CI/CD Docker: How to Build, Push, and Deploy Containers

What Is a CI/CD Pipeline?

CI/CD Docker stands for Continuous Integration and Continuous Delivery or Deployment of an app or environment. The primary purpose of CI/CD pipelines is to help developers automate tasks involved in building, testing, and deploying containerized applications. This vastly reduces the number of Docker commands that have to be manually executed during deployment.

See Also: What is Docker Container: Architecture, Uses, and Benefits

The process begins with changes pushed into a Git repository. A Git reference, like the main branch, will trigger a project defined in the YAML file. The workflow runs on a hosted machine and executes a series of jobs. These jobs build a new image, run tests, perform integration testing, and push Docker images to a Docker registry. This way, a new version can be easily deployed automatically to a production server.

The server simply pulls the new image and deploys a new container using environment variables and other configuration resources for the project.

A deployment workflow often records logs and reports errors, giving developers information about failed tasks without requiring them to execute each step manually.

A Docker CI/CD workflow typically follows these steps:

• Developers push code changes to the repository.
• The CI/CD workflow starts from the main branch.
• The pipeline builds a new image and assigns tags.
• A series of integration tests validate the application.
• The pipeline pushes images to the Docker registry.
• The production server pulls the new Docker image.
• The deployment starts a new container on the server.
• All of the logs and app health are checked for errors.
• The previous version remains available on the server.

Note: In many cases, vulnerability scanning tools are integrated into CI/CD pipelines to detect any issues.

Continuous Integration

Continuous Integration involves frequent merging of code changes into a shared repository. The priority here is for each change to be tracked and monitored automatically through several tests and validation steps before it can become a part of the codebase.

When it comes to Docker projects, CI mostly uses GitHub Actions or Jenkins to automate all of these checks. For example, if a project uses Ubuntu’s latest version as its main runner, it will execute scripts using the following steps and execution order:

• It will check out the latest code from the repository.
• Then it will install the required app dependencies.
• Next, it will build the Docker image and run the tests.
• Then, the validation, including Docker Compose files.
• Finally, it will report the test results and build errors.

This approach gives development teams faster feedback and helps catch problems early. It also creates a consistent process for checking code, rather than relying on developers to perform all steps manually.

See Also: Docker Tutorials for Beginners

Continuous Delivery vs. Continuous Deployment

(CD) or Continuous Delivery automatically prepares code for release after passing tests. The resulting build remains ready for deployment, but a developer or operations team typically approves the release before it reaches production. It’s something teams prefer to do manually.

Continuous Deployment takes the process one step further by automatically releasing every change that passes the required tests and checks. This means a successful pipeline moves the latest version directly into the target environment without requiring manual approval.

Here is how continuous delivery and continuous deployment differ:

Note: In CI/CD environments, container orchestration manages deployment and scaling of containers and helps with the application of new container versions.

How CI/CD Works With Docker

The way CI/CD works with Docker is by linking code changes into a fully automated process for building, testing, and deploying containerized applications. This means that, instead of manually creating images and connecting to the server for every change or release, the automated process handles everything by using predefined workflow steps and phases.

It’s simple: the change is pushed to a Git repository, from where the pipeline builds an image from the updated code and runs automated tests. If all goes well, the image is pushed to a target Docker registry.

The exact workflow depends on the project’s requirements, but most Docker CI/CD pipelines follow the same core stages. Let’s go through an example:

• Code Commit: A developer pushes new code changes to the Git repository, triggering the CI/CD workflow.
• Image Building: The pipeline builds a Docker image containing the updated application code and required dependencies.
• Image Testing: Automated unit, integration, and application tests run against the new build to identify potential issues.
• Build Pushing: After the tests pass, the pipeline tags the Docker image and pushes it to a container registry.
• Deployment: The Docker host pulls the new image and replaces the existing container with the updated version.
• Full Verification: Health checks, application responses, and deployment logs confirm whether the new container is running correctly.
• Potential Rollback: If the deployment fails or the application behaves unexpectedly, the previous working image is restored.

A well-designed Docker CI/CD gives users a consistent process for moving changes from development to production. As you learn how these stages work, you gain the knowledge needed to understand how images, metadata, and tags move through the pipeline.

Using true tags, such as a specific application version or Git commit, also makes it easier to identify the exact image deployed to a server. This approach gives teams a clear history of releases and helps them trace problems back to a specific version.

See Also: Docker Vs Kubernetes: Which Container Platform Is Right for Your Infrastructure?

