Optimizing the Longhorn Cloud-native Software Defined Storage Engine for High Performance
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arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866917930833281024 |
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| author | Kampadais, Konstantinos Chazapis, Antony Bilas, Angelos |
| author_facet | Kampadais, Konstantinos Chazapis, Antony Bilas, Angelos |
| contents | Longhorn is an open-source, cloud-native software-defined storage (SDS) engine that delivers distributed block storage management in Kubernetes environments. This paper explores performance optimization techniques for Longhorn's core component, the Longhorn engine, to overcome limitations in leveraging high-performance server hardware, such as solid-state NVMe disks and low-latency, high-bandwidth networking. By integrating ublk at the frontend, to expose the virtual block device to the operating system, restructuring the communication protocol, and employing DBS, our simplified, direct-to-disk storage scheme, the system achieves significant performance improvements with respect to the default I/O path. Our results contribute to enhancing Longhorn's applicability in both cloud and on-premises setups, as well as provide insights for the broader SDS community. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_14419 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Optimizing the Longhorn Cloud-native Software Defined Storage Engine for High Performance Kampadais, Konstantinos Chazapis, Antony Bilas, Angelos Distributed, Parallel, and Cluster Computing Longhorn is an open-source, cloud-native software-defined storage (SDS) engine that delivers distributed block storage management in Kubernetes environments. This paper explores performance optimization techniques for Longhorn's core component, the Longhorn engine, to overcome limitations in leveraging high-performance server hardware, such as solid-state NVMe disks and low-latency, high-bandwidth networking. By integrating ublk at the frontend, to expose the virtual block device to the operating system, restructuring the communication protocol, and employing DBS, our simplified, direct-to-disk storage scheme, the system achieves significant performance improvements with respect to the default I/O path. Our results contribute to enhancing Longhorn's applicability in both cloud and on-premises setups, as well as provide insights for the broader SDS community. |
| title | Optimizing the Longhorn Cloud-native Software Defined Storage Engine for High Performance |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2502.14419 |