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Protecting the Software Supply Chain: The Art of Continuous Improvement

Without continuous improvement in software security, you’re not standing still — you’re walking backward into oncoming traffic. Attack vectors multiply, evolve, and look for the weakest link in your software supply chain daily. 

Cybersecurity Ventures forecasts that the global cost of software supply chain attacks will reach nearly $138 billion by 2031, up from $60 billion in 2025 and $46 billion in 2023. A single overlooked vulnerability isn’t just a flaw; it’s an open invitation for compromise, potentially threatening your entire system. The cost of a breach doesn’t stop with your software — it extends to your reputation and customer trust, which are far harder to rebuild. 

Docker’s suite of products offers your team peace of mind. With tools like Docker Scout, you can expose vulnerabilities before they expose you. Continuous image analysis doesn’t just find the cracks; it empowers your teams to seal them from code to production. But Docker Scout is just the beginning. Tools like Docker Hub’s trusted content, Docker Official Images (DOI), Image Access Management (IAM), and Hardened Docker Desktop work together to secure every stage of your software supply chain. 

In this post, we’ll explore how these tools provide built-in security, governance, and visibility, helping your team innovate faster while staying protected. 

Securing the supply chain

Your software supply chain isn’t just an automated sequence of tools and processes. It’s a promise — to your customers, team, and future. Promises are fragile. The cracks can start to show with every dependency, third-party integration, and production push. Tools like Image Access Management help protect your supply chain by providing granular control over who can pull, share, or modify images, ensuring only trusted team members access sensitive assets. Meanwhile, Hardened Docker Desktop ensures developers work in a secure, tamper-proof environment, giving your team confidence that development is aligned with enterprise security standards. The solution isn’t to slow down or second-guess; it’s to continuously improve on securing your software supply chain, such as automated vulnerability scans and trusted content from Docker Hub.

A breach is more than a line item in the budget. Customers ask themselves, “If they couldn’t protect this, what else can’t they protect?” Downtime halts innovation as fines for compliance failures and engineering efforts re-route to forensic security analysis. The brand you spent years perfecting could be reduced to a cautionary tale. Regardless of how innovative your product is, it’s not trusted if it’s not secure. 

Organizations must stay prepared by regularly updating their security measures and embracing new technologies to outpace evolving threats. As highlighted in the article Rising Tide of Software Supply Chain Attacks: An Urgent Problem, software supply chain attacks are increasingly targeting critical points in development workflows, such as third-party dependencies and build environments. High-profile incidents like the SolarWinds attack have demonstrated how adversaries exploit trust relationships and weaknesses in widely used components to cause widespread damage. 

Preventing security problems from the start

Preventing attacks like the SolarWinds breach requires prioritizing code integrity and adopting secure software development practices. Tools like Docker Scout seamlessly integrate security into developers’ workflows, enabling proactive identification of vulnerabilities in dependencies and ensuring that trusted components form the backbone of your applications.

Docker Hub’s trusted content and Docker Scout’s policy evaluation features help ensure that your organization uses compliant and secure images. Docker Official Images (DOI) provide a robust foundation for deployments, mitigating risks from untrusted components. To extend this security foundation, Image Access Management allows teams to enforce image-sharing policies and restrict access to sensitive components, preventing accidental exposure or misuse. For local development, Hardened Docker Desktop ensures that developers operate in a secure, enterprise-grade environment, minimizing risks from the outset. This combination of tools enables your engineering team to put out fires and, more importantly, prevent them from starting in the first place.

Building guardrails

Governance isn’t a roadblock; it’s the blueprint for progress. The problem is that some companies treat security like a fire extinguisher — something you grab when things go wrong. That is not a viable strategy in the long run. Real innovation happens when security guardrails are so well-designed that they feel like open highways, empowering teams to move fast without compromising safety. 

A structured policy lifecycle loop — mapping connections, planning changes, deploying cleanly, and retiring the dead weight — turns governance into your competitive edge. Automate it, and you’re not just checking boxes; you’re giving your teams the freedom to move fast and trust the road ahead. 

Continuous improvement on security policy management doesn’t have to feel like a bureaucratic chokehold. Docker provides a streamlined workflow to secure your software supply chain effectively. Docker Scout integrates seamlessly into your development lifecycle, delivering vulnerability scans, image analysis, and detailed reports and recommendations to help teams address issues before code reaches production. 

With the introduction of Docker Health Scores — a security grading system for container images — teams gain a clear and actionable snapshot of their image security posture. These scores empower developers to prioritize remediation efforts and continuously improve their software’s security from code to production.

