Scalable Fault-Tolerant Systems in Cloud Stor...

Scalable Fault-Tolerant Systems in Cloud Storage: Case Study of Amazon S3 and Dynamo DB

Author Name : Vignesh Natarajan, Prof. (Dr) Punit Goel

ABSTRACT Scalable fault-tolerant systems are an essential requirement for cloud storage solutions to achieve high availability and reliability in the presence of hardware failures, network outages, and unforeseen disruptions. This paper provides a design and implementation overview of scalable, fault-tolerant systems with an emphasis on Amazon S3 (Simple Storage Service) and DynamoDB, two popular cloud services. Amazon S3 is an object storage service that provides redundancy across multiple geographically distributed data centers, while DynamoDB is a managed NoSQL database service that supports large-scale, low-latency workloads with automatic scaling. The case study investigates how these systems realize fault tolerance through data replication, partitioning, and consistency models to meet common challenges in cloud storage related to data durability, availability, and latency. Amazon S3 achieves fault tolerance by replicating data across multiple availability zones,