Junctiond: Extending FaaS Runtimes with Kernel-Bypass
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866916151794073600 |
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| author | Saurez, Enrique Fried, Joshua Chaudhry, Gohar Irfan Choukse, Esha Goiri, Íñigo Elnikety, Sameh Belay, Adam Fonseca, Rodrigo |
| author_facet | Saurez, Enrique Fried, Joshua Chaudhry, Gohar Irfan Choukse, Esha Goiri, Íñigo Elnikety, Sameh Belay, Adam Fonseca, Rodrigo |
| contents | This report explores the use of kernel-bypass networking in FaaS runtimes and demonstrates how using Junction, a novel kernel-bypass system, as the backend for executing components in faasd can enhance performance and isolation. Junction achieves this by reducing network and compute overheads and minimizing interactions with the host operating system. Junctiond, the integration of Junction with faasd, reduces median and P99 latency by 37.33% and 63.42%, respectively, and can handle 10 times more throughput while decreasing latency by 2x at the median and 3.5 times at the tail. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_03377 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Junctiond: Extending FaaS Runtimes with Kernel-Bypass Saurez, Enrique Fried, Joshua Chaudhry, Gohar Irfan Choukse, Esha Goiri, Íñigo Elnikety, Sameh Belay, Adam Fonseca, Rodrigo Distributed, Parallel, and Cluster Computing This report explores the use of kernel-bypass networking in FaaS runtimes and demonstrates how using Junction, a novel kernel-bypass system, as the backend for executing components in faasd can enhance performance and isolation. Junction achieves this by reducing network and compute overheads and minimizing interactions with the host operating system. Junctiond, the integration of Junction with faasd, reduces median and P99 latency by 37.33% and 63.42%, respectively, and can handle 10 times more throughput while decreasing latency by 2x at the median and 3.5 times at the tail. |
| title | Junctiond: Extending FaaS Runtimes with Kernel-Bypass |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2403.03377 |