Building a CI/CD Pipeline for Java Applications with Jenkins and AWS CodePipeline

Continuous Integration and Continuous Deployment (CI/CD) are essential for delivering software reliably and rapidly. In this guide, we’ll build a professional CI/CD pipeline for a Java application using Jenkins and AWS CodePipeline. By combining Jenkins’s flexibility with AWS CodePipeline’s managed delivery capabilities, you can automate build, test, and deployment processes for faster and safer releases. Many teams host their code and builds on AWS and use CodePipeline for orchestration alongside Jenkins, achieving quick, streamlined releases. We’ll cover every step – from Jenkins setup and AWS service integration to best practices, security, and rollback strategies – in a natural, human-readable format.

Why Jenkins + AWS CodePipeline for CI/CD?

Jenkins is a popular open-source automation server that excels at continuous integration – compiling code, running tests, and packaging applications. AWS CodePipeline, on the other hand, is a managed CI/CD service that automates software release workflows. Using them together leverages the strengths of both: Jenkins can handle complex builds or use existing job configurations, while CodePipeline orchestrates the end-to-end workflow in the cloud (source, build, test, deploy). In our pipeline, CodePipeline will act as the control plane that triggers Jenkins for the build stage and then uses AWS services to deploy the built artifact. For example, the high-level flow will be:

• A developer pushes code to the source repository.
• AWS CodePipeline detects the change and invokes Jenkins to build and test the application.
• If the build succeeds, CodePipeline triggers a deployment (e.g., via AWS CodeDeploy) to release the new version.
• If any stage fails, the pipeline can halt or roll back to a safe state.

According to AWS’s reference architecture, CodePipeline can integrate with Jenkins as a build provider and with CodeDeploy for deployments. In such a setup, “AWS CodePipeline invokes Jenkins to build the application,” then “upon a successful build, AWS CodePipeline triggers deployment on AWS CodeDeploy,” and “AWS CodeDeploy deploys the application onto AWS servers”. This means our Java app’s code will flow from source -> Jenkins (build/test) -> CodePipeline -> CodeDeploy (or another deploy target), fully automated.

Prerequisites and Setup Overview

Before diving into configuration, make sure you have the following in place:

• AWS Account with permissions to use CodePipeline, CodeDeploy, EC2, S3, etc.
• Jenkins Server running on AWS (e.g., an EC2 instance for Jenkins master). We will set up Jenkins on an EC2 and integrate it with AWS.
• Java and Build Tools on Jenkins: Install JDK (Java Development Kit) and your build tool (e.g., Apache Maven or Gradle) on the Jenkins server so it can compile and package the Java application.
• Source Code Repository: e.g., AWS CodeCommit or GitHub/Bitbucket repository containing your Java application code (including any build configuration like pom.xml for Maven). AWS CodePipeline supports CodeCommit, GitHub, etc. for the source stage.
• AWS CLI or IAM Roles: We’ll use IAM roles for permissions. For Jenkins running on EC2, an instance profile with appropriate permissions is recommended (so you don’t need to hard-code AWS credentials).

At a high level, here are the steps we’ll follow:

1. Set Up Jenkins on AWS EC2 – Install Jenkins and required plugins, configure credentials and roles.
2. Configure Jenkins Job for CI – Create a Jenkins project to build the Java app, run tests, and prepare an artifact.
3. Set Up AWS CodeDeploy – (If using CodeDeploy for deployment) Prepare an EC2 environment or AWS Elastic Beanstalk, etc., and install CodeDeploy agent or set up the deployment target.
4. Create AWS CodePipeline – Define the pipeline with Source, Build (Jenkins), and Deploy stages.
5. Integrate Jenkins with CodePipeline – Use the AWS CodePipeline plugin in Jenkins so CodePipeline can trigger jobs and receive artifacts.
6. Run the Pipeline and Verify – Test the end-to-end flow with a code change, and ensure each stage works.
7. Implement Security and Rollback Strategies – Apply best practices for credentials, access control, and enabling rollbacks for failed deployments.

Throughout the tutorial, we’ll also highlight best practices (like using IAM roles, securing Jenkins, etc.) and include a short LinkedIn-ready summary at the end.

