Developing AI and ML-Based Real-Time Streaming Microservices for Distributed Systems

Faloye Oluwadamilohun Mary
Ladoke Akintola University of Technology

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Abstract

Microservices architecture has made it easier for spread-out systems to change and grow. You can process and analyze even more data-even faster-by adding AI and ML to microservices streaming data in real time. This paper discusses the design and development of intelligent microservices, with the main focus being how to combine AI/ML with microservices architecture. We discuss various pros and cons of the use of AI and ML in microservices, especially when it relates to fetching data from different locations in real time. Such integration could be very useful in real-life applications, such as online shopping, doctor visits, or money-related dealings. The recommendations for further research and development in this domain conclude the paper.

Keywords

Microservices Architecture, Artificial Intelligence (AI), Machine Learning (ML), Real-Time Streaming, Distributed Systems, Intelligent Microservices, Data Processing, Scalability, Flexibility, Automation.

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