Keeping up with continuous improvement

Security threats aren’t slowing down. New attack vectors and vulnerabilities grow every day. With cybercrime costs expected to rise from $9.22 trillion in 2024 to $13.82 trillion by 2028, organizations face a critical choice: adapt to this evolving threat landscape or risk falling behind, exposing themselves to escalating costs and reputational damage. Continuous improvement in software security isn’t a luxury. Building and maintaining trust with your customers is essential so they know that every fresh deployment is better than the one that came before. Otherwise, expect high costs due to imminent software supply chain attacks. 

Best practices for securing the software supply chain involve integrating vulnerability scans early in the development lifecycle, leveraging verified content from trusted sources, and implementing governance policies to ensure consistent compliance standards without manual intervention. Continuous monitoring of vulnerabilities and enforcing runtime policies help maintain security at scale, adapting to the dynamic nature of modern software ecosystems.

Start today

Securing your software supply chain is a journey of continuous improvement. With Docker’s tools, you can empower your teams to build and deploy software securely, ensuring vulnerabilities are addressed before they become liabilities.

Don’t wait until vulnerabilities turn into liabilities. Explore Docker Hub, Docker Scout, Hardened Docker Desktop, and Image Access Management to embed security into every stage of development. From granular control over image access to tamper-proof local environments, Docker’s suite of tools helps safeguard your innovation, protect your reputation, and empower your organization to thrive in a dynamic ecosystem.

Learn more

Docker Scout: Integrates seamlessly into your development lifecycle, delivering vulnerability scans, image analysis, and actionable recommendations to address issues before they reach production.

Docker Health Scores: A security grading system for container images, offering teams clear insights into their image security posture.

Docker Hub: Access trusted, verified content, including Docker Official Images (DOI), to build secure and compliant software applications.

Docker Official Images (DOI): A curated set of high-quality images that provide a secure foundation for your containerized applications.

Image Access Management (IAM): Enforce image-sharing policies and restrict access to sensitive components, ensuring only trusted team members access critical assets.

Hardened Docker Desktop: A tamper-proof, enterprise-grade development environment that aligns with security standards to minimize risks from local development.

Quelle: https://blog.docker.com/feed/

Mastering Docker and Jenkins: Build Robust CI/CD Pipelines Efficiently

Hey there, fellow engineers and tech enthusiasts! I’m excited to share one of my favorite strategies for modern software delivery: combining Docker and Jenkins to power up your CI/CD pipelines. 

Throughout my career as a Senior DevOps Engineer and Docker Captain, I’ve found that these two tools can drastically streamline releases, reduce environment-related headaches, and give teams the confidence they need to ship faster.

In this post, I’ll walk you through what Docker and Jenkins are, why they pair perfectly, and how you can build and maintain efficient pipelines. My goal is to help you feel right at home when automating your workflows. Let’s dive in.

Brief overview of continuous integration and continuous delivery

Continuous integration (CI) and continuous delivery (CD) are key pillars of modern development. If you’re new to these concepts, here’s a quick rundown:

Continuous integration (CI): Developers frequently commit their code to a shared repository, triggering automated builds and tests. This practice prevents conflicts and ensures defects are caught early.

Continuous delivery (CD): With CI in place, organizations can then confidently automate releases. That means shorter release cycles, fewer surprises, and the ability to roll back changes quickly if needed.

Leveraging CI/CD can dramatically improve your team’s velocity and quality. Once you experience the benefits of dependable, streamlined pipelines, there’s no going back.

Why combine Docker and Jenkins for CI/CD?

Docker allows you to containerize your applications, creating consistent environments across development, testing, and production. Jenkins, on the other hand, helps you automate tasks such as building, testing, and deploying your code. I like to think of Jenkins as the tireless “assembly line worker,” while Docker provides identical “containers” to ensure consistency throughout your project’s life cycle.

Here’s why blending these tools is so powerful:

Consistent environments: Docker containers guarantee uniformity from a developer’s laptop all the way to production. This consistency reduces errors and eliminates the dreaded “works on my machine” excuse.

Speedy deployments and rollbacks: Docker images are lightweight. You can ship or revert changes at the drop of a hat — perfect for short delivery process cycles where minimal downtime is crucial.

Scalability: Need to run 1,000 tests in parallel or support multiple teams working on microservices? No problem. Spin up multiple Docker containers whenever you need more build agents, and let Jenkins orchestrate everything with Jenkins pipelines.

For a DevOps junkie like me, this synergy between Jenkins and Docker is a dream come true.

Setting up your CI/CD pipeline with Docker and Jenkins

Before you roll up your sleeves, let’s cover the essentials you’ll need:

Docker Desktop (or a Docker server environment) installed and running. You can get Docker for various operating systems.

