Behind AWS S3's Scale

AWS S3, launched in 2006, has evolved into a highly scalable multi-tenant storage service, supporting 100 million requests per second and storing 280 trillion objects across 31 regions. Initially designed for backups and media storage, it now serves as a backbone for analytics and machine learning. S3's architecture comprises over 300 microservices, organized into four main components: a front-end REST API, a namespace service, a storage fleet, and a management fleet. The storage system utilizes millions of hard drives, employing a new backend called ShardStore, which optimizes data storage and retrieval. S3 employs Erasure Coding for data redundancy, allowing recovery from multiple shard failures while minimizing extra capacity usage. The system's design mitigates hot spots and balances I/O demand across drives, enhancing performance. S3 also leverages parallelism, encouraging users to make multiple connections to optimize throughput. In 2020, S3 introduced strong read-after-write consistency, ensuring immediate access to the latest data. With an impressive durability rate of 11 nines, S3 is designed to minimize data loss, making it a reliable choice for cloud storage.

- AWS S3 supports 100 million requests per second and stores 280 trillion objects.

- The architecture consists of over 300 microservices and employs millions of hard drives.

- S3 uses Erasure Coding for efficient data redundancy and recovery.

- Strong read-after-write consistency was introduced in 2020, enhancing data access.

- S3 offers 11 nines of durability, ensuring minimal data loss.