Month: March 2020

Serverless in the wild: characterizing and optimising the serverless workload at a large cloud provider

~ Adrian Colyer ~ 4 Comments
Serverless in the wild: characterizing and optimising the serverless workload at a large cloud provider, Shahrad et al., arXiv 2020 This is a fresh-from-the-arXivs paper that Jonathan Mace (@mpi_jcmace) drew my attention to on Twitter last week, thank you Jonathan! It's a classic trade-off: the quality of service offered (better service presumably driving more volume ... Continue Reading

An empirical guide to the behavior and use of scalable persistent memory

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An empirical guide to the behavior and use of scalable persistent memory, Yang et al., FAST'20 We've looked at multiple papers exploring non-volatile main memory and its implications (e.g. most recently 'Efficient lock-free durable sets'). One thing they all had in common is an evaluation using some kind of simulation of the expected behaviour of ... Continue Reading

Characterizing, modeling, and benchmarking RocksDB key-value workloads at Facebook

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Characterizing, modeling, and benchmarking RocksDB key-value workloads at Facebook, Cao et al., FAST'20 You get good at what you practice. Or in the case of key-value stores, what you benchmark. So if you want to design a system that will offer good real-world performance, it's really useful to have benchmarks that accurately represent real-world workloads. ... Continue Reading

Building an elastic query engine on disaggregated storage

~ Adrian Colyer ~ 1 Comment
Building an elastic query engine on disaggregated storage, Vuppalapati, NSDI'20 This paper describes the design decisions behind the Snowflake cloud-based data warehouse. As the saying goes, 'all snowflakes are special' - but what is it exactly that's special about this one? When I think about cloud-native architectures, I think about disaggregation (enabling each resource type ... Continue Reading