Jenkins downloaded from Docker Hub or installed on your machine. These days, you’ll want jenkins/jenkins:lts (the long-term support image) rather than the deprecated library/jenkins image.

Proper permissions for Docker commands and the ability to manage Docker images on your system.

A GitHub or similar code repository where you can store your Jenkins pipeline configuration (optional, but recommended).

Pro tip: If you’re planning a production setup, consider a container orchestration platform like Kubernetes. This approach simplifies scaling Jenkins, updating Jenkins, and managing additional Docker servers for heavier workloads.

Building a robust CI/CD pipeline with Docker and Jenkins

After prepping your environment, it’s time to create your first Jenkins-Docker pipeline. Below, I’ll walk you through common steps for a typical pipeline — feel free to modify them to fit your stack.

1. Install necessary Jenkins plugins

Jenkins offers countless plugins, so let’s start with a few that make configuring Jenkins with Docker easier:

Docker Pipeline Plugin

Docker

CloudBees Docker Build and Publish

How to install plugins:

Open Manage Jenkins > Manage Plugins in Jenkins.

Click the Available tab and search for the plugins listed above.

Install them (and restart Jenkins if needed).

Code example (plugin installation via CLI):

# Install plugins using Jenkins CLI
java -jar jenkins-cli.jar -s http://<jenkins-server>:8080/ install-plugin docker-pipeline
java -jar jenkins-cli.jar -s http://<jenkins-server>:8080/ install-plugin docker
java -jar jenkins-cli.jar -s http://<jenkins-server>:8080/ install-plugin docker-build-publish

Pro tip (advanced approach): If you’re aiming for a fully infrastructure-as-code setup, consider using Jenkins configuration as code (JCasC). With JCasC, you can declare all your Jenkins settings — including plugins, credentials, and pipeline definitions — in a YAML file. This means your entire Jenkins configuration is version-controlled and reproducible, making it effortless to spin up fresh Jenkins instances or apply consistent settings across multiple environments. It’s especially handy for large teams looking to manage Jenkins at scale.

Reference:

Jenkins Plugin Installation Guide.

Jenkins Configuration as Code Plugin.

2. Set up your Jenkins pipeline

In this step, you’ll define your pipeline. A Jenkins “pipeline” job uses a Jenkinsfile (stored in your code repository) to specify the steps, stages, and environment requirements.

Example Jenkinsfile:

pipeline {
agent any
stages {
stage('Checkout') {
steps {
git branch: 'main', url: 'https://github.com/your-org/your-repo.git'
}
}
stage('Build') {
steps {
script {
dockerImage = docker.build("your-org/your-app:${env.BUILD_NUMBER}")
}
}
}
stage('Test') {
steps {
sh 'docker run –rm your-org/your-app:${env.BUILD_NUMBER} ./run-tests.sh'
}
}
stage('Push') {
steps {
script {
docker.withRegistry('https://index.docker.io/v1/', 'dockerhub-credentials') {
dockerImage.push()
}
}
}
}
}
}

Let’s look at what’s happening here:

Checkout: Pulls your repository.

Build: Creates a built docker image (your-org/your-app) with the build number as a tag.

Test: Runs your test suite inside a fresh container, ensuring Docker containers create consistent environments for every test run.

Push: Pushes the image to your Docker registry (e.g., Docker Hub) if the tests pass.

Reference: Jenkins Pipeline Documentation.

3. Configure Jenkins for automated builds

Now that your pipeline is set up, you’ll want Jenkins to run it automatically:

Webhook triggers: Configure your source control (e.g., GitHub) to send a webhook whenever code is pushed. Jenkins will kick off a build immediately.

Poll SCM: Jenkins periodically checks your repo for new commits and starts a build if it detects changes.

Which trigger method should you choose?

Webhook triggers are ideal if you want near real-time builds. As soon as you push to your repo, Jenkins is notified, and a new build starts almost instantly. This approach is typically more efficient, as Jenkins doesn’t have to continuously check your repository for updates. However, it requires that your source control system and network environment support webhooks.

Poll SCM is useful if your environment can’t support incoming webhooks — for example, if you’re behind a corporate firewall or your repository isn’t configured for outbound hooks. In that case, Jenkins routinely checks for new commits on a schedule you define (e.g., every five minutes), which can add a small delay and extra overhead but may simplify setup in locked-down environments.

Personal experience: I love webhook triggers because they keep everything as close to real-time as possible. Polling works fine if webhooks aren’t feasible, but you’ll see a slight delay between code pushes and build starts. It can also generate extra network traffic if your polling interval is too frequent.

