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1. CausalMesh: A Causal Cache for Stateful Serverless Computing

   https://doi.org/10.14778/3704965.3704969  

   Zhang, Haoran; Mu, Shuai; Angel, Sebastian; Liu, Vincent (September 2024, Proceedings of the VLDB Endowment)

   Stateful serverless workflows consist of multiple serverless functions that access state on a remote database. Developers sometimes add a cache layer between the serverless runtime and the database to improve I/O latency. However, in a serverless environment, functions in the same workflow may be scheduled to different nodes with different caches, which can cause non-intuitive anomalies. This paper presents CausalMesh, a novel approach to causally consistent caching in serverless computing. CausalMesh is the first cache system that supports coordination-free and abort-free read/write operations and read transactions when clients roam among multiple servers. CausalMesh also supports read-write transactional causal consistency in the presence of client roaming, but at the cost of abort-freedom. Our evaluation shows that CausalMesh has lower latency and higher throughput than existing proposals. 

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2. CausalMesh: A Causal Cache for Stateful Serverless Computing

   https://doi.org/10.1145/3733620.3733631  

   Zhang, Haoran; Mu, Shuai; Angel, Sebastian; Liu, Vincent (April 2025, ACM SIGMOD Record)

   Stateful serverless workflows consist of multiple serverless functions that access state on a remote database. Developers sometimes add a cache layer between the serverless runtime and the database to improve I/O latency. However, in a serverless environment, functions in the same workflow may be scheduled to different nodes with different caches, which can cause non-intuitive anomalies. This paper presents CausalMesh, a novel approach to causally consistent caching in serverless computing. CausalMesh is the first cache system that supports coordination-free and abort-free read/write operations and read transactions when clients roam among multiple servers. CausalMesh also supports read-write transactional causal consistency in the presence of client roaming but at the cost of abort-freedom. Our evaluation shows that CausalMesh has lower latency and higher throughput than existing proposals. 

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3. Boki: Towards Data Consistency and Fault Tolerance with Shared Logs in Stateful Serverless Computing

   https://doi.org/10.1145/3653072  

   Jia, Zhipeng; Witchel, Emmett (September 2024, ACM transactions on computer systems)

   Boki is a new serverless runtime that exports a shared log API to serverless functions. Boki shared logs enable stateful serverless applications to manage their state with durability, consistency, and fault tolerance. Boki shared logs achieve high throughput and low latency. The key enabler is themetalog, a novel mechanism that allows Boki to address ordering, consistency and fault tolerance independently. The metalog orders shared log records with high throughput and it provides read consistency while allowing service providers to optimize the write and read path of the shared log in different ways. To demonstrate the value of shared logs for stateful serverless applications, we build Boki support libraries that implement fault-tolerant workflows, durable object storage, and message queues. Our evaluation shows that shared logs can speed up important serverless workloads by up to 4.2 ×. 

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4. Boki: Stateful Serverless Computing with Shared Logs

   https://doi.org/10.1145/3477132.3483541  

   Jia, Zhipeng; Witchel, Emmett (October 2021, Proceedings of the ACM SIGOPS 28th Symposium on Operating Systems Principles)

   Boki is a new serverless runtime that exports a shared log API to serverless functions. Boki shared logs enable stateful serverless applications to manage their state with durability, consistency, and fault tolerance. Boki shared logs achieve high throughput and low latency. The key enabler is the metalog, a novel mechanism that allows Boki to address ordering, consistency and fault tolerance independently. The metalog orders shared log records with high throughput and it provides read consistency while allowing service providers to optimize the write and read path of the shared log in different ways. To demonstrate the value of shared logs for stateful serverless applications, we build Boki support libraries that implement fault-tolerant workflows, durable object storage, and message queues. Our evaluation shows that shared logs can speed up important serverless workloads by up to 4.7x. 

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5. Nightcore: efficient and scalable serverless computing for latency-sensitive, interactive microservices

   https://doi.org/10.1145/3445814.3446701  

   Jia, Zhipeng; Witchel, Emmett (April 2021, Architectrual Support for Programming Languages and Operating Systems)

   null (Ed.)

   The microservice architecture is a popular software engineering approach for building flexible, large-scale online services. Serverless functions, or function as a service (FaaS), provide a simple programming model of stateless functions which are a natural substrate for implementing the stateless RPC handlers of microservices, as an alternative to containerized RPC servers. However, current serverless platforms have millisecond-scale runtime overheads, making them unable to meet the strict sub-millisecond latency targets required by existing interactive microservices. We present Nightcore, a serverless function runtime with microsecond-scale overheads that provides container-based isolation between functions. Nightcore’s design carefully considers various factors having microsecond-scale overheads, including scheduling of function requests, communication primitives, threading models for I/O, and concurrent function executions. Nightcore currently supports serverless functions written in C/C++, Go, Node.js, and Python. Our evaluation shows that when running latency-sensitive interactive microservices, Nightcore achieves 1.36×–2.93× higher throughput and up to 69% reduction in tail latency. 

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