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Occupy the Cloud: Distributed Computing for the 99%

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abstract

Distributed computing remains inaccessible to a large number of users, in spite of many open source platforms and extensive commercial offerings. While distributed computation frameworks have moved beyond a simple map-reduce model, many users are still left to struggle with complex cluster management and configuration tools, even for running simple embarrassingly parallel jobs. We argue that stateless functions represent a viable platform for these users, eliminating cluster management overhead, fulfilling the promise of elasticity. Furthermore, using our prototype implementation, PyWren, we show that this model is general enough to implement a number of distributed computing models, such as BSP, efficiently. Extrapolating from recent trends in network bandwidth and the advent of disaggregated storage, we suggest that stateless functions are a natural fit for data processing in future computing environments.

fields

cs.DC 1

years

2025 1

verdicts

UNVERDICTED 1

representative citing papers

Joint$\lambda$: Orchestrating Serverless Workflows on Jointcloud FaaS Systems

cs.DC · 2025-05-28 · unverdicted · novelty 6.0

Jointλ provides a distributed, function-side orchestration layer with Backend-Shim compatibility and datastore-based failover that runs serverless workflows on heterogeneous Jointcloud FaaS systems, delivering up to 3.3× lower makespan and 65% cost reduction versus single-cloud commercial services.

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  • Joint$\lambda$: Orchestrating Serverless Workflows on Jointcloud FaaS Systems cs.DC · 2025-05-28 · unverdicted · none · ref 47 · internal anchor

    Jointλ provides a distributed, function-side orchestration layer with Backend-Shim compatibility and datastore-based failover that runs serverless workflows on heterogeneous Jointcloud FaaS systems, delivering up to 3.3× lower makespan and 65% cost reduction versus single-cloud commercial services.