Rethinking State Management in Actor Systems for Cloud-Native Applications. Liu, Y., Laigner, R., & Zhou, Y. In Proceedings of the 2024 ACM Symposium on Cloud Computing, of SoCC '24, pages 898–914, New York, NY, USA, 2024. Association for Computing Machinery. Paper doi abstract bibtex The actor model has gained increasing popularity. However, it lacks support for complex state management tasks, such as enforcing foreign key constraints and ensuring data replication consistency across actors. These are crucial properties in partitioned application designs, such as microservices. To fill this gap, we start by analyzing the key impediments in state-of-the-art actor systems. We find it difficult for developers to express complex data relationships across actors and reason about the impact of state updates on performance due to opaque state management abstractions. To solve this conundrum, we develop SmSa, a novel data management layer for actor systems, allowing developers to declare data dependencies that cut across actors, including foreign keys, data replications, and other dependencies. SmSa can transparently enforce the declared dependencies, reducing the burden on developers. Furthermore, SmSa employs novel logging and concurrency control algorithms to support transactional maintenance of data dependencies.We demonstrate SmSa can support core data management tasks where dependencies across components appear frequently without jeopardizing application logic expressiveness and performance. Our experiments show SmSa significantly reduces the logging overhead and leads to increased concurrency level, improving by up to 2X the performance of state-of-the-art deterministic scheduling approaches. As a result, SmSa will make it easier to design and implement highly partitioned and distributed applications.
@inproceedings{rethinking_actor_state,
title = {Rethinking State Management in Actor Systems for Cloud-Native Applications},
author = {Liu, Yijian and Laigner, Rodrigo and Zhou, Yongluan},
year = 2024,
booktitle = {Proceedings of the 2024 ACM Symposium on Cloud Computing},
location = {Redmond, WA, USA},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
series = {SoCC '24},
pages = {898–914},
doi = {10.1145/3698038.3698540},
isbn = 9798400712869,
url = {https://www.researchgate.net/publication/385107871_Rethinking_State_Management_in_Actor_Systems_for_Cloud-Native_Applications},
abstract = {The actor model has gained increasing popularity. However, it lacks support for complex state management tasks, such as enforcing foreign key constraints and ensuring data replication consistency across actors. These are crucial properties in partitioned application designs, such as microservices. To fill this gap, we start by analyzing the key impediments in state-of-the-art actor systems. We find it difficult for developers to express complex data relationships across actors and reason about the impact of state updates on performance due to opaque state management abstractions. To solve this conundrum, we develop SmSa, a novel data management layer for actor systems, allowing developers to declare data dependencies that cut across actors, including foreign keys, data replications, and other dependencies. SmSa can transparently enforce the declared dependencies, reducing the burden on developers. Furthermore, SmSa employs novel logging and concurrency control algorithms to support transactional maintenance of data dependencies.We demonstrate SmSa can support core data management tasks where dependencies across components appear frequently without jeopardizing application logic expressiveness and performance. Our experiments show SmSa significantly reduces the logging overhead and leads to increased concurrency level, improving by up to 2X the performance of state-of-the-art deterministic scheduling approaches. As a result, SmSa will make it easier to design and implement highly partitioned and distributed applications.},
numpages = 17,
keywords = {actor system, application safety, consistency, microservices, state management}
}
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