Ceph: Reliable, scalable, and high-performance distributed storage

As the size and performance requirements of storage systems have increased, file system designers have looked to new architectures to facilitate system scalability. The emerging object-based storage paradigm diverges from server-based (e. g. NFS) and SAN-based storage systems by coupling processors and memory with disk drives, allowing systems to delegate low-level file system operations (e. g. allocation and scheduling) to object storage devices (OSDs) and decouple I/O (read/write) from metadata (file open/close) operations. Even recent object-based systems inherit a variety of decades-old architectural choices going back to early UNIX file systems, however, limiting their ability to effectively scale.;This dissertation shows that device intelligence can be leveraged to provide reliable, scalable, and high-performance file service in a dynamic cluster environment. It presents a distributed metadata management architecture that provides excellent performance and scalability by adapting to highly variable system workloads while tolerating arbitrary node crashes. A flexible and robust data distribution function places data objects in a large, dynamic cluster of storage devices, simplifying metadata and facilitating system scalability, while providing a uniform distribution of data, protection from correlated device failure, and efficient data migration. This placement algorithm facilitates the creation of a reliable and scalable object storage service that distributes the complexity of consistent data replication, failure detection, and recovery across a heterogeneous cluster of semi-autonomous devices.;These architectural components, which have been implemented in the Ceph distributed file system, are evaluated under a variety of workloads that show superior I/O performance, scalable metadata management, and failure recovery.