4. Build, test, and deploy with Docker containers

Here comes the fun part — automating the entire cycle from build to deploy:

Build Docker image: After pulling the code, Jenkins calls docker.build to create a new image.

Run tests: Automated or automated acceptance testing runs inside a container spun up from that image, ensuring consistency.

Push to registry: Assuming tests pass, Jenkins pushes the tagged image to your Docker registry — this could be Docker Hub or a private registry.

Deploy: Optionally, Jenkins can then deploy the image to a remote server or a container orchestrator (Kubernetes, etc.).

This streamlined approach ensures every step — build, test, deploy — lives in one cohesive pipeline, preventing those “where’d that step go?” mysteries.

5. Optimize and maintain your pipeline

Once your pipeline is up and running, here are a few maintenance tips and enhancements to keep everything running smoothly:

Clean up images: Routine cleanup of Docker images can reclaim space and reduce clutter.

Security updates: Stay on top of updates for Docker, Jenkins, and any plugins. Applying patches promptly helps protect your CI/CD environment from vulnerabilities.

Resource monitoring: Ensure Jenkins nodes have enough memory, CPU, and disk space for builds. Overworked nodes can slow down your pipeline and cause intermittent failures.

Pro tip: In large projects, consider separating your build agents from your Jenkins controller by running them in ephemeral Docker containers (also known as Jenkins agents). If an agent goes down or becomes stale, you can quickly spin up a fresh one — ensuring a clean, consistent environment for every build and reducing the load on your main Jenkins server.

Why use Declarative Pipelines for CI/CD?

Although Jenkins supports multiple pipeline syntaxes, Declarative Pipelines stand out for their clarity and resource-friendly design. Here’s why:

Simplified, opinionated syntax: Everything is wrapped in a single pipeline { … } block, which minimizes “scripting sprawl.” It’s perfect for teams who want a quick path to best practices without diving deeply into Groovy specifics.

Easier resource allocation: By specifying an agent at either the pipeline level or within each stage, you can offload heavyweight tasks (builds, tests) onto separate worker nodes or Docker containers. This approach helps prevent your main Jenkins controller from becoming overloaded.

Parallelization and matrix builds: If you need to run multiple test suites or support various OS/browser combinations, Declarative Pipelines make it straightforward to define parallel stages or set up a matrix build. This tactic is incredibly handy for microservices or large test suites requiring different environments in parallel.

Built-in “escape hatch”: Need advanced Groovy features? Just drop into a script block. This lets you access Scripted Pipeline capabilities for niche cases, while still enjoying Declarative’s streamlined structure most of the time.

Cleaner parameterization: Want to let users pick which tests to run or which Docker image to use? The parameters directive makes your pipeline more flexible. A single Jenkinsfile can handle multiple scenarios — like unit vs. integration testing — without duplicating stages.

Declarative Pipeline examples

Below are sample pipelines to illustrate how declarative syntax can simplify resource allocation and keep your Jenkins controller healthy.

Example 1: Basic Declarative Pipeline

pipeline {
agent any
stages {
stage('Build') {
steps {
echo 'Building…'
}
}
stage('Test') {
steps {
echo 'Testing…'
}
}
}
}

Runs on any available Jenkins agent (worker).

Uses two stages in a simple sequence.

Example 2: Stage-level agents for resource isolation

pipeline {
agent none // Avoid using a global agent at the pipeline level
stages {
stage('Build') {
agent { docker 'maven:3.9.3-eclipse-temurin-17' }
steps {
sh 'mvn clean package'
}
}
stage('Test') {
agent { docker 'openjdk:17-jdk' }
steps {
sh 'java -jar target/my-app-tests.jar'
}
}
}
}

Each stage runs in its own container, preventing any single node from being overwhelmed.

agent none at the top ensures no global agent is allocated unnecessarily.

Example 3: Parallelizing test stages

pipeline {
agent none
stages {
stage('Test') {
parallel {
stage('Unit Tests') {
agent { label 'linux-node' }
steps {
sh './run-unit-tests.sh'
}
}
stage('Integration Tests') {
agent { label 'linux-node' }
steps {
sh './run-integration-tests.sh'
}
}
}
}
}
}

Splits tests into two parallel stages.

Each stage can run on a different node or container, speeding up feedback loops.

Example 4: Parameterized pipeline

pipeline {
agent any

parameters {
choice(name: 'TEST_TYPE', choices: ['unit', 'integration', 'all'], description: 'Which test suite to run?')
}

stages {
stage('Build') {
steps {
echo 'Building…'
}
}
stage('Test') {
when {
expression { return params.TEST_TYPE == 'unit' || params.TEST_TYPE == 'all' }
}
steps {
echo 'Running unit tests…'
}
}
stage('Integration') {
when {
expression { return params.TEST_TYPE == 'integration' || params.TEST_TYPE == 'all' }
}
steps {
echo 'Running integration tests…'
}
}
}
}

Lets you choose which tests to run (unit, integration, or both).

