Advanced Software Technology Paradigms and AI Deployment

Up-to-date software technology paradigms consider widely modern market demands, used application types as well as appropriate frameworks and platforms. A state-of-the-art overview of the used paradigms and approaches is provided as well as the challenges for IT experts are formulated. The paper is devoted to the advanced software technology (SWT) paradigms with the support of modern building blocks as well as LLMs (Large Language Model) and AI (Artificial Intelligence) deployment. The contribution addresses the ongoing challenges to modern software and provides quality and experience optimization for the development process. Between the advanced paradigms, DevOps is considered, and the pros and cons of the approach are discussed. As case studies an efficient combination of DevOps and CVS (Concurrent Versioning System) is discussed, titled GitOps, promising rapid AI deployment purposed to automate project stages as well as quality optimization. As an advanced process model, the above-mentioned GitOps approach provides multiple pros for the acceleration of secure and error-free code development, increased reuse of the source fragments, and cost reduction. The further advantages are formulated and proven as follows: (1) Single Source of Truth: easier to identify the causes of errors and to restore the infrastructure at any time; (2) Automation and Recovery: the entire deployment pipeline is automated; (3) Security: because changes to the infrastructure are controlled via pull requests and peer reviews, potential security risks and errors are reduced; (4) Portability: the entire infrastructure is defined as code what allows easy portability between different cloud platforms; (5) Multiple Stages: providing different stages for development and “hot fixes” in emergency.