COGNITIVE SOFTWARE ENGINEERING: INTEGRATION OF AI, DEVOPS, AND CLOUD-NATIVE ARCHITECTURES

Abstract

Cognitive Software Engineering is an emerging approach that combines advanced technologies, such as Artificial Intelligence (AI), Cognitive DevOps, and cloud-native architectures, to transform the software development lifecycle. This approach goes beyond traditional automation, introducing intelligence and continuous learning at every step, from code generation to maintenance. AI-powered tools such as GitHub Copilot and Dynatrace exemplify the use of advanced algorithms to increase productivity, predict failures, and improve the user experience. In addition, Cognitive DevOps enables intelligent monitoring and proactive problem solving, while cloud-native architectures promote dynamic scalability and resiliency. Despite the benefits, Cognitive Software Engineering presents challenges, such as the need to deal with ethical issues, data privacy, and implementation costs. Still, it represents a significant advancement in the way software systems are designed and managed, making it an ideal choice for organizations seeking continuous innovation in a competitive digital landscape. This study explores the pillars of this approach, highlighting its practical applications, benefits, and limitations.