View-centric performance optimization for database-backed web applications

View-centric performance optimization for database-backed web applications Yang et al., ICSE 2019 The problem set-up in this paper discusses the importance of keeping web page load times low as a fundamental contributor to user satisfaction (See e.g. ‘Why performance matters’). Between client-side tools such as Google’s Lighthouse, back-end tools that can analyse ORM usage and … Continue reading View-centric performance optimization for database-backed web applications

Three key checklists and remedies for trustworthy analysis of online controlled experiments at scale

Three key checklists and remedies for trustworthy analysis of online controlled experiments at scale Fabijan et al., ICSE 2019 Last time out we looked at machine learning at Microsoft, where we learned among other things that using an online controlled experiment (OCE) approach to rolling out changes to ML-centric software is important. Prior to that … Continue reading Three key checklists and remedies for trustworthy analysis of online controlled experiments at scale

Software engineering for machine learning: a case study

Software engineering for machine learning: a case study Amershi et al., ICSE'19 Previously on The Morning Paper we’ve looked at the spread of machine learning through Facebook and Google and some of the lessons learned together with processes and tools to address the challenges arising. Today it’s the turn of Microsoft. More specifically, we’ll be … Continue reading Software engineering for machine learning: a case study

Automating chaos experiments in production

Automating chaos experiments in production Basiri et al., ICSE 2019 Are you ready to take your system assurance programme to the next level? This is a fascinating paper from members of Netflix’s Resilience Engineering team describing their chaos engineering initiatives: automated controlled experiments designed to verify hypotheses about how the system should behave under gray … Continue reading Automating chaos experiments in production

One SQL to rule them all: an efficient and syntactically idiomatic approach to management of streams and tables

One SQL to rule them all: an efficient and syntactically idiomatic approach to management of streams and tables Begoli et al., SIGMOD'19 In data processing it seems, all roads eventually lead back to SQL! Today’s paper choice is authored by a collection of experts from the Apache Beam, Apache Calcite, and Apache Flink projects, outlining … Continue reading One SQL to rule them all: an efficient and syntactically idiomatic approach to management of streams and tables

Machine learning systems are stuck in a rut

Machine learning systems are stuck in a rut Barham & Isard, HotOS'19 In this paper we argue that systems for numerical computing are stuck in a local basin of performance and programmability. Systems researchers are doing an excellent job improving the performance of 5-year old benchmarks, but gradually making it harder to explore innovative machine … Continue reading Machine learning systems are stuck in a rut