Paper Title

Designing Distributed Systems for On-Demand Scoring and Prediction Services

Keywords

Distributed Systems
On-Demand Scoring
Prediction Services
Real-Time Analytics
Microservices
Scalability
Fault Tolerance
Dynamic Load Balancing
Machine Learning
Model Management
Caching
Hybrid Architecture
Data Pipelines
AI-Driven Optimization
Real-Time Decision-Making

Article Type

Research Article

Journal

International Journal of Current Science

Publication Info

Volume: 13 | Issue: 4 | Pages: 514-543

Published On

December, 2023

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Abstract

The research focuses on the key design principles required for implementing a distributed system that efficiently handles high-throughput prediction requests while ensuring minimal latency and high availability. The proposed architecture utilizes a modular microservices framework to enable independent scaling, seamless deployment, and dynamic load management. Each microservice is responsible for a specific function, such as data ingestion, feature transformation, model serving, and request routing, allowing for high cohesion and low coupling in the system design. This approach enables teams to independently update and maintain individual components without disrupting the overall service.