rel="noopener" class="_"} for information on how to connect to a remote application.
|
||||
|
||||
## Next steps
|
||||
|
||||
In this module, we took a look at creating a general development image that we can use pretty much like our normal command line. We also set up our Compose file to expose the debugging port and configure Spring Boot to live reload our changes.
|
||||
|
||||
In the next module, we’ll take a look at how to run unit tests in Docker. See
|
||||
|
||||
[Run your tests](run-tests.md){: .button .primary-btn}
|
||||
|
||||
## Feedback
|
||||
|
||||
Help us improve this topic by providing your feedback. Let us know what you think by creating an issue in the [Docker Docs](https://github.com/docker/docker.github.io/issues/new?title=[Java%20docs%20feedback]){:target="_blank" rel="noopener" class="_"} GitHub repository. Alternatively, [create a PR](https://github.com/docker/docker.github.io/pulls){:target="_blank" rel="noopener" class="_"} to suggest updates.
|
||||
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|
|
@ -1,20 +1,25 @@
|
|||
---
|
||||
description: Containerize Java apps using Docker
|
||||
title: Getting started with Java
|
||||
keywords: Docker, getting started, java, language
|
||||
title: What will you learn in this module?
|
||||
description: Containerize Java apps using Docker
|
||||
toc_min: 1
|
||||
toc_max: 2
|
||||
---
|
||||
|
||||
> ### Coming soon
|
||||
>
|
||||
> Thanks for your interest in learning how to containerize a Java application. We are actively writing this guide. Watch this space!
|
||||
|
||||
Meanwhile, here's an outline of the tasks we are planning to cover. Here's an outline of what we'd like to cover. Using the Java getting started guide, you'll learn how to:
|
||||
The Java getting started guide teaches you how to create a containerized Spring Boot application using Docker. In this module, you’ll learn how to:
|
||||
|
||||
* Clone and run a Spring Boot application with Maven
|
||||
* Create a new Dockerfile which contains instructions required to build a Java image
|
||||
* Build an image and run the newly built image as a container
|
||||
* Set up a local development environment to connect a database to the container, and use Docker Compose to run the application.
|
||||
* Configure a CI/CD pipeline for your application using GitHub Actions.
|
||||
* Run the newly built image as a container
|
||||
* Set up a local development environment to connect a database to the container
|
||||
* Use Docker Compose to run the Spring Boot application
|
||||
* Configure a CI/CD pipeline for your application using GitHub Actions
|
||||
* Deploy your application to the cloud
|
||||
|
||||
After completing the Java getting started modules, you should be able to containerize your own Java application based on the examples and instructions provided in this guide.
|
||||
|
||||
Let’s get started!
|
||||
|
||||
[Build your first Java image](build-images.md){: .button .primary-btn}
|
||||
|
||||
<br />
|
||||
|
|
|
|||
|
|
@ -0,0 +1,8 @@
|
|||
<ul class="pagination">
|
||||
<li {% if include.selected=="1"%}class="active"{% endif %}><a href="/language/java/build-images/">Build images</a></li>
|
||||
<li {% if include.selected=="2"%}class="active"{% endif %}><a href="/language/java/run-containers/">Run your image as a container</a></li>
|
||||
<li {% if include.selected=="3"%}class="active"{% endif %}><a href="/language/java/develop/">Use containers for development</a></li>
|
||||
<li {% if include.selected=="4"%}class="active"{% endif %}><a href="/language/java/run-tests/">Run tests</a></li>
|
||||
<li {% if include.selected=="5"%}class="active"{% endif %}><a href="/language/java/configure-ci-cd/">Configure CI/CD</a></li>
|
||||
<li {% if include.selected=="6"%}class="active"{% endif %}><a href="/language/java/deploy/">Deploy your app</a></li>
|
||||
</ul>
|
||||
|
|
@ -0,0 +1,185 @@
|
|||
---
|
||||
title: "Run your image as a container"
|
||||
keywords: Java, run, image, container,
|
||||
description: Learn how to run the image as a container.
|
||||
---
|
||||
|
||||
{% include_relative nav.html selected="2" %}
|
||||
|
||||
## Prerequisites
|
||||
|
||||
Work through the steps to build a Java image in [Build your Java image](build-images.md).
