BAASLESS: Backend-as-a-Service (BaaS)-Enabled Workflows in Federated Serverless Infrastructures
Serverless is a popular paradigm for expressing compute-intensive applications as serverless workflows. In practice, a significant portion of the computing is typically offloaded to various Backend-as-a-Service (BaaS) cloud services. There cent rise of federated serverless and Sky computing offers c...
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Veröffentlicht in: | IEEE transactions on cloud computing 2024-08, p.1-15 |
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Sprache: | eng |
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Zusammenfassung: | Serverless is a popular paradigm for expressing compute-intensive applications as serverless workflows. In practice, a significant portion of the computing is typically offloaded to various Backend-as-a-Service (BaaS) cloud services. There cent rise of federated serverless and Sky computing offers cost and performance advantages for these BaaS-enabled serverless workflows. However, due to vendor lock-in and lack of service interoperability, many challenges remain that impact the development, deployment, and scheduling of BaaS-enabled serverless workflows in federated serverless infrastructures. This paper introduces BAASLESS - a novel platform that delivers global and dynamic federated BaaS to serverless work flows. BAASLESS provides: (i) a novel SDK for uniform and dynamic access to federated BaaS services, reducing the complexity associated with the development of BaaS-enabled serverless workflows, (ii) a novel globally-federated serverless BaaS framework that delivers a suite of BaaS -less ML services, including text-to-speech, speech-to-text, translation, and OCR, together with a globally federated storage infrastructure, comprising AWS and Google cloud providers, and (iii) a novel model and an algorithm for scheduling BaaS-enabled serverless workflows to improve their performance. Experimental results using three complementary BaaS-enabled serverless workflows show that BAASLESS improves workflow execution time by up to 2.95× compared to the state-of-the-art serverless schedulers, often at a lower cost. |
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ISSN: | 2168-7161 2372-0018 |
DOI: | 10.1109/TCC.2024.3439268 |