Self-learning CI/CD design practices
The concept of self-learning in CI/CD refers to the ability of systems to adapt and improve their deployment patterns based on feedback and data-driven insights. This involves the use of machine learning algorithms to analyze past deployments, identify patterns, and predict outcomes to enhance the CI/CD pipeline’s efficiency.
Design patterns in CI/CD provide, as mentioned several times in this book, a structured approach to solving common problems encountered during software delivery.
Anti-patterns, on the other hand, are common responses to recurring problems that are ineffective and counterproductive. Recognizing these anti-patterns is crucial as they can lead to inefficiencies and increased risk in the software delivery process. For example, the Manual Intervention anti-pattern, where manual steps are required in the deployment process, can lead to errors and delays.
Self-learning CI/CD systems aim to minimize these anti-patterns...