|
||||
|
||||
## Overview
|
||||
|
||||
In the previous module, we created our sample application and then we created a Dockerfile that we used to build an image. We created our image using the command `docker build`. Now that we have an image, we can run that image and see if our application is running correctly.
|
||||
|
||||
A container is a normal operating system process except that this process is isolated and has its own file system, its own networking, and its own isolated process tree separated from the host.
|
||||
|
||||
To run an image inside a container, we use the `docker run` command. The `docker run` command requires one parameter which is the name of the image. Let’s start our image and make sure it is running correctly. Run the following command in your terminal:
|
||||
|
||||
```console
|
||||
$ docker run java-docker
|
||||
```
|
||||
|
||||
After running this command, you’ll notice that we did not to the command prompt. This is because our application is a REST server and runs in a loop waiting for incoming requests without returning control back to the OS until we stop the container.
|
||||
|
||||
Let’s open a new terminal then make a `GET` request to the server using the `curl` command.
|
||||
|
||||
```console
|
||||
$ curl --request GET \
|
||||
--url http://localhost:8080/actuator/health \
|
||||
--header 'content-type: application/json'
|
||||
curl: (7) Failed to connect to localhost port 8080: Connection refused
|
||||
```
|
||||
|
||||
As you can see, our `curl` command failed because the connection to our server was refused. This means, we were not able to connect to the localhost on port 8080. This is expected because our container is run in isolation which includes networking. Let’s stop the container and restart with port 8080 published on our local network.
|
||||
|
||||
To stop the container, press `ctrl-c`. This will return you to the terminal prompt.
|
||||
|
||||
To publish a port for our container, we’ll use the `--publish flag` (`-p` for short) on the `docker run` command. The format of the `--publish` command is `[host port]:[container port]`. So, if we wanted to expose port 8000 inside the container to port 8080 outside the container, we would pass `8080:8000` to the `--publish` flag.
|
||||
|
||||
Start the container and expose port 8080 to port 8080 on the host.
|
||||
|
||||
```console
|
||||
$ docker run --publish 8080:8080 java-docker
|
||||
```
|
||||
|
||||
Now, let’s rerun the curl command from above.
|
||||
|
||||
```console
|
||||
$ curl --request GET \
|
||||
--url http://localhost:8080/actuator/health \
|
||||
--header 'content-type: application/json'
|
||||
{"status":"UP"}
|
||||
```
|
||||
|
||||
Success! We were able to connect to the application running inside of our container on port 8080.
|
||||
|
||||
Now, press ctrl-c to stop the container.
|
||||
|
||||
## Run in detached mode
|
||||
|
||||
This is great so far, but our sample application is a web server and we don't have to be connected to the container. Docker can run your container in detached mode or in the background. To do this, we can use the `--detach` or `-d` for short. Docker starts your container as earlier, but this time, it will “detach” from the container and return you to the terminal prompt.
|
||||
|
||||
```console
|
||||
$ docker run -d -p 8080:8080 java-docker
|
||||
5ff83001608c7b787dbe3885277af018aaac738864d42c4fdf5547369f6ac752
|
||||
```
|
||||
|
||||
Docker started our container in the background and printed the Container ID on the terminal.
|
||||
|
||||
Again, let’s make sure that our container is running properly. Run the same curl command from above.
|
||||
|
||||
```console
|
||||
$ curl --request GET \
|
||||
--url http://localhost:8080/actuator/health \
|
||||
--header 'content-type: application/json'
|
||||
{"status":"UP"}
|
||||
```
|
||||
|
||||
## List containers
|
||||
|
||||
As we ran our container in the background, how do we know if our container is running, or what other containers are running on our machine? Well, we can run the `docker ps` command. Just like how we run the `ps` command in Linux to see a list of processes on our machine, we can run the `docker ps` command to view a list of containers running on our machine.
|
||||
|
||||
```console
|
||||
$ docker ps
|
||||
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
|
||||
5ff83001608c java-docker "./mvnw spring-boot:…" About a minute ago Up About a minute 0.0.0.0:8080->8080/tcp trusting_beaver
|
||||
```
|
||||
|
||||
The `docker ps` command provides a bunch of information about our running containers. We can see the container ID, the image running inside the container, the command that was used to start the container, when it was created, the status, ports that exposed and the name of the container.