Step 1: Setting Up Jenkins on AWS

Launching Jenkins on EC2: Begin by provisioning an EC2 instance that will host Jenkins. You can use an Amazon Linux 2 or Ubuntu server and install Jenkins on it (either via the official Jenkins package or a Docker image). When launching the EC2 instance, attach an IAM role that Jenkins will use to interact with AWS services. As a best practice, use an EC2 instance profile for credentials instead of static AWS keys (plugins.jenkins.io). For example, create an IAM role (e.g., “JenkinsServerRole”) with permissions such as:

• AWSCodePipelineCustomActionAccess – allows Jenkins to poll CodePipeline and get job details (needed for the CodePipeline plugin) docs.aws.amazon.com.
• Permissions to upload/download artifacts to the S3 bucket used by CodePipeline (often included in the above policy).
• (If using CodeDeploy) Permissions to register deployments via CodeDeploy API.

By using an IAM role on the EC2, Jenkins can assume those permissions safely without embedding AWS keys (which aligns with AWS best practices (plugins.jenkins.io).

Installing Jenkins: Once the EC2 is running, install Jenkins. This typically involves:

• Installing Java (Jenkins runs on Java; ensure you have Java 11 or the appropriate version on the server).
• Adding the Jenkins repository and installing via package manager (for Amazon Linux/Red Hat: yum install jenkins after adding repo; for Ubuntu/Debian: use apt). Or run the official Jenkins Docker container if preferred.
• Start the Jenkins service and complete the initial setup wizard in a web browser (you may need to open port 8080 or your configured port in the EC2 Security Group).
• Install Jenkins recommended plugins during setup.

Securing Jenkins: Before integrating with CodePipeline, secure your Jenkins server. At minimum, set up an admin user and password (don’t run Jenkins with the default open security). It’s also recommended to enable SSL (HTTPS) for Jenkins or put it behind a secure proxy. If CodePipeline needs to reach Jenkins (for example, to show build logs links), ensure your network settings (security group, firewall) allow inbound connections on Jenkins’ port only from authorized sources (e.g., your IP or AWS CodePipeline’s IP ranges) and that Jenkins requires authentication (docs.aws.amazon.com). In practice, Jenkins will poll CodePipeline for jobs, so direct inbound access from CodePipeline isn’t strictly required, but securing Jenkins is still critical.

Installing Required Plugins: Next, install the AWS CodePipeline Plugin on Jenkins. This plugin allows Jenkins to act as a build provider for CodePipeline. It will let Jenkins poll for build jobs from CodePipeline and send back build results and artifacts. In Jenkins, go to Manage Jenkins > Manage Plugins, and under Available (or using the Plugin Manager), find and install “AWS CodePipeline Plugin”. It may also install dependencies like AWS SDK. After installation, restart Jenkins if required.

Additionally, if your Java project uses Maven, ensure the Jenkins Maven Integration plugin or Pipeline Maven integration is installed, or have Maven available on the system. Similarly, for Gradle or other build tools, set them up on Jenkins. You might also install the JUnit plugin to archive test results, etc., though not mandatory.

Jenkins Job Setup for Java Build: Now configure a Jenkins project that CodePipeline will trigger. You can use a Freestyle project or a Jenkins Pipeline (declarative Jenkinsfile). For simplicity, we’ll outline a freestyle job configuration:

• New Item > Freestyle Project (name it something like “JavaApp-Build”). This name will be referenced by CodePipeline.
• Source Code Management: Select “AWS CodePipeline” as the SCM source in the job configuration. Fill in the required fields (this will tie the Jenkins job to a specific CodePipeline pipeline and stage). For example, you might provide the AWS region and pipeline name/stage name so Jenkins knows where to poll for changes. The plugin documentation indicates you should also configure a Build Trigger: select Poll SCM and set a schedule (e.g., * * * * * for every minute, or a reasonable interval). This doesn’t poll Git; it polls the CodePipeline job queue for any incoming build job. Essentially, when CodePipeline has a build to run, Jenkins (with this plugin) will pick it up within that schedule.
• Build Steps: Add steps to compile and test the Java application. If using Maven, you could add an “Invoke top-level Maven targets” build step (if Maven plugin is installed) and specify goals like clean package. Alternatively, add an “Execute shell” step to run Maven or Gradle commands. Ensure the build step performs compilation and runs your test suite (e.g., mvn clean verify to compile and run tests). This will catch any failing tests during the CI stage.
• Post-build Actions: Add “AWS CodePipeline Publisher” as a post-build action. This is critical – it tells Jenkins to upload the build output back to AWS CodePipeline. You can configure one or more output artifacts here. For instance, if your build produces a JAR or WAR file, specify its path. If left blank, the entire workspace will be zipped and sent as the artifact. Typically, you might package your Java app as a single artifact (like a .jar or .war file along with an appspec file for CodeDeploy). Configure the artifact name/path according to what CodePipeline expects in the next stage.
• Apply and save this job configuration.

