Serverless, or Functions-as-a-Service (FaaS), is an increasingly popular paradigm for application development,
\nas it provides implicit elastic scaling and load based billing. However, the weak execution guarantees and
\nintrinsic compute-storage separation of FaaS create serious challenges when developing applications that
\nrequire persistent state, reliable progress, or synchronization. This has motivated a new generation of serverless
\nframeworks that provide stateful abstractions. For instance, Azure\u2019s Durable Functions (DF) programming
\nmodel enhances FaaS with actors, workflows, and critical sections.
\nAs a programming model, DF is interesting because it combines task and actor parallelism, which makes
\nit suitable for a wide range of serverless applications. We describe DF both informally, using examples, and
\nformally, using an idealized high-level model based on the untyped lambda calculus. Next, we demystify
\nhow the DF runtime can (1) execute in a distributed unreliable serverless environment with compute-storage
\nseparation, yet still conform to the fault-free high-level model, and (2) persist execution progress without
\nrequiring checkpointing support by the language runtime. To this end we define two progressively more
\ncomplex execution models, which contain the compute-storage separation and the record-replay, and prove
\nthat they are equivalent to the high-level model.<\/p>\n","protected":false},"excerpt":{"rendered":"
Serverless, or Functions-as-a-Service (FaaS), is an increasingly popular paradigm for application development, as it provides implicit elastic scaling and load based billing. However, the weak execution guarantees and intrinsic compute-storage separation of FaaS create serious challenges when developing applications that require persistent state, reliable progress, or synchronization. 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