|
||||
|
||||
You are probably wondering where the name of our container is coming from. Since we didn’t provide a name for the container when we started it, Docker generated a random name. We’ll fix this in a minute, but first we need to stop the container. To stop the container, run the `docker stop` command which does just that, stops the container. We need to pass the name of the container or we can use the container ID.
|
||||
|
||||
```console
|
||||
$ docker stop trusting_beaver
|
||||
trusting_beaver
|
||||
```
|
||||
|
||||
Now, rerun the `docker ps` command to see a list of running containers.
|
||||
|
||||
```console
|
||||
$ docker ps
|
||||
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
|
||||
```
|
||||
|
||||
## Stop, start, and name containers
|
||||
|
||||
You can start, stop, and restart Docker containers. When we stop a container, it is not removed, but the status is changed to stopped and the process inside the container is stopped. When we ran the `docker ps` command in the previous module, the default output only shows running containers. When we pass the `--all` or `-a` for short, we see all containers on our machine, irrespective of their start or stop status.
|
||||
|
||||
```console
|
||||
$ docker ps -a
|
||||
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
|
||||
5ff83001608c java-docker "./mvnw spring-boot:…" 5 minutes ago Exited (143) 18 seconds ago trusting_beaver
|
||||
630f2872ddf5 java-docker "./mvnw spring-boot:…" 11 minutes ago Exited (1) 8 minutes ago modest_khayyam
|
||||
a28f9d587d95 java-docker "./mvnw spring-boot:…" 17 minutes ago Exited (1) 11 minutes ago lucid_greider
|
||||
```
|
||||
|
||||
You should now see several containers listed. These are containers that we started and stopped, but have not been removed.
|
||||
|
||||
Let’s restart the container that we just stopped. Locate the name of the container we just stopped and replace the name of the container below using the `restart` command.
|
||||
|
||||
```console
|
||||
$ docker restart trusting_beaver
|
||||
```
|
||||
|
||||
Now, list all the containers again using the `docker ps` command.
|
||||
|
||||
```console
|
||||
$ docker ps -a
|
||||
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
|
||||
5ff83001608c java-docker "./mvnw spring-boot:…" 10 minutes ago Up 2 seconds 0.0.0.0:8080->8080/tcp trusting_beaver
|
||||
630f2872ddf5 java-docker "./mvnw spring-boot:…" 16 minutes ago Exited (1) 13 minutes ago modest_khayyam
|
||||
a28f9d587d95 java-docker "./mvnw spring-boot:…" 22 minutes ago Exited (1) 16 minutes ago lucid_greider
|
||||
```
|
||||
|
||||
Notice that the container we just restarted has been started in detached mode and has port 8080 exposed. Also, observe the status of the container is “Up X seconds”. When you restart a container, it starts with the same flags or commands that it was originally started with.
|
||||
|
||||
Now, let’s stop and remove all of our containers and take a look at fixing the random naming issue. Find the name of your running container and replace the name in the command below with the name of the container on your system.
|
||||
|
||||
```console
|
||||
$ docker stop trusting_beaver
|
||||
trusting_beaver
|
||||
```
|
||||
|
||||
Now that our container is stopped, let’s remove it. When you remove a container, the process inside the container will be stopped and the metadata for the container will been removed.
|
||||
|
||||
To remove a container, simple run the `docker rm` command passing the container name. You can pass multiple container names to the command using a single command. Again, replace the container names in the following command with the container names from your system.
|
||||
|
||||
```console
|
||||
$ docker rm trusting_beaver modest_khayyam lucid_greider
|
||||
trusting_beaver
|
||||
modest_khayyam
|
||||
lucid_greider
|
||||
```
|
||||
|
||||
Run the `docker ps --all` command again to see that all containers are removed.
|
||||
|
||||
Now, let’s address the random naming issue. The standard practice is to name your containers for the simple reason that it is easier to identify what is running in the container and what application or service it is associated with.
|
||||
|
||||
To name a container, we just need to pass the `--name` flag to the `docker run` command.
