4 container security trends that matter to your CI/CD strategy

The DevSecOps-CI/CD pipeline world is on the cusp of a major shift, away from manual to intelligent tools for building secure containers. Developers are looking for ways to deliver a faster CI/CD pipeline, a shift-left-everywhere approach, a reduction in the number of tools they use, streamlined, repeatable operations, and controls that are built in from the start, without even having to set them up or architect them, and with easy, ongoing maintenance.

Whether they are tackling cloud architecture; designing a fast, scalable CI/CD pipeline; or moving to a DevSecOps model with a shift-left-everywhere approach, enterprises have one common challenge: relying on manual and reactive tools.  

"Vulnerability scanning" tools, if used before or after deployment, provide a point-in-time snapshot of vulnerabilities. In addition to vulnerability scanning, machine learning and operations, or "MLops" tools, are used to predict vulnerabilitiesUsing these manual, reactive tools results in a significant challenge known as the "continuous vulnerability remediation effort cycle" approach. That approach, which is exhausting to multiple teams, is not feasible to support an enterprise with changing business environment requirements, at a scalable level.

A new movement has begun to simplify the CI/CD pipeline, leveraging artificial intelligence to build containers in an automatic flexible, architecture that produces secure container environments within minutes.

Here are four trends that are playing out for container security as developers try to simplify the CI/CD pipeline.

1. Smart cloud container-building technologies are emerging  

There is greater adoption of smart cloud technologies that use and leverage intelligence to build containers. The intelligence will not only build the container, but can also apply security, compliance, and other relevant controls and maintain the state of the container.

Smart cloud container building is about building the application stack environment—the operating system, the databases, the dependencies, and all security, compliance and other controls. This is deployed in a matter of minutes, with a single click that delivers continuous, easy, ongoing maintenance. The human element is removed. It is the intelligence, rather than the developer, that architects and builds the container.

2. CI/CD pipelines simplified

Smart cloud container-building tools are simplifying the CI/CD pipeline for DevSecOps because organizations will no longer need to leverage a collection of manual tools to build and secure containers. The smart technology will help enable a pipeline that is fast, reliable, consistent, and secure and help organizations get to the cloud quickly, freeing up developers to focus on high-priority development activities. The days when developers had to set up and maintain containers manually are over.

The CI/CD pipeline is being simplified to the following steps:

• Application testing
• Smart building
• Validation scanning
• Deployment

3. Vulnerability scanning used more for security validation—less for shifting left

Vulnerability scanning tools won't go away but will evolve to a validation step. Instead using them to try to enable a shift-left-everywhere effort, you'll use them more for container security validation purposes and to satisfying best practice/regulations scanning requirements. Initially, many organizations used them to do vulnerability scanning after the fact when the container was already deployed into the environment.

The next trend was vulnerability scanning tools being used prior to deployment or runtime development, so you knew what needed to be fixed before your containers were deployed.

When you use smart technology to build your containers, you're depending on intelligence to have whittled down most vulnerabilities before you even deploy the containers. Increasingly, vulnerability scanning is about validating the security of containers that were built and deployed using smart cloud container-building technology.

4. MLOps will help identify and predict post-deployment

Machine-learning operations (MLOps) is used in organizations that have fully deployed containers to predict future controls and operations. From a security context, MLOps can help identify and predict potential security vulnerabilities or operational controls. With the usage of smart cloud container-building, attack surfaces will decrease significantly and feed to MLOps, creating more focused MLOps predictions.

The shift to intelligence for containers is on

If you find yourself looking through endless documentation on how to set up a DevOps tool, offering runtime security discovering YAMLs, or agent-based tools identifying vulnerabilities to remediate, this is a good indication you are going down a reactive tool approach.

By simplifying the CI/CD pipeline and leveraging intelligence, you don't have to use all these different reactive, manual tools to set up, design, architect, and secure your container environment. Why try to build a kit car, using manual tools, when you can buy the Formula One car ready to go so you can win the race?