Maglev | BestHub

Xueersi Online School Tech Team

Aug 7, 2020 · Operations

Designing High‑Performance Software L4 Load Balancers: Insights from LVS, Google Maglev, and Facebook Katran

This article examines the limitations of traditional L4 load balancers like LVS and explains how modern software solutions—leveraging DPDK, VPP, XDP/eBPF, and consistent‑hash algorithms such as Google Maglev and Facebook Katran—can achieve high‑throughput, scalable, and highly available L4 load balancing in data‑center environments.

DPDKL4Maglev

0 likes · 17 min read

Designing High‑Performance Software L4 Load Balancers: Insights from LVS, Google Maglev, and Facebook Katran

Architecture Digest

Dec 23, 2016 · Operations

Google’s Maglev Load Balancer: Architecture, Performance, and Design Insights

Google’s internal Maglev load balancer, described in a recent research paper, bypasses the kernel to operate directly on the NIC, uses ECMP routing, consistent hashing, and memory‑shared queues to achieve sub‑microsecond packet processing while scaling horizontally across clusters.

High PerformanceMaglevNetworking

0 likes · 9 min read

Google’s Maglev Load Balancer: Architecture, Performance, and Design Insights