|
||||
|
||||
```console
|
||||
$ docker run --rm -d -p 8080:8080 --name springboot-server java-docker
|
||||
2e907c68d1c98be37d2b2c2ac6b16f353c85b3757e549254de68746a94a8a8d3
|
||||
$ docker ps
|
||||
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
|
||||
2e907c68d1c9 java-docker "./mvnw spring-boot:…" 8 seconds ago Up 8 seconds 0.0.0.0:8080->8080/tcp springboot-server
|
||||
```
|
||||
|
||||
That’s better! We can now easily identify our container based on the name.
|
||||
|
||||
## Next steps
|
||||
|
||||
In this module, we took a look at running containers, publishing ports, and running containers in detached mode. We also took a look at managing containers by starting, stopping, and, restarting them. We also looked at naming our containers so they are more easily identifiable.
|
||||
|
||||
In the next module, we’ll learn how to run a database in a container and connect it to our application. See:
|
||||
|
||||
[Use containers for development](develop.md){: .button .primary-btn}
|
||||
|
||||
## Feedback
|
||||
|
||||
Help us improve this topic by providing your feedback. Let us know what you think by creating an issue in the [Docker Docs](https://github.com/docker/docker.github.io/issues/new?title=[Java%20docs%20feedback]){:target="_blank" rel="noopener" class="_"} GitHub repository. Alternatively, [create a PR](https://github.com/docker/docker.github.io/pulls){:target="_blank" rel="noopener" class="_"} to suggest updates.
|
||||
|
||||
<br />
|
||||
|
|
@ -0,0 +1,217 @@
|
|||
---
|
||||
title: "Run your tests"
|
||||
keywords: Java, build, test
|
||||
description: How to build and run your Tests
|
||||
---
|
||||
|
||||
{% include_relative nav.html selected="4" %}
|
||||
|
||||
## Prerequisites
|
||||
|
||||
Work through the steps to build an image and run it as a containerized application in [Use your container for development](develop.md).
|
||||
|
||||
## Introduction
|
||||
|
||||
Testing is an essential part of modern software development. Testing can mean a lot of things to different development teams. There are unit tests, integration tests and end-to-end testing. In this guide we take a look at running your unit tests in Docker.
|
||||
|
||||
## Refactor Dockerfile to run tests
|
||||
|
||||
The **Spring Pet Clinic** source code has already tests defined in the test directory `src/test/java/org/springframework/samples/petclinic`. You just need to update the JaCoCo version in your `pom.xml` to ensure your tests work with JDK v15 or higher with `<jacoco.version>0.8.6</jacoco.version>`, so we can use the following Docker command to start the container and run tests:
|
||||
|
||||
```shell
|
||||
$ docker run -it --rm --name springboot-test java-docker ./mvnw test
|
||||
...
|
||||
[INFO] Results:
|
||||
[INFO]
|
||||
[WARNING] Tests run: 40, Failures: 0, Errors: 0, Skipped: 1
|
||||
[INFO]
|
||||
[INFO] ------------------------------------------------------------------------
|
||||
[INFO] BUILD SUCCESS
|
||||
[INFO] ------------------------------------------------------------------------
|
||||
[INFO] Total time: 01:49 min
|
||||
```
|
||||
|
||||
### Multi-stage Dockerfile for testing
|
||||
|
||||
Let’s take a look at pulling the testing commands into our Dockerfile. Below is a multi-stage Dockerfile that we will use to build our production image and our test image. Add the highlighted lines to your Dockerfile
|
||||
|
||||
```dockerfile
|
||||
# syntax=docker/dockerfile:1
|
||||
|
||||
FROM openjdk:16-alpine3.13 as base
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
COPY .mvn/ .mvn
|
||||
COPY mvnw pom.xml ./
|
||||
RUN ./mvnw dependency:go-offline
|
||||
COPY src ./src
|
||||
|
||||
FROM base as test
|
||||
CMD ["./mvnw", "test"]
|
||||
|
||||
FROM base as development
|
||||
CMD ["./mvnw", "spring-boot:run", "-Dspring-boot.run.profiles=mysql", "-Dspring-boot.run.jvmArguments='-agentlib:jdwp=transport=dt_socket,server=y,suspend=n,address=*:8000'"]
|
||||
|
||||
FROM base as build
|
||||
RUN ./mvnw package
|
||||
|
||||
FROM openjdk:11-jre-slim as production
|
||||
EXPOSE 8080
|
||||
|
||||
COPY --from=build /app/target/spring-petclinic-*.jar /spring-petclinic.jar
|
||||
|
||||
CMD ["java", "-Djava.security.egd=file:/dev/./urandom", "-jar", "/spring-petclinic.jar"]
|
||||
```
|
||||
|
||||
We first add a label to the `FROM openjdk:16-alpine3.13` statement. This allows us to refer to this build stage in other build stages. Next, we added a new build stage labeled `test`. We'll use this stage for running our tests.
