DevSecOps, Machine Learning and Beyond: How IT Security is Changing

Immutable infrastructure. Technologies like Docker containers enable immutable infrastructure. By design, immutable infrastructure cannot be modified once it is running unless you wipe it out and create an entirely new version. From a security perspective, immutable infrastructure is an advantage because it makes it easier to detect anomalies that could signal a threat. When there is no legitimate reason for a running application to be patched or modified, changes stand out more clearly.

The DevSecOps (or Rugged Ops) concept. This is an extension of the DevOps philosophy. DevSecOps emphasizes the importance of integrating the security team into all parts of software development and deployment, rather than leaving them disconnected. When security experts are involved in designing, testing and managing code, they stand a better chance of helping an organization to discover and fix vulnerabilities before software goes into production.

Machine learning. Relying on humans to detect and interpret security problems is error-prone and doesn't scale. For that reason, today's generation of security tools leverage machine learning to detect and respond to anomalies automatically.

Automated security policy configuration. If you want to create large software environments, you can't configure security policies for them manually. You need to rely on automated tools that use machine learning to generate and update security policies automatically, in real time.