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Portals: A Showcase of Multi-Dataflow Stateful Serverless
RISE Research Institutes of Sweden, Digital Systems, Data Science. KTH Royal Institute of Technology, Sweden.ORCID iD: 0000-0002-7119-5234
KTH Royal Institute of Technology, Sweden.
KTH Royal Institute of Technology, Sweden.
RISE Research Institutes of Sweden, Digital Systems, Data Science. KTH Royal Institute of Technology, Sweden.ORCID iD: 0000-0002-9351-8508
2023 (English)In: Proceedings of the VLDB Endowment, ACM Digital Library, 2023, Vol. 16, no 12, p. 4054-4057Conference paper, Published paper (Refereed)
Abstract [en]

Serverless applications spanning the cloud and edge require flexible programming frameworks for expressing compositions across the different levels of deployment. Another critical aspect for applications with state is failure resilience beyond the scope of a single dataflow graph that is the current standard in data streaming systems. This paper presents Portals, an interactive, stateful dataflow composition framework with strong end-to-end guarantees. Portals enables event-driven, resilient applications that span across dataflow graphs and serverless deployments. The demonstration exhibits three scenarios in our multi-dataflow streaming-based system: dynamically composing a stateful serverless application; an interactive cloud and edge serverless application; and a Portals browser playground. This work was partially funded by Digital Futures, the Swedish Foundation for Strategic Research under Grant No.: BD15-0006, as well as RISE AI. 

Place, publisher, year, edition, pages
ACM Digital Library, 2023. Vol. 16, no 12, p. 4054-4057
Keywords [en]
’current; Composition frameworks; Data streaming; Dataflow; Dataflow graphs; Failure resilience; Flexible programming; IS failure; Programming framework; Streaming systems; Data flow analysis
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:ri:diva-67702DOI: 10.14778/3611540.3611619Scopus ID: 2-s2.0-85174497385OAI: oai:DiVA.org:ri-67702DiVA, id: diva2:1810032
Conference
49th International Conference on Very Large Data Bases, VLDB 2023
Funder
Swedish Foundation for Strategic Research, BD15-0006
Note

This work was partially funded by Digital Futures, the Swedish Foundation for Strategic Research under Grant No.: BD15-0006, as well as RISE AI.

Available from: 2023-11-06 Created: 2023-11-06 Last updated: 2023-11-16Bibliographically approved

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Spenger, JonasCarbone, Paris

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