containerization

This article presents the main findings from an in-depth study of MLFlow design concepts in containerized and cloud-native systems. The research focuses on how MLFlow, as a core MLOps framework, can be efficiently deployed and managed in cloud- native environments to ensure scalable, reproducible, and secure machine learning workflows. The study analyzes the architectural principles and integration patterns of MLFlow components: Tracking Server, Projects, Models, and Registry within distributed containerized infrastructures.

The article examines the security of microservice architectures in the context of common vulnerabilities that arise in distributed systems. The authors analyze the essence of the microservice approach, which, despite its advantages in scalability and flexibility, introduces new challenges in the field of cybersecurity. The main focus is on issues of access management, network configuration, and data protection during transmission between services, which can create additional attack vectors.

Summary. The article proposes a methodology for evaluating the dependability of web portals at various stages of their life cycle through the integration of Immutable Infrastructure and containerization technologies. As web systems grow in complexity and functional load, and as the demand for high availability and fault tolerance increases, traditional reliability as- sessment approaches based on defect density, error frequency, and test coverage become insufficient.