Magneto: Load-Balanced Key-Value Service for Write-Intensive Workloads
Yuanhang Gao, Yingwen Chen, Xiangrui Yang, Huan Zhou, Shihua Tang, Ming Xu · IEEE Transactions on Services Computing · 2025
High-performance key-value (KV) storage is critical for the cloud, providing KV services to various cloud applications. A key challenge for KV services is that workloads of cloud applications are often write-intensive and exhibit highly-skewed characteristics, which result in load imbalance among storage servers thus lowering system performance. To address this problem, prior works set up an in-switch write-back caching mechanism, which adopts a centralized controller to balance writes. However, the limited bandwidth between the switches and the controller is a severe bottleneck for achieving high performance. In this paper, we present Magneto, a novel key-value service architecture for the cloud. At the core of Magneto is a delayed-write mechanism in the switch data plane to absorb frequent write queries for hot items. It effectively balances the load under write-intensive workloads without involving the controller. Magneto also designs a reliability mechanism to ensure system reliability during switch state transitions and failures. We implement a prototype using an FPGA-integrated switch, which has high packet-processing performance and contains enough memory to provide both the in-switch cache and the write buffer. Extensive evaluation shows that Magneto can achieve 8.4x system throughput gains compared to baseline systems when handling a skewed workload consisting of 70% reads and 30% writes. Moreover, it can reduce the load on back-end servers up to 56% in total.