автоматизація

The article is devoted to the study of the automation of management processes of information and communication networks using network programming tools. The work substantiates the relevance of automation as a key direction in the development of modern information and communication systems, driven by the growth in traffic volumes and the complexity of network architecture. It is shown that automation allows for increasing operational efficiency, reducing task execution time, and minimizing the human factor.

This article discusses modern approaches to organizing continuous integration (CI) and continuous delivery (CD) processes in software development using artificial intelligence (AI) technologies. The historical development of CI/CD is analyzed, along with their role in ensuring high-quality software, the main advantages and disadvantages of traditional approaches, and the prospects for integrating AI technologies to automate and optimize these processes.

Modern logistics monitoring solutions increasingly depend on the integration of IoT devices for real-time data collection, shipment tracking, goods and vehicle monitoring, and informed decision- making. However, current IoT-based logistics systems face significant challenges, including complex data management, limited interoperability among stakeholders, and inefficiencies resulting from centralized control mechanisms.

The paper examines the explores the use of artificial intelligence (AI) methods and tools for the efficient construction, management, and optimization of cloud IT infrastructures. The main challenges related to the automation of deployment, scaling, monitoring, and resource optimization in the cloud environment are analyzed, along with the role of AI in addressing these issues. Approaches to integrating AI to improve productivity, reduce operational costs, and enhance the security of cloud platforms are discussed.

The article investigates the integration of information security into Agile software development processes, focusing on the adaptation of DevSecOps methods. The goal was to enhance the implementation of security practices by reducing vulnerability detection time, simplifying the integration of security into the development cycle, and improving team collaboration. The analysis revealed that automation of security testing reduces vulnerability detection time by 40%, while cross-functional teams improve collaboration by 30%.

In the current context of widespread adoption of cloud technologies such as AWS, GCP, and Azure, organizations face challenges in centralized management of cloud resources, including ensuring security standards, monitoring service metrics, optimizing costs, and managing configurations. The main issue lies in the differences in the architecture of services provided by various cloud vendors, which complicates the integration and standardization of processes in multi-cloud environments.

Nowadays, with the rapid development of modern technologies in software engineering, active digitalization, and the migration of many services online, ensuring the security of these services in terms of integrity, confidentiality, and availability of information has become more important than ever. The level of application security directly depends on investments made in security during software development.

The aim of this study is a comprehensive analysis of the fundamental SOAR (Security Orchestration, Automation, and Response) model in the context of cybersecurity for virtual networks. The paper presents a synthesis of the core concepts of orchestration, automation, and response, which are critical elements of modern approaches to risk management and information system protection.

The article explores the development and implementation of an automated system for constructing professionograms of artificial intelligence (AI) specialists using modern information technologies. Against the backdrop of an ever-evolving digital economy and rising demand for qualified AI professionals, the study highlights the need for accurate and scalable tools to identify and assess relevant competencies.