At this point, Jenkins is ready to build our Java application when prompted by CodePipeline. But to complete the loop, we need to set up the AWS side (CodePipeline and deployment target) so that there’s a pipeline to trigger Jenkins and then deploy the output.

Step 2: Setting Up AWS Services for the Pipeline

Now we will prepare the AWS components that our pipeline will use: source control, artifact storage, and deployment target.

Source Repository: If you haven’t already, set up your source code repository. AWS CodeCommit is a fully-managed Git service and works seamlessly with CodePipeline. You can also use GitHub or Bitbucket. For this guide, let’s assume you use AWS CodeCommit for a fully AWS-integrated approach (the steps for GitHub are similar, you’d just authorize CodePipeline to your GitHub repo). Create a CodeCommit repository and push your Java application code to it (including build files like pom.xml). This repo will hold your application source and AWS CodePipeline will watch it for changes.

S3 Artifact Bucket: AWS CodePipeline will automatically create or use an S3 bucket to store pipeline artifacts (intermediate files like the output from Jenkins that will be passed to the deploy stage). You don’t usually need to manually configure this when using the console wizard – just know it exists. Ensure that your pipeline’s service role and the Jenkins role have access to this artifact bucket. (By default, CodePipeline’s service role and the CodePipeline plugin with proper IAM role will handle this).

Deployment Environment: Decide where and how you will deploy the Java application. Common options include:

• AWS CodeDeploy to EC2: CodeDeploy can deploy the built artifact onto a fleet of EC2 instances (or on-prem servers) running your application (e.g., Java app servers). We’ll use CodeDeploy in our example pipeline.
• AWS Elastic Beanstalk: A PaaS for web applications – CodePipeline can deploy to Beanstalk environments (especially for web apps, this is convenient).
• AWS ECS/EKS: If your Java app is containerized, you might push a Docker image to ECR and deploy to ECS or Kubernetes. (This would use CodeBuild or Jenkins to build the Docker image and CodePipeline to deploy, beyond our scope here).
• AWS Lambda or CloudFormation: For serverless or infrastructure, CodePipeline can use these as deploy targets too.

We’ll proceed with CodeDeploy as it’s a straightforward way to deploy to EC2 instances (or even on-prem, if needed) and supports rolling updates and rollbacks. To set up CodeDeploy:

• Open the AWS CodeDeploy console and create a CodeDeploy Application (give it a name like “MyJavaApp”).
• Create a Deployment Group within that application. This defines the target instances for deployment. For example, if you have EC2 instances in an Auto Scaling Group or tagged instances (with a tag like App:MyJavaApp), configure the group to include those. Also specify the deployment settings (e.g., deployment type: rolling, blue/green, etc., and whether to enable automatic rollback – more on that later).
• Attach the CodeDeploy agent on your target EC2 instances. If you use the AWS-provided CodeDeploy Amazon Machine Image or user-data scripts, ensure the agent is installed and running on each instance. This agent is what will actually pull the new application version from S3 and install it during deployments.
• The EC2 instances for deployment should also have an IAM role (e.g., CodeDeploy EC2 role) that grants permissions to access the S3 artifact (so it can download the files) and register with CodeDeploy.

AppSpec File: In your Java application repository, include an appspec.yml (for CodeDeploy) at the root. This file instructs CodeDeploy how to deploy the new version. For a Java app, an appspec.yml might specify to copy the JAR/WAR to a certain directory and include scripts to restart the application or web server. For example, if deploying a Spring Boot fat JAR, your AppSpec might simply copy the jar to /opt/myapp/ and run a script to restart the service. If deploying a WAR to Tomcat, it might copy the WAR to Tomcat’s webapps directory and restart Tomcat. Ensure the build artifact that Jenkins produces includes this appspec and any deploy scripts, so CodeDeploy can use them. (If using Elastic Beanstalk instead, you’d simply deploy the WAR or JAR to Beanstalk – no appspec needed.)

With source, build, and deployment destinations prepped, we can now create the pipeline that ties it all together.

