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JD Tech Talk
JD Tech Talk
Aug 3, 2024 · Operations

Evolution of Load Balancing Strategies in JD Advertising Online Model System

This article examines the progression of load‑balancing techniques used in JD's advertising online model system, analyzing current challenges, outlining requirements, reviewing static and dynamic strategies, and presenting a multi‑objective, hierarchical approach that improves service availability, resource utilization, and overall system stability.

Distributed SystemsDynamic Schedulingload balancing
0 likes · 14 min read
Evolution of Load Balancing Strategies in JD Advertising Online Model System
JD Cloud Developers
JD Cloud Developers
Aug 2, 2024 · Operations

How JD’s Advertising Platform Optimizes Load Balancing for Heterogeneous Clusters

Exploring the evolution of JD’s advertising online model system, this article examines the challenges of heterogeneous hardware load balancing, outlines static and dynamic strategies—including DNS, Nginx, LVS, Ribbon, and Dubbo—and presents a multi‑objective framework that improves service availability and resource utilization, achieving up to 20%+ efficiency gains.

Distributed Systemsheterogeneous hardwareload balancing
0 likes · 17 min read
How JD’s Advertising Platform Optimizes Load Balancing for Heterogeneous Clusters
JD Retail Technology
JD Retail Technology
Jul 24, 2024 · Operations

Load Balancing Strategies for Heterogeneous Hardware Clusters in JD Advertising Online Model System

This article examines the evolution, theory, and practical implementation of load balancing strategies for JD Advertising's online model system, focusing on heterogeneous hardware clusters, dual‑objective optimization of service availability and resource utilization, and the resulting performance improvements in large‑scale production environments.

Distributed Systemsheterogeneous clustersload balancing
0 likes · 15 min read
Load Balancing Strategies for Heterogeneous Hardware Clusters in JD Advertising Online Model System
Bilibili Tech
Bilibili Tech
Jun 2, 2023 · Backend Development

Investigation and Resolution of Service Availability Fluctuations in a High‑QPS Go Backend Service

An investigation of a 100k‑QPS Go monolith revealed that intermittent availability drops were caused by a memory‑leak in the third‑party gcache LFU implementation, which inflated GC work and produced long mark phases; upgrading gcache eliminated the leak and restored 0.999+ availability, highlighting the need for thorough observability and dependency monitoring.

Garbage CollectionGogcache
0 likes · 10 min read
Investigation and Resolution of Service Availability Fluctuations in a High‑QPS Go Backend Service