Programming Support for Scalable, Serializable and Elastic Cloud Applications
2020-07-30T14:34:08Z (GMT) by
Elasticity is an essential feature for cloud applications to handle varying and unpredictable workloads in a cost-effective way on cloud platforms. However, implementing a stateful elastic application is hard, as programmers have to: (1) reason about concurrent execution in the applications (serializability); (2) guarantee the application can process more requests with larger scale (scalability); and (3) provide elasticity management to improve performance and resource efficiency for applications (efficient elasticity management). Unfortunately, addressing all those concerns requires deep understanding and rich experience in distributed systems and cloud computing.
In this dissertation, we provide programming support to help programmers implement their stateful elastic cloud applications in a simpler manner. Specifically, we present AEON, an actor-based programming language, and \arch, an elastic programming framework. On the one hand, AEON provides programmers with scalability and serialzability, executing actor-based programs in a serialized manner while still retaining a high degree of parallelism. Meanwhile, AEON can adjust programs' scale via fine-grained live actor migration. On the other hand, PLASMA includes (1) an elastic programming language as a second ``level'' of programming (complementing the main application programming language) for describing elasticity behaviors, and (2) a novel semantics-aware elasticity management runtime that tracks program execution and acts upon application features as suggested by elasticity behaviors.
With these, PLASMA can provide efficient elasticity management to cloud applications