|
||||
|
||||
Now let’s rebuild our image and run our tests. We will run the `docker build` command as above, but this time we will add the `--target test` flag so that we specifically run the test build stage.
|
||||
|
||||
```shell
|
||||
$ docker build -t java-docker --target test .
|
||||
[+] Building 0.7s (6/6) FINISHED
|
||||
...
|
||||
=> => writing image sha256:967ac80cb7799a5d12a4bdfc67c37b5a6533c6e418c903907d3e86b7d4ebf89a
|
||||
=> => naming to docker.io/library/java-docker
|
||||
```
|
||||
|
||||
Now that our test image is built, we can run it as a container and see if our tests pass.
|
||||
|
||||
```shell
|
||||
$ docker run -it --rm --name springboot-test java-docker
|
||||
[INFO] Scanning for projects...
|
||||
[INFO]
|
||||
[INFO] ------------< org.springframework.samples:spring-petclinic >------------
|
||||
[INFO] Building petclinic 2.4.2
|
||||
...
|
||||
|
||||
[INFO] Results:
|
||||
[INFO]
|
||||
[WARNING] Tests run: 40, Failures: 0, Errors: 0, Skipped: 1
|
||||
[INFO]
|
||||
[INFO] ------------------------------------------------------------------------
|
||||
[INFO] BUILD SUCCESS
|
||||
[INFO] ------------------------------------------------------------------------
|
||||
[INFO] Total time: 01:22 min
|
||||
```
|
||||
|
||||
The build output is truncated, but you can see that the Maven test runner was successful and all our tests passed.
|
||||
|
||||
This is great. However, we'll have to run two Docker commands to build and run our tests. We can improve this slightly by using a `RUN` statement instead of the `CMD` statement in the test stage. The `CMD` statement is not executed during the building of the image, but is executed when you run the image in a container. When using the `RUN` statement, our tests run when the building the image, and stop the build when they fail.
|
||||
|
||||
Update your Dockerfile with the highlighted line below.
|
||||
|
||||
```dockerfile
|
||||
# syntax=docker/dockerfile:1
|
||||
|
||||
FROM openjdk:16-alpine3.13 as base
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
COPY .mvn/ .mvn
|
||||
COPY mvnw pom.xml ./
|
||||
RUN ./mvnw dependency:go-offline
|
||||
COPY src ./src
|
||||
|
||||
FROM base as test
|
||||
RUN ["./mvnw", "test"]
|
||||
|
||||
FROM base as development
|
||||
CMD ["./mvnw", "spring-boot:run", "-Dspring-boot.run.profiles=mysql", "-Dspring-boot.run.jvmArguments='-agentlib:jdwp=transport=dt_socket,server=y,suspend=n,address=*:8000'"]
|
||||
|
||||
FROM base as build
|
||||
RUN ./mvnw package
|
||||
|
||||
FROM openjdk:11-jre-slim as production
|
||||
EXPOSE 8080
|
||||
|
||||
COPY --from=build /app/target/spring-petclinic-*.jar /spring-petclinic.jar
|
||||
|
||||
CMD ["java", "-Djava.security.egd=file:/dev/./urandom", "-jar", "/spring-petclinic.jar"]
|
||||
```
|
||||
|
||||
Now, to run our tests, we just need to run the `docker build` command as above.
|
||||
|
||||
```shell
|
||||
$ docker build -t java-docker --target test .