Step 3: Creating the CI/CD Pipeline in AWS CodePipeline

Head over to the AWS CodePipeline console to set up the pipeline:

• Pipeline Creation: Click Create Pipeline. Give it a name (e.g., “MyJavaApp-Pipeline”). Select or create a new service role for CodePipeline – this role allows the pipeline to access other services (CodeCommit, CodeDeploy, etc.). Usually the console will create a role named AWSCodePipelineServiceRole-<pipelineName> with appropriate managed policies. Ensure it has permission to invoke CodeDeploy and read/write the S3 artifact bucket.
• Source Stage: Choose your source provider (e.g., AWS CodeCommit). If CodeCommit, select the repository name and branch (for instance, the main or master branch to watch for code changes). If using GitHub, you’d authorize and select the repo and branch. For CodeCommit, CodePipeline sets up a CloudWatch Events trigger to automatically start the pipeline on new commits. You can also manually start the pipeline anytime. When configuring the source, CodePipeline will output the source code as an artifact (e.g., named “SourceArtifact”). This will be passed to Jenkins in the next stage.
• Build Stage (Jenkins Integration): Add a new stage for build. Choose Build provider as Jenkins. (If Jenkins isn’t an option in the dropdown, double-check that the CodePipeline plugin on Jenkins is installed and Jenkins is running – you may need to register a webhook or simply proceed; Jenkins actually polls for jobs). You will need to specify:
  • The Provider name or Jenkins provider – this is typically a reference to the Jenkins integration. AWS may require you to specify the Jenkins instance or a custom action name. Often, by installing the plugin and having the IAM role setup, “Jenkins” appears as an option. (If you have multiple Jenkins, you could use custom action names.)The Project name – this should match the exact name of the Jenkins job you created (e.g., “JavaApp-Build”). CodePipeline will send build jobs to that project.The Input artifact – select the output from the source stage (e.g., “SourceArtifact” from CodeCommit). The Jenkins plugin will download this artifact (which is basically a zip of your repository at that commit) into the Jenkins workspace.The Output artifact name – e.g., “BuildArtifact”. This is what CodePipeline will call the artifact that Jenkins returns. Make sure this matches what you configured in the Jenkins job’s post-build publisher (they don’t have to have the same name internally, but conceptually it’s the artifact containing your built jar/war and appspec). Jenkins, through the plugin, will upload artifacts back to CodePipeline which stores them in S3.
  When CodePipeline runs, it will create a job in Jenkins via the plugin: Jenkins will detect it, do the build and tests, then if successful, archive and send the output artifact to CodePipeline. You can monitor the Jenkins console output for build progress, and CodePipeline will poll for the job status. This stage will be marked successful or failed based on Jenkins’ result.
• Deploy Stage: Add a stage for deployment. Choose Deploy provider as AWS CodeDeploy (or another service like Elastic Beanstalk, depending on your choice). For CodeDeploy, select the Application Name and Deployment Group that you set up earlier (e.g., Application “MyJavaApp”, Deployment Group “MyJavaApp-Prod” or similar). Also specify the Input artifact for this stage as the output from the build stage (e.g., “BuildArtifact”). CodeDeploy will retrieve that artifact from S3 and deploy it to the specified instances according to your appspec. If you prefer Elastic Beanstalk, you would choose that and specify the Beanstalk environment; CodePipeline would then directly deploy the artifact to Beanstalk.

After adding these stages, review and create the pipeline. AWS CodePipeline will likely run immediately once created (or you can trigger it). On the first run, if your CodeCommit already had code, it will pull the latest commit as source. The pipeline will then invoke Jenkins for the build stage.

Step 4: Executing and Testing the Pipeline

With everything configured, it’s time to test the CI/CD pipeline:

• Initial Run: When the pipeline triggers, check Jenkins to see if the build started. Jenkins (via the plugin) will download the source from CodePipeline’s artifact, then execute the build steps (compile the Java code, run tests). If something is misconfigured (for example, Jenkins can’t connect to CodePipeline or lacks permissions), the build might not start – double-check the IAM role on Jenkins and that the plugin is set up correctly (Jenkins logs can help debug any AWS API permission issues).
• Build Success: If Jenkins builds successfully, it will package the artifact. For instance, Maven will produce a .jar or .war in the target/ directory. Jenkins then uploads the artifact zip back to CodePipeline. CodePipeline receives it and transitions to the Deploy stage.
• Deployment: CodeDeploy will take the artifact and deploy to the target instances. You can watch the deployment in the CodeDeploy console – it will go through steps like ApplicationStop (if defined), DownloadBundle, BeforeInstall, AfterInstall, ApplicationStart, etc., as defined in your appspec hooks. If any step fails (say the app doesn’t start), CodeDeploy will report a failure.
• Pipeline Outcome: If all stages succeed, congratulations – you have a fully working CI/CD pipeline! A commit to the CodeCommit repo will automatically trigger Jenkins to build the new code and then deploy via CodeDeploy. The pipeline provides visibility into each stage.

