SCALABLE MICROSERVICES FOR REAL-TIME BIG DATA PROCESSING IN THE CLOUD

The use of scalable microservices for real-time large data processing in cloud systems is examined in this article. It looks at how modern businesses can handle large data volumes with little delay by using microservices architecture. The article illustrates how microservices outperform conventional batch processing techniques in stream processing scenarios by analyzing a number of components, such as data input, message broker integration, and processing layers. In order to facilitate effective data processing at scale, it also looks into resource management techniques, auto-scaling systems, and cloud integration capabilities. The article also provides a thorough framework for enterprises looking to use microservices for their large data processing requirements by outlining best practices for microservices implementation, including important topics like failure handling, monitoring, and data flow optimization.