# Reliable State Machines: A Framework for Programming Reliable Cloud Services

## TL;DR

Reliable State Machines (RSMs) provide a fault-tolerant programming framework for cloud services, ensuring exactly-once processing and automatic state recovery, simplifying development and improving reliability in distributed cloud applications.

## Contribution

The paper introduces RSMs, a novel fault-tolerant programming framework with formal guarantees, implementation on .NET, and demonstrated high performance and simplicity in cloud service development.

## Key findings

- RSMs guarantee exactly-once processing of requests.
- The framework achieves high throughput in micro-benchmarks.
- A case study shows simplified code and production-grade performance.

## Abstract

Building reliable applications for the cloud is challenging because of unpredictable failures during a program's execution. This paper presents a programming framework called Reliable State Machines (RSMs), that offers fault-tolerance by construction. Using our framework, a programmer can build an application as several (possibly distributed) RSMs that communicate with each other via messages, much in the style of actor-based programming. Each RSM is additionally fault-tolerant by design and offers the illusion of being "always-alive". An RSM is guaranteed to process each input request exactly once, as one would expect in a failure-free environment. The RSM runtime automatically takes care of persisting state and rehydrating it on a failover. We present the core syntax and semantics of RSMs, along with a formal proof of failure-transparency. We provide an implementation of the RSM framework and runtime on the .NET platform for deploying services to Microsoft Azure. We carried out an extensive performance evaluation on micro-benchmarks to show that one can build high-throughput applications with RSMs. We also present a case study where we rewrote a significant part of a production cloud service using RSMs. The resulting service has simpler code and exhibits production-grade performance.