Chariots: A Scalable Shared Log for Data Management in Multi-Datacenter Cloud Environments

Abstract

Web-based applications face unprecedented workloads demanding the processing of a large number of events reaching to the millions per second. That is why developers are increasingly relying on scalable cloud platforms to implement cloud applications. Chariots exposes a shared log to be used by cloud applications. The log is essential for many tasks like bookkeeping, recovery, and debugging. Logs offer linearizability and simple append and read operations of immutable records to facilitate building complex systems like stream processors and transaction managers. As a cloud platform, Chariots offers fault-tolerance, persistence, and high-availability, transparently. Current shared log infrastructures suffer from the bottleneck of serializing log records through a centralized server which limits the throughput to that of a single machine. We propose a novel distributed log store, called the Fractal Log Store (FLStore), that overcomes the bottleneck of a single-point of contention. FLStore maintains the log within the datacenter. We also propose Chariots, which provides multi-datacenter replication for shared logs. In it, FLStore is leveraged as the log store. Chariots maintains causal ordering of records in the log and has a scalable design that allows elastic expansion of resources.