Building Docker Images Unwrapped

Docker packages applications into containers that include code and all dependencies. To achieve this, a Docker Image needs to be created in the first place. In a CI/CD environment, the images are generated as code changes reach the repository automatically.

Let’s take a look at the process in a step-by-step manner:

#1: Creating the Dockerfile

Docker enables consistent builds by using Dockerfiles to create application images. Then, the Dockerfile defines exactly how the application image is built. It specifies the base image, dependencies, application files, configuration, and startup command. So, when the CI/CD project starts a build, Docker reads these instructions and creates the image automatically.

See Also: Docker Security for Small Teams

#2: Building a Docker Image

The pipeline uses the Dockerfile to build a new image whenever a configured code change triggers the workflow. The build process combines the application code and its dependencies into a portable image.

Images should be tagged with unique identifiers to ensure traceability in production. A CI/CD pipeline typically assigns each image a version, Git commit SHA, or other unique identifier.

This allows the deployment process to determine exactly which Docker image belongs to each release.

Note: Best practices suggest never embedding secrets directly into Docker images.

#3: Tagging Docker Images

The image tagging gives each build a reference that the CI/CD pipeline uses throughout the remaining stages. Version tags and Git commit identifiers make it easier to connect a running container with the source code used to build it. The pipeline then pushes the tagged image to a Docker registry, where the deployment stage retrieves it when updating the Docker host.

#4: Testing Docker Images

Lastly, befre and image can reach the production stage, the automated CI/CD process runs automated tests across the environment. The purpose of these tests is to ensure that the application configuration and container setup are valid without a developer’s manual intervention.

If a test fails, the pipeline stops and prevents the image from moving to the deployment stage. That’s why automated container image scanning should be performed before pushing the images to the registry.

Note: Docker’s layer caching feature can significantly speed up build processes in CI/CD.

Pushing Images to a Container Registry

After the Docker image passes the required tests, the CI/CD workflow pushes it to a container registry. The registry stores Docker images and makes them available to the deployment stage, where the Docker host pulls the image required for the release.

Docker images can be pushed to AWS ECR or Docker Hub.

The same workflow applies to other container registries, including private registries used by businesses to keep production images under their control.

Note: Using multi-stage builds can minimize the security attack surface of final images. Also, relying on mutable tags like ‘latest’ can create unpredictable deployments.

CI/CD Last Stage: Deploying Docker Containers

Docker images can be deployed on remote servers automatically. Once an image passes the required tests, the CI/CD pipeline connects to the Docker host, pulls the specified image, and starts the updated container. The deployment process replaces the previous application version with the new image while applying the required environment variables and configuration.

Note: Automated health checks should be performed after deployment to verify functionality.

Setting Up GitHub Actions for Docker Deployment

GitHub Actions connects the source code repository with the Docker build and deployment process. A workflow defines what happens when code changes are pushed, which environment runs the jobs, and which actions execute each stage.

The following features form the core of a GitHub Actions workflow for Docker deployments:

Note: Containers eliminate discrepancies between environments by ensuring identical runtime setups.

Creating the Workflow:

Here’s an example showing the core structure of a Docker deployment workflow:

name: Docker Deploy
on:
  push:
    branches: [main]
jobs:
  build:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: docker/login-action@v3
        with:
          username: ${{ secrets.DOCKERHUB_USERNAME }}
          password: ${{ secrets.DOCKERHUB_TOKEN }}
      - uses: docker/build-push-action@v6
        with:
          context: .
          push: true
          tags: username/myapp:${{ github.sha }}

This example demonstrates the core build and push process without adding deployment code yet. The main branch triggers the workflow, ubuntu-latest provides the runner, and GitHub Actions uses the repository’s Git context to build the Docker image.

The registry credentials come from GitHub Secrets rather than being stored directly in the YAML file. The ${{ github.sha }} value offers the image with a unique tag based on the commit responsible for the build.

CI/CD Docker Pipeline Made Simple with ServerMania

ServerMania provides world-class Dedicated Servers, cloud platform AraCloud, and tailored Application Hosting Solutions to simplify continuous integration and deployment workloads.

ServerMania infrastructure also supports container orchestration beyond raw Docker deployments. You can run applications across Server Clusters for distributed projects or use a fully managed Kubernetes-ready infrastructure for deployments that require automated scheduling, scaling, and high availability.

💬To learn more, we encourage you to contact our 24/7 customer support to book a consultation for free to discuss your project with an expert. We’re available right now!