Full Article: PDF
Scientific Object Identifier: http://s-o-i.org/1.1/TAS-08-148-24
DOI: https://dx.doi.org/10.15863/TAS.2025.08.148.24
Language: English
Citation: Bogutskii, A. (2025). Enhancing the resilience of stream processing platforms: engineering approaches to scalability and fault tolerance. ISJ Theoretical & Applied Science, 08 (148), 170-175. Soi: https://s-o-i.org/1.1/TAS-08-148-24 Doi: https://dx.doi.org/10.15863/TAS.2025.08.148.24 |
Pages: 170-175
Published: 30.08.2025
Abstract: This article examines engineering approaches to improving the resilience of stream processing platforms that handle real-time event data. It analyzes architectural solutions designed to achieve scalability and fault tolerance under high load and unpredictable failure conditions. The importance of mechanisms such as replication, state management, automated recovery, and the selection of appropriate message delivery semantics is emphasized. Special attention is given to the use of containerization, orchestration (Kubernetes), and cloud-based streaming services. Case studies from Netflix, Uber, and LinkedIn are presented to illustrate the practical applicability of the described methods. The article highlights the necessity of a comprehensive engineering approach to designing robust stream processing systems within modern digital infrastructure.
Key words: stream processing platforms, scalability, fault tolerance, Kafka, Flink, Kubernetes, data processing.
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