Spring Boot 4 Microservices & REST APIs · レッスン

Spring BootアプリケーションのDocker化

Dockerfileを作成し、Spring Bootアプリケーションを軽量で移植性の高いコンテナにパッケージ化します。

「Spring BootアプリケーションのDocker化」はCoddyKit上の無料Spring Boot 4 Microservices & REST APIsレッスンです。これはレッスン1/3です。下記で完全なレッスンを無料で読むことができます。その後、ブラウザ内の組み込みコードエディタと24時間対応のAIチューターでハンズオン演習できます。これはSpring Boot 4 Microservices & REST APIs学習パスの一部であり、ウェブとCoddyKitアプリ全体で進捗が同期されます。 Spring Boot 4 Microservices & REST APIsコースには全3レッスンが含まれています。

このレッスンの一部はまだ翻訳されておらず、英語で表示されています。

Why Dockerize Spring Boot?

Welcome to containerizing Spring Boot apps! Docker helps package your application into a standardized unit called a container.

Why is this great for Spring Boot?

Portability: Run your app consistently anywhere Docker runs.
Isolation: Your app and its dependencies are bundled together, avoiding conflicts.
Consistency: The environment is the same from development to production.

Docker Fundamentals for Apps

Before we dive in, let's quickly define key Docker terms:

Image: A lightweight, standalone, executable package that includes everything needed to run a piece of software, including the code, a runtime, libraries, environment variables, and config files. Think of it as a blueprint.
Container: A runnable instance of an image. You can create, start, stop, move, or delete a container. It's the actual running application.
Dockerfile: A text file that contains all the commands, in order, to build a given image.

Our Sample Spring Boot App

Let's imagine we have a simple Spring Boot application. When we build it, it typically produces a single executable JAR file (e.g., my-app.jar).

Here's a basic Spring Boot application structure:

package com.coddykit.docker;

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;

@SpringBootApplication
public class DockerApp {

  public static void main(String[] args) {
    SpringApplication.run(DockerApp.class, args);
    // This will print to the container's standard output
    System.out.println("Spring Boot app started inside Docker!");
  }
}

Introducing the Dockerfile

A Dockerfile is a script of instructions that Docker uses to build an image. It's like a recipe for creating your container environment.

We'll create a file named Dockerfile (no extension) in the root directory of our Spring Boot project. Each line in the Dockerfile is an instruction.

Choosing a Base Image (FROM)

Every Dockerfile starts with the FROM instruction. This specifies the base image your application will build upon. For Java applications, a common choice is an OpenJDK image.

openjdk:17-jdk-slim provides a Java 17 Development Kit (JDK) in a slim, smaller image, which is great for production.

FROM openjdk:17-jdk-slim

Copying Your Application (COPY)

Next, we need to get our compiled Spring Boot JAR file into the Docker image. The COPY instruction does exactly that.

Assuming your built JAR is in target/my-app.jar, we copy it into the image's root directory and rename it to app.jar for simplicity.

COPY target/my-app.jar app.jar

Exposing Ports (EXPOSE)

Spring Boot applications typically run on a specific port, often 8080. The EXPOSE instruction informs Docker that the container listens on the specified network ports at runtime.

While EXPOSE doesn't actually publish the port, it serves as documentation and helps with port mapping when running the container.

EXPOSE 8080

Defining the Entrypoint (ENTRYPOINT)

The ENTRYPOINT instruction configures a container that will run as an executable. This is how we tell Docker to start our Spring Boot application when the container launches.

We use the java -jar app.jar command to execute our application's JAR file.

ENTRYPOINT ["java", "-jar", "app.jar"]

Putting It All Together: Dockerfile

Here's what our complete Dockerfile looks like. You would place this file in the root of your Spring Boot project.

FROM openjdk:17-jdk-slim
VOLUME /tmp
COPY target/docker-app-0.0.1-SNAPSHOT.jar app.jar
EXPOSE 8080
ENTRYPOINT ["java", "-jar", "/app.jar"]

Note: The JAR name might vary based on your project. VOLUME /tmp is often added to support Spring Boot's embedded Tomcat.

Building Your Docker Image

Once your Dockerfile is ready and your Spring Boot application is compiled (e.g., using mvn package), you can build the Docker image.

Navigate to your project's root directory in the terminal and run:

docker build -t my-spring-app .

This command:

docker build: Initiates the image build process.
-t my-spring-app: Tags the image with a name (my-spring-app).
.: Specifies the build context (the current directory, where the Dockerfile is located).

Dockerfile Instruction Check

Which Dockerfile instruction is used to define the command that runs when a container starts from an image?

Recap: Dockerizing Your App

You've successfully learned the basics of Dockerizing a Spring Boot application!

We understood the role of Dockerfiles, images, and containers.
We explored key Dockerfile instructions: FROM, COPY, EXPOSE, and ENTRYPOINT.
You now know how to bundle your Spring Boot JAR into a portable Docker image.

This sets the stage for running your applications consistently in any Docker environment!

よくある質問

「Spring BootアプリケーションのDocker化」レッスンは無料ですか？

はい。「Spring BootアプリケーションのDocker化」の完全なテキストはこのウェブで無料で読めます。インタラクティブに演習し（組み込みコードエディタと24時間対応のAIチューター）、Spring Boot 4 Microservices & REST APIsコースの残りをアンロックするには、CoddyKit PROにアップグレードしてください。 Spring Boot 4 Microservices & REST APIsコースには全3レッスンが含まれています。

「Spring BootアプリケーションのDocker化」で何を学びますか？

Dockerfileを作成し、Spring Bootアプリケーションを軽量で移植性の高いコンテナにパッケージ化します。ブラウザで直接実行するハンズオンコードでSpring Boot 4 Microservices & REST APIsを演習し、24時間対応のAIチューターがレッスンを進める中での質問に答えます。

Spring Boot 4 Microservices & REST APIsを始めるのに経験は必要ですか？

事前経験は必要ありません。CoddyKitのSpring Boot 4 Microservices & REST APIsは初級者から上級者向けに構成されているため、ここから始めるか最初から始めて、自分のペースで進むことができます。これはレッスン1/3です。

「Spring BootアプリケーションのDocker化」レッスンにはどのくらい時間がかかりますか？

ほとんどのCoddyKitレッスンは約5～10分かかります。各レッスンはコンパクトでインタラクティブなので、着実に進歩し、ウェブとアプリ全体で正確に前回の場所から再開できます。

このSpring Boot 4 Microservices & REST APIsレッスンでコードを書いて実行できますか？

はい。すべてのSpring Boot 4 Microservices & REST APIsレッスンに組み込みコードエディタが含まれているため、ブラウザでリアルコードを書いて実行し、即座のAIフィードバックを取得できます。ローカル設定は不要です。

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