Cloudburst: stateful functions-as-a-service
Cloudburst: stateful functions-as-a-service, Sreekanti et al., arXiv 2020
Today’s paper choice is a fresh-from-the-arXivs take on serverless computing from the RISELab at Berkeley, addressing some of the limitations outlined in last year’s ‘Berkeley view on serverless computing.’ Stateless is fine until you need state, at which point the coarse-grained solutions offered by current platforms limit the kinds of application designs that work well. Last week we looked at a function shipping solution to the problem; Cloudburst uses the more common data shipping to bring data to caches next to function runtimes (though you could also make a case that the scheduling algorithm placing function execution in locations where the data is cached a flavour of function-shipping too).
Given the simplicity and economic appeal of FaaS, it is interesting to explore designs that preserve the autoscaling and operational benefits of current offerings, while adding performant, cost-efficient and consistent shared state and communication.
The key ingredients of Cloudburst are a highly-scalable key-value store for persistent state (Anna), local caches co-located with function execution environments, and cache-consistency protocols to preserve developer sanity while data is moved in and out of those caches. Oh, and there’s a scheduler Continue reading