|
||||
[+] Building 27.6s (11/12)
|
||||
=> CACHED [base 3/6] COPY .mvn/ .mvn
|
||||
=> CACHED [base 4/6] COPY mvnw pom.xml ./
|
||||
=> CACHED [base 5/6] RUN ./mvnw dependency:go-offline
|
||||
=> CACHED [base 6/6] COPY src ./src
|
||||
=> [test 1/1] RUN ["./mvnw", "test", "-Dspring-boot.run.profiles=mysql"]
|
||||
=> exporting to image
|
||||
=> => exporting layers
|
||||
=> => writing image sha256:10cb585a7f289a04539e95d583ae97bcf8725959a6bd32c2f5632d0e7c1d16a0
|
||||
=> => naming to docker.io/library/java-docker
|
||||
```
|
||||
|
||||
The build output is truncated for simplicity, but you can see that our tests ran succesfully and passed. Let’s break one of the tests and observe the output when our tests fail.
|
||||
|
||||
Open the `src/test/java/org/springframework/samples/petclinic/model/ValidatorTests.java` file and change **line 57** to the following.
|
||||
|
||||
```shell
|
||||
55 ConstraintViolation<Person> violation = constraintViolations.iterator().next();
|
||||
57 assertThat(violation.getPropertyPath().toString()).isEqualTo("firstName");
|
||||
57 assertThat(violation.getMessage()).isEqualTo("must be empty");
|
||||
58 }
|
||||
```
|
||||
|
||||
Now, run the `docker build` command from above and observe that the build fails and the failing testing information is printed to the console.
|
||||
|
||||
```shell
|
||||
$ docker build -t java-docker --target test .
|
||||
=> [base 6/6] COPY src ./src
|
||||
=> ERROR [test 1/1] RUN ["./mvnw", "test", "-Dspring-boot.run.profiles=mysql"]
|
||||
...
|
||||
------
|
||||
executor failed running [./mvnw test]: exit code: 1
|
||||
```
|
||||
|
||||
### Multi-stage Dockerfile for development
|
||||
|
||||
The new version of the Dockerfile produces a final image which is ready for production, but as you can notice, you also have a dedicated step to produce a development container.
|
||||
|
||||
```dockerfile
|
||||
FROM base as development
|
||||
CMD ["./mvnw", "spring-boot:run", "-Dspring-boot.run.profiles=mysql", "-Dspring-boot.run.jvmArguments='-agentlib:jdwp=transport=dt_socket,server=y,suspend=n,address=*:8000'"]
|
||||
```
|
||||
|
||||
We can now update of our `docker-compose.dev.yml` to use this specific target to build the `petclinic` service and remove the `command` definition as follows:
|
||||
|
||||
```dockerfile
|
||||
services:
|
||||
petclinic:
|
||||
build:
|
||||
context: .
|
||||
target: development
|
||||
ports:
|
||||
- 8000:8000
|
||||
- 8080:8080
|
||||
environment:
|
||||
- SERVER_PORT=8080
|
||||
- MYSQL_URL=jdbc:mysql://mysqlserver/petclinic
|
||||
volumes:
|
||||
- ./:/app
|
||||
```
|
||||
|
||||
Now, let's run the Compose application. You should now see that application behaves as previously and you can still debug it.
|
||||
|
||||
```shell
|
||||
$ docker-compose -f docker-compose.dev.yml up --build
|
||||
```
|
||||
|
||||
## Next steps
|
||||
|
||||
In this module, we took a look at running tests as part of our Docker image build process.
|
||||
|
||||
In the next module, we’ll take a look at how to set up a CI/CD pipeline using GitHub Actions. See:
|
||||
|
||||
[Configure CI/CD](configure-ci-cd.md){: .button .primary-btn}
|
||||
|
||||
## Feedback
|
||||
|
||||
Help us improve this topic by providing your feedback. Let us know what you think by creating an issue in the [Docker Docs](https://github.com/docker/docker.github.io/issues/new?title=[Java%20docs%20feedback]){:target="_blank" rel="noopener" class="_"} GitHub repository. Alternatively, [create a PR](https://github.com/docker/docker.github.io/pulls){:target="_blank" rel="noopener" class="_"} to suggest updates.
|
||||
|
||||
<br />
|
||||
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Reference in New Issue