Management of distributed data processing systems: main problems and modern challenges

In the modern information society, the requirements for fast processing, convenient storage and transmission of information are increasing. Dynamic ways of accessing data, searching for information at certain time intervals, and performing complex operations with data are needed. The transition from centralized data processing to distributed systems is due to the rapid development of technology, an increase in data volumes, and the requirement for high availability and speed of information processing. The purpose of the article is to discuss the main problems and challenges faced by modern distributed data processing systems. Research methods. The analysis is based on domestic and foreign scientific publications devoted to the problems of distributed data processing systems. The theoretical framework was built using methodological principles, including general scientific methods of analysis and synthesis, methods of deductive and inductive reasoning, as well as comparative and generalizing approaches. Such tools made it possible to identify the key patterns of functioning of the studied systems and determine the directions of their improvement. Results. The application of the chosen method made it possible to identify a set of aspects that require priority attention in the design and operation of distributed systems. The growing volume of data combined with the dynamic development of digital technologies significantly complicates the management processes of such structures. To achieve stable operation, it is necessary to constantly modernize administrative tools, improve information security methods and increase the efficiency of computing nodes. The key conditions for the successful development of distributed systems are flexibility of architecture, adaptability to a changing information environment and rational use of resources. In the context of accelerating digitalization, it is precisely integrated management strategies that make it possible to ensure the optimal combination of productivity, reliability and security, which creates the prerequisites for their sustainable functioning in the long term. Conclusions. Studying the problems of modern distributed data processing systems allows us to draw the following conclusions: it is necessary to ensure the security of data and network infrastructure through effective protection measures; the problem of scalability becomes relevant with increasing amounts of data and system load; strategies and technologies should be developed for effective system scaling, resource optimization, load balancing, and energy management; 4) algorithms, system architecture, and advanced technologies should be continuously improved to improve performance; 5) and an important challenge is to ensure system continuous operation and resiliency for automatic recovery from failures and failures, as well as data availability.