Mergeable replicated data types – Part II

Mergeable replicated data types - part II Kaki et al., OOPLSA '19 Last time out we saw how Mergeable Replicated Data Types (MRDTs) use a bijection between the natural domain of a data type and relational sets to define merge semantics between two concurrently modified versions given their lowest common ancestor (LCA). Today we’re picking … Continue reading Mergeable replicated data types – Part II

Mergeable replicated data types – Part I

Mergeable replicated data types Kaki et al., OOPSLA'19 This paper was published at OOPSLA, but perhaps it’s amongst the distributed systems community that I expect there to be the greatest interest. Mergeable Replicated Data Types (MRDTs) are in the same spirit as CRDTs but with the very interesting property that they compose. Furthermore, a principled … Continue reading Mergeable replicated data types – Part I

Local-first software: you own your data, in spite of the cloud

Local-first software: you own your data, in spite of the cloud Kleppmann et al., Onward! '19 Watch out! If you start reading this paper you could be lost for hours following all the interesting links and ideas, and end up even more dissatisfied than you already are with the state of software today. You might … Continue reading Local-first software: you own your data, in spite of the cloud

SLOG: serializable, low-latency, geo-replicated transactions

SLOG: serializable, low-latency, geo-replicated transactions Ren et al., VLDB'19 SLOG is another research system motivated by the needs of the application developer (aka, user!). Building correct applications is much easier when the system provides strict serializability guarantees. Strict serializability reduces application code complexity and bugs, since it behaves like a system that is running on … Continue reading SLOG: serializable, low-latency, geo-replicated transactions

Software-defined far memory in warehouse scale computers

Software-defined far memory in warehouse-scale computers Lagar-Cavilla et al., ASPLOS'19 Memory (DRAM) remains comparatively expensive, while in-memory computing demands are growing rapidly. This makes memory a critical factor in the total cost of ownership (TCO) of large compute clusters, or as Google like to call them "Warehouse-scale computers (WSCs)." This paper describes a "far memory" … Continue reading Software-defined far memory in warehouse scale computers

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., ASPLOS'19 Last time around we looked at the DeathStarBench suite of microservices-based benchmark applications and learned that microservices systems can be especially latency sensitive, and that hotspots can propagate through a microservices architecture in interesting ways. Seer is … Continue reading Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices

An open-source benchmark suite for microservices and their hardware-software implications for cloud & edge systems

An open-source benchmark suite for microservices and their hardware-software implications for cloud & edge systems Gan et al., ASPLOS'19 Microservices are well known for producing ‘death star’ interaction diagrams like those shown below, where each point on the circumference represents an individual service, and the lines between them represent interactions. Systems built with lots of … Continue reading An open-source benchmark suite for microservices and their hardware-software implications for cloud & edge systems