Continuous Integration and Delivery for Monolithic Applications

Continuous Integration (CI) and Continuous Delivery (CD) are essential practices in modern software development. They help to ensure that code changes are integrated and tested frequently, reducing the risk of introducing bugs and making it easier to release new features. While these practices are often associated with microservices architectures, they can also be applied to monolithic applications. In this blog post, we will explore how to implement CI/CD for monolithic applications.

Prerequisites

Before we dive into the details of CI/CD for monolithic applications, let’s review some prerequisites:

1. Version control: A version control system such as Git is essential for managing code changes and collaborating with other developers.
2. Build automation: A build automation tool such as Maven or Gradle is necessary for compiling and packaging the application.
3. Test automation: A test automation framework such as JUnit or TestNG is required for automating unit and integration tests.
4. Containerization: Containerization using Docker or a similar technology can help to ensure consistency across different environments and simplify deployment.

CI/CD Pipeline for Monolithic ApplicationsA typical CI/CD pipeline for a monolithic application consists of the following stages:

1. Build: The application is compiled and packaged into an artifact, such as a JAR or Docker image.
2. Test: Unit and integration tests are run against the artifact to ensure that it is functioning correctly.
3. Deploy: The artifact is deployed to a staging environment for further testing and validation.
4. Release: The artifact is deployed to production, making it available to end-users.

Let’s take a closer look at each stage and how it can be implemented for a monolithic application.

Build StageThe build stage involves compiling and packaging the application into an artifact. For a monolithic application, this typically involves running a build automation tool such as Maven or Gradle. Here’s an example Maven build script:

<project>
  <groupId>com.example</groupId>
  <artifactId>my-monolith</artifactId>
  <version>1.0.0</version>
  <packaging>jar</packaging>
<dependencies>
    <!-- dependencies go here -->
  </dependencies>
  <build>
    <plugins>
      <plugin>
        <groupId>org.apache.maven.plugins</groupId>
        <artifactId>maven-compiler-plugin</artifactId>
        <version>3.8.0</version>
        <configuration>
          <source>1.8</source>
          <target>1.8</target>
        </configuration>
      </plugin>
      <plugin>
        <groupId>org.apache.maven.plugins</groupId>
        <artifactId>maven-jar-plugin</artifactId>
        <version>3.1.0</version>
        <configuration>
          <archive>
            <manifest>
              <mainClass>com.example.MyMonolithApplication</mainClass>
            </manifest>
          </archive>
        </configuration>
      </plugin>
    </plugins>
  </build>
</project>

This script defines a Maven project with a JAR packaging type. It also includes the Maven Compiler Plugin and Maven Jar Plugin to compile the code and package it into a JAR file, respectively.

Test Stage

The test stage involves running unit and integration tests against the artifact produced in the build stage. For a monolithic application, this typically involves running a test automation framework such as JUnit or TestNG. Here’s an example JUnit test class:

import org.junit.Test;
import static org.junit.Assert.assertEquals;
public class MyMonolithTest {
  @Test
  public void testAddition() {
    MyMonolith monolith = new MyMonolith();
    int result = monolith.add(2, 3);
    assertEquals(5, result);
  }
}

This test class defines a single test method that tests the add method of the MyMonolith class.

Deploy Stage

The deploy stage involves deploying the artifact produced in the build stage to a staging environment for further testing and validation. For a monolithic application, this typically involves deploying the artifact to a container such as Docker.

Here's an example Dockerfile:

FROM openjdk:8-jdk-alpine
ARG JAR_FILE=target/*.jar
COPY ${JAR_FILE} app.jar
ENTRYPOINT ["java","-jar","/app.jar"]

This Dockerfile defines a Docker image based on the OpenJDK 8 JDK Alpine image. It copies the JAR file produced by the Maven build script to the image and sets the entry point to run the JAR file.

Release Stage

The release stage involves deploying the artifact produced in the build stage to production, making it available to end-users. For a monolithic application, this typically involves deploying the artifact to a container orchestration platform such as Kubernetes.

Here’s an example Kubernetes deployment manifest:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-monolith
spec:
  replicas: 3
  selector:
    matchLabels:
      app: my-monolith
  template:
    metadata:
      labels:
        app: my-monolith
    spec:
      containers:
      - name: my-monolith
        image: my-registry/my-monolith:latest
        ports:
        - containerPort: 8080

This deployment manifest defines a Kubernetes deployment with three replicas of the my-monolith container. The container is based on the Docker image produced by the Dockerfile and listens on port 8080.

Conclusion

Implementing CI/CD for monolithic applications can help to ensure that code changes are integrated and tested frequently, reducing the risk of introducing bugs and making it easier to release new features. By following the best practices outlined in this blog post, you can create a robust CI/CD pipeline for your monolithic application. Remember to use version control, build automation, test automation, and containerization to create a consistent and reliable pipeline.