Only executes relevant stages based on the chosen parameter, saving resources.

Example 5: Matrix builds

pipeline {
agent none

stages {
stage('Build and Test Matrix') {
matrix {
agent {
label "${PLATFORM}-docker"
}
axes {
axis {
name 'PLATFORM'
values 'linux', 'windows'
}
axis {
name 'BROWSER'
values 'chrome', 'firefox'
}
}
stages {
stage('Build') {
steps {
echo "Build on ${PLATFORM} with ${BROWSER}"
}
}
stage('Test') {
steps {
echo "Test on ${PLATFORM} with ${BROWSER}"
}
}
}
}
}
}
}

Defines a matrix of PLATFORM x BROWSER, running each combination in parallel.

Perfect for testing multiple OS/browser combinations without duplicating pipeline logic.

Additional resources:

Jenkins Pipeline Syntax: Official reference for sections, directives, and advanced features like matrix, parallel, and post conditions.

Jenkins Pipeline Steps Reference: Comprehensive list of steps you can call in your Jenkinsfile.

Jenkins Configuration as Code Plugin (JCasC): Ideal for version-controlling your Jenkins configuration, including plugin installations and credentials.

Using Declarative Pipelines helps ensure your CI/CD setup is easier to maintain, scalable, and secure. By properly configuring agents — whether Docker-based or label-based — you can spread workloads across multiple worker nodes, minimize resource contention, and keep your Jenkins controller humming along happily.

Best practices for CI/CD with Docker and Jenkins

Ready to supercharge your setup? Here are a few tried-and-true habits I’ve cultivated:

Leverage Docker’s layer caching: Optimize your Dockerfiles so stable (less frequently changing) layers appear early. This drastically reduces build times.

Run tests in parallel: Jenkins can run multiple containers for different services or microservices, letting you test them side by side. Declarative Pipelines make it easy to define parallel stages, each on its own agent.

Shift left on security: Integrate security checks early in the pipeline. Tools like Docker Scout let you scan images for vulnerabilities, while Jenkins plugins can enforce compliance policies. Don’t wait until production to discover issues.

Optimize resource allocation: Properly configure CPU and memory limits for Jenkins and Docker containers to avoid resource hogging. If you’re scaling Jenkins, distribute builds across multiple worker nodes or ephemeral agents for maximum efficiency.

Configuration management: Store Jenkins jobs, pipeline definitions, and plugin configurations in source control. Tools like Jenkins Configuration as Code simplify versioning and replicating your setup across multiple Docker servers.

With these strategies — plus a healthy dose of Declarative Pipelines — you’ll have a lean, high-octane CI/CD pipeline that’s easier to maintain and evolve.

Troubleshooting Docker and Jenkins Pipelines

Even the best systems hit a snag now and then. Here are a few hurdles I’ve seen (and conquered):

Handling environment variability: Keep Docker and Jenkins versions synced across different nodes. If multiple Jenkins nodes are in play, standardize Docker versions to avoid random build failures.

Troubleshooting build failures: Use docker logs -f <container-id> to see exactly what happened inside a container. Often, the logs reveal missing dependencies or misconfigured environment variables.

Networking challenges: If your containers need to talk to each other — especially across multiple hosts — make sure you configure Docker networks or an orchestration platform properly. Read Docker’s networking documentation for details, and check out the Jenkins diagnosing issues guide for more troubleshooting tips.

Conclusion

Pairing Docker and Jenkins offers a nimble, robust approach to CI/CD. Docker locks down consistent environments and lightning-fast rollouts, while Jenkins automates key tasks like building, testing, and pushing your changes to production. When these two are in harmony, you can expect shorter release cycles, fewer integration headaches, and more time to focus on developing awesome features.

A healthy pipeline also means your team can respond quickly to user feedback and confidently roll out updates — two crucial ingredients for any successful software project. And if you’re concerned about security, there are plenty of tools and best practices to keep your applications safe.

I hope this guide helps you build (and maintain) a high-octane CI/CD pipeline that your team will love. If you have questions or need a hand, feel free to reach out on the community forums, join the conversation on Slack, or open a ticket on GitHub issues. You’ll find plenty of fellow Docker and Jenkins enthusiasts who are happy to help.

Thanks for reading, and happy building!

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Quelle: https://blog.docker.com/feed/