Distributed shared logs simplify the implementation and interoperation of data stores. This paper addresses a simple question: Is it feasible to build a single, datacenter-wide distributed shared log that can support all the data stores running in a datacenter? We answer in the affirmative by presenting RingWorld, a scalable log based on a ring of programmable switches that can sustain tens of billions of appends per second while maintaining low latency. We hope the design of RingWorld will propel the adoption of shared logs as a core part of datacenter infrastructure.

Data serialization is critical for many datacenter applications, but the memory copies required to move application data into packets are costly. Recent zero-copy APIs expose NIC scatter-gather capabilities, raising the possibility of offloading this data movement to the NIC. However, as the memory coordination required for scatter-gather adds bookkeeping overhead, scatter-gather is not always useful. We describe Cornflakes, a hybrid serialization library stack that uses scatter-gather for serialization when it improves performance and falls back to memory copies otherwise. We have implemented Cornflakes within a UDP and TCP networking stack, across Mellanox and Intel NICs. On a Twitter cache trace, Cornflakes achieves 15.4% higher throughput than prior software approaches on a custom key-value store and 8.8% higher throughput than Redis serialization within Redis.