If something goes wrong:

• Check the CodePipeline execution details for error messages. For example, if Jenkins stage fails, you can click on it and see logs (the CodePipeline plugin should feed logs back, or at least a link to Jenkins).
• On Jenkins, make sure the job polled and picked up the job. The Poll SCM schedule may cause a slight delay – it’s not instant. You can adjust the frequency or trigger a manual build for testing.
• Verify IAM permissions: The Jenkins server’s role needs access to CodePipeline (polling jobs, acknowledging jobs, etc.) and to S3 for artifacts. The CodePipeline service role needs access to CodeDeploy and the S3 bucket as well.
• Ensure the artifacts are handled correctly: If CodeDeploy says it can’t find the file or appspec, verify that the appspec.yml was included in the artifact and the file paths match what CodeDeploy expects.
• Double-check the appspec hooks if deployment fails. For example, if the application didn’t start, the script in ApplicationStart might have an issue.

This initial setup can be iterative – adjust configurations until the pipeline runs smoothly end-to-end.

Step 5: Best Practices and Security Considerations

Setting up the pipeline is half the battle; operational excellence and security is the other half. Here are some best practices and considerations to ensure your CI/CD pipeline is robust and secure:

• Least Privilege IAM Roles: Restrict permissions on the roles we created. The Jenkins EC2 IAM role should only have the minimum access needed (for CodePipeline and S3, maybe CloudWatch logs if needed). The CodePipeline service role should likewise only access the specific resources (it usually has a generated policy scoping to the pipeline’s resources). This limits blast radius in case credentials are compromised.
• No Hard-Coded Credentials: We already applied this by using IAM roles. Do not store AWS access keys on the Jenkins server or in Jenkins job configs. The AWS CodePipeline plugin and AWS CLI can use the instance role transparently. This avoids accidental leakage of keys in logs or code repositories.
• Secure Jenkins Access: As mentioned, enable authentication on Jenkins and use HTTPS if possible. Limit network access to Jenkins (e.g., within a VPC or via a VPN/bastion). AWS CodePipeline doesn’t need inbound access to Jenkins (Jenkins polls CodePipeline), so you can even block all inbound internet traffic and just allow your developers to access Jenkins through a secure channel. Always keep Jenkins and its plugins up to date to patch vulnerabilities.
• Pipeline Artifacts Security: Artifacts in S3 are, by default, encrypted at rest and have permissions such that only the pipeline (and services in the account) can access them. Still, be mindful not to include sensitive information in artifacts unless necessary. If you have secrets (like database passwords) needed during deployment, use AWS Secrets Manager or SSM Parameter Store and retrieve them at deploy time rather than baking in config files.
• Build Isolation: Consider using Jenkins agents (worker nodes) for builds, especially if you want to scale or isolate builds. You could have dynamic build agents (using Jenkins EC2 Plugin or Kubernetes plugin) to execute the Maven build. This isolates the build environment and can be more secure (the master Jenkins only orchestrates).
• Testing and Quality Gates: Integrate automated tests in the pipeline. We included running unit tests. You might also add static code analysis (using tools like SonarQube) or security scans (dependency vulnerability scanners) in Jenkins. Ensuring code quality and security before deployment is a best practice.
• Multiple Environments and Manual Approvals: In production scenarios, you’d typically have multiple stages (Dev, QA, Prod). You can extend CodePipeline with additional stages – e.g., an automated test stage (perhaps using CodeBuild or a Jenkins test stage), a staging deployment, then a manual approval before production deploy. AWS CodePipeline supports manual approval actions, which is useful to gate releases and have humans verify things at critical points.
• Monitoring and Notifications: Set up monitoring for your pipeline and Jenkins. AWS CodePipeline can emit events to Amazon CloudWatch Events or EventBridge – you can trigger notifications (SNS or Slack) on failures or successes. Jenkins can be configured to send email or Slack notifications for failed builds. Also, consider aggregating logs – push Jenkins logs or CodeDeploy logs to CloudWatch Logs for troubleshooting.
• Audit and Logging: Enable AWS CloudTrail to audit who is triggering deployments and changes to the pipeline. On Jenkins, keep an audit log of who triggered jobs or if any configuration changed (Jenkins has a Job Config History plugin for tracking changes). This helps in compliance and debugging.

