Strategies for Scaling Backend Architectures under High Transactional Load in Cloud Ecosystems
Keywords:
backend architecture scaling, cloud computing, high transactional load, autoscaling, multi-tenant systems, transaction processing, data ingestion pipelinesAbstract
The article examines contemporary approaches to scaling backend architectures under conditions of high transactional load in cloud ecosystems. Particular attention is given to the challenges arising in multi-tenant environments, where large volumes of business transactions are simultaneously processed through distributed services, integration layers, and data processing systems. A comprehensive analysis of studies on autoscaling, computational resource management, microservice architectures, container orchestration, serverless computing, and high-throughput data ingestion pipelines was conducted. The findings indicate that mechanisms for early data validation, workload prediction, integration event management, and coordination of service interactions are becoming increasingly important. Based on the analysis, the author developed the Transaction-Aware Adaptive Backend Scaling Model. The proposed model expands current perspectives on the scaling of distributed backend platforms and can be applied in the design of high-load cloud systems, transactional services, and enterprise-level integration solutions. The article may be of interest to software developers, cloud platform architects, distributed systems specialists, and researchers in the field of cloud computing.
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