How to Integrate Docker Scout with Microsoft Azure DevOps Pipeline

Azure DevOps Pipeline is a powerful and flexible continuous integration and continuous delivery (CI/CD) platform provided by Microsoft. It allows you to automate the building, testing, and deployment of your applications, making the software development life cycle more efficient and reliable. With Azure DevOps Pipeline, you can define, manage, and execute pipelines that deliver code changes from development to production in a consistent and repeatable manner.

What is Docker Scout?

Docker Scout is intended for anyone involved in the SDLC that focuses on maintaining or improving the security of their application. This includes developers, DevOps engineers, security professionals, and anyone else involved in the software development lifecycle. The feature is particularly useful for organizations that need to ensure the security and compliance of their container images and want to have a detailed understanding of the software supply chain. Docker Scout can be used by individuals or teams, and is available to users with a paid Docker subscription.

Docker Scout provides developers and organizations with detailed insights into the security of their container images, enabling them to make informed decisions about how to address vulnerabilities and improve the overall security of their software.

Integration of Docker Scout and Azure DevOps Pipeline

Azure DevOps Pipeline configuration is designed to work with a repository that is connected to Azure DevOps and contains the definition and contents of a Docker image. The main purpose of this pipeline is to automate the process of building the Docker image and generating a Common Vulnerabilities and Exposures (CVE) report using Docker Scout.

What this section covers:

• Repository Connection: The pipeline is triggered whenever there is a commit to the main branch of the repository. This indicates that there is new code or changes that need to be built into a Docker image.

• Build Docker Image: The pipeline’s first step is to build the Docker image based on the Dockerfile provided in the repository. It uses the Docker@2 task to perform this. The image is built with a specific tag that includes the Build ID, ensuring uniqueness and traceability.

• Install Docker Scout: Before analyzing the Docker image for CVEs, the pipeline fetches and installs the Docker Scout CLI. This is done using a curl command that downloads the necessary script and installs it on the pipeline agent.

• Docker Hub Authentication: To interact with Docker Hub and perform the CVE analysis, the pipeline logs in to Docker Hub using credentials stored as environment variables. This is essential for Docker Scout to access the necessary information about the image.

• CVE Analysis with Docker Scout: The pipeline then uses the Docker Scout CLI to perform a CVE analysis on the built Docker image. The command used is docker scout CVEs, and it specifies the image and tag to be analyzed. The –exit-code flag ensures that the pipeline will fail if any critical or high-severity CVEs are detected in the image.

By following this process, the pipeline automates the building of the Docker image and the CVE analysis using Docker Scout. This helps ensure that security vulnerabilities are identified and addressed early in the development process, contributing to the overall security and quality of the Docker images being produced.

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Ajeet Singh Raina is a developer advocate at Docker. He is a founder of Collabnix. He leads a Collabnix Slack community of 10K members. He is a Docker Community Leader and leads the Docker Bangalore community of 15K+ members. His community blogging site attracts millions of DevOps engineers every year and has more than 750+ blogs on Docker, Kubernetes and Cloud. Follow him on Twitter, Slack and Discord.