Engineering server-driven consistency for large scale dynamic web services

Abstract

Many researchers have shown that server-driven consistency protocols can potentially reduce read latency. Server-driven consistency protocols are particularly attractive for large-scale dynamic web workloads because dynamically gener- A ted data can change rapidly and unpredictably. However, there have been no reports on engineering server-driven con-sistency for such a workload. This paper reports our experi-ence in engineering server-driven consistency for a Sporting and Event web site hosted by IBM, one of the most popu-lar web sites on the Internet for the duration of the event. Our study focuses on scalability and cachability of dynamic content. To assess scalability, we measure both the amount of state that a server needs to maintain to ensure consis-tency and the bursts of load that a server sustains to send out invalidation messages when a popular object is modified. We find that it is possible to limit the size of the server's state without significant performance costs and that bursts of load can be smoothed out with minimal impact on the consistency guarantees. To improve performance, we sys-tematically investigate several design issues for which prior research has suggested widely different solutions, including how long servers should send invalidations to idle clients. Finally, we quantify the performance impact of caching dy-namic data with server-driven consistency protocols and find that it can reduce read latency by more than 10%. We have implemented a prototype of a server-driven consistency pro-tocol based on our findings on top of the popular Squid cache.