By following these practices, you ensure that your CI/CD pipeline is not only functional but also secure and maintainable.

Step 6: Rollback Strategies for Safe Deployments

Even with a solid pipeline and tests, deployments can occasionally introduce issues. It’s crucial to have rollback mechanisms to quickly restore a stable version if something goes wrong.

Automatic Rollbacks with CodeDeploy: AWS CodeDeploy has a built-in automatic rollback feature. You can configure the deployment group to auto-rollback if a deployment fails or if certain alarms are triggered (for example, a CloudWatch alarm for high error rate). When enabled, CodeDeploy will automatically redeploy the last known good revision if the new deployment fails. Essentially, it keeps track of the previous successful deployment and rolls back to it in case of failure, treating the rollback as a new deployment of that old version. It’s highly recommended to enable this, especially for production environments, as it provides quick recovery without manual intervention.

Manual Rollbacks: If automatic rollback isn’t enabled or a bug is discovered later (not immediately at deployment), you can perform a manual rollback. This might involve manually re-running the pipeline with a previous version of code. Since CodePipeline retains artifacts for past runs (in S3) and CodeDeploy can deploy any given revision, you could manually trigger a deployment of the last good artifact. One way is to keep track of versioned artifacts (e.g., include version numbers or build IDs in the filenames). If needed, you can go to the CodeDeploy console and redeploy an older revision to the deployment group. Alternatively, you could push a Git revert commit and let the pipeline deploy that as a “roll forward” that effectively restores the old code.

Blue/Green Deployments: A proactive strategy is to use Blue/Green (also known as red/black) deployments. CodeDeploy supports blue/green mode, where it launches a new set of instances (or containers) with the new version (green) while keeping the old version (blue) running. You can test the new version, then switch traffic over. If issues are detected, you can quickly roll back traffic to the old instances. This minimizes downtime and risk. For example, if deploying a Java app on EC2 behind a load balancer, CodeDeploy can provision new instances (or use an autoscaling group swap) and switch the load balancer to them. If something’s wrong, you switch back within minutes. Blue/Green does require more automation and sometimes extra infrastructure, but it greatly eases rollback pain.

Database Changes: Rollbacks aren’t just about code; consider your database migrations. If your deployment included a schema change, rolling back might be non-trivial. Use feature flags or backward-compatible DB changes when possible so that the previous app version can still run. If not, have database rollback scripts or backups ready.

Testing After Deploy & Canary: To catch issues early, implement post-deployment smoke tests or health checks. AWS CodeDeploy can be hooked with CloudWatch Alarms (for instance, if the new version triggers high error rates, an alarm can fail the deployment, prompting auto-rollback). You can also do canary releases – deploy to a small subset of servers first, validate, then proceed. While not strictly “rollback”, these strategies reduce the chance of needing one by limiting bad deployments.

In summary, plan your rollback strategy in advance. Use CodeDeploy’s automatic rollback for failures, maintain the ability to redeploy old versions, and consider advanced deployment patterns (blue/green, canaries) for safety.

Conclusion

Building a CI/CD pipeline with Jenkins and AWS CodePipeline brings together the best of both worlds: Jenkins provides a powerful, customizable build/test environment, and AWS CodePipeline adds scalable, managed orchestration and deployment capabilities. We’ve walked through setting up Jenkins on AWS, integrating it as a build stage in CodePipeline, and deploying a Java application with AWS CodeDeploy. Along the way, we highlighted how to secure the pipeline and handle failures gracefully. With this setup, each commit to your Java app’s repo can go through a fully automated workflow – compiling code, running tests, and deploying to production in a repeatable, efficient manner. This not only speeds up delivery but also improves reliability by catching issues early and enabling quick rollbacks.

By following the steps and best practices above, you can implement a robust CI/CD pipeline that accelerates your development process while keeping risks in check.

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