Alibaba’s same‑city active‑active architecture deploys multiple data centers within one city, splits traffic between them, and ensures instant failover with layered high‑availability across access, application, and data layers, using technologies like DNS, SLB, Nginx, Redis and OceanBase.
This guide walks through Alibaba Cloud SLB’s architecture, product variants, and environment prerequisites, and step‑by‑step Terraform provisioning for CLB, ALB, and NLB, covering health checks, HTTPS setup, traffic routing, performance testing, best practices, security hardening, monitoring, and disaster‑recovery procedures.
This guide explains the two‑location three‑center disaster‑recovery pattern, describing its purpose, typical deployment across two cities and three data centers, and step‑by‑step recommendations for same‑city dual‑active or primary‑backup setups, remote backup strategies, traffic routing, and essential monitoring.
This article presents a comprehensive view of cloud stability governance from both front‑end and back‑end perspectives, detailing system architecture, micro‑frontend integration, CI/CD deployment pipelines, SLB forwarding and health‑check configurations, monitoring dashboards, UI automation testing, and the resulting operational improvements.
This article details a comprehensive, front‑and‑back‑end approach to cloud stability, covering system architecture across private and public clouds, micro‑frontend integration, CI/CD pipelines, SLB routing, health‑check configurations, monitoring dashboards, data reconciliation, UI automation testing, and the resulting improvements in observability, gray‑release, rollback, and incident reduction.
The August 4 2023 Bilibili outage, triggered by automatic back‑origin and domain‑disable policies that flooded the BFS load balancer with traffic, caused widespread white‑screens, but was mitigated within the 1‑5‑10 framework through rapid CDN switching, rate‑limit enhancements, storage backup, and client‑side fallback, illustrating the need for tighter cloud‑edge coordination.
A detailed post‑mortem of the July 2021 Bilibili outage reveals how a Lua‑induced CPU spike in the OpenResty‑based SLB caused widespread service disruption, the step‑by‑step emergency response, root‑cause analysis, and the subsequent architectural and operational improvements to prevent recurrence.
This postmortem details the July 13, 2021 Bilibili outage caused by a Lua‑induced CPU 100% bug in the OpenResty‑based SLB, describing the incident timeline, root‑cause analysis, mitigation steps, and the subsequent technical and process improvements to enhance reliability and multi‑active deployment.
This article details the July 13, 2021 Bilibili service outage caused by a Lua‑based SLB CPU spike, describing the incident timeline, root‑cause analysis of a weight‑zero bug, mitigation steps including new SLB deployment, and the subsequent operational and architectural improvements.
On July 13 2021 Bilibili’s L7 SLB crashed when a recent Lua deployment set a balancer weight to the string “0”, producing a NaN value that triggered an infinite loop and 100 % CPU, prompting emergency restarts, a fresh cluster rollout, and long‑term safeguards such as automated provisioning, stricter Lua validation, and enhanced multi‑active disaster‑recovery processes.
This article explains how to apply rate limiting at each layer of a modern service architecture—SLB, Nginx, Spring Cloud Gateway, and individual microservices—detailing traffic characteristics, interception methods, isolation techniques, and practical configurations to protect systems from overload, attacks, and cascading failures.
This article explains the principles and practical steps for implementing rate limiting at the SLB, Nginx/Kong, Spring Cloud Gateway, and Java microservice layers, covering traffic characteristics, interception rules, configuration methods, and isolation techniques to protect cloud‑native systems.
The article explains how to apply rate‑limiting at each entry point of a distributed system—SLB, Nginx, Spring Cloud Gateway, and individual Java microservices—detailing traffic characteristics, limiting strategies, isolation techniques, and the role of circuit breaking to protect backend stability.
This article explains the background of Server Load Balancing (SLB), details its three transmission modes—reverse proxy, transparent, and triangle—illustrates packet interactions with TCP and HTTP flows, and provides analysis of each mode using Wireshark captures.
This article explains the background of server load balancing (SLB), compares layer‑4 and layer‑7 implementations, and details three transmission modes—reverse proxy, transparent, and triangle—illustrating packet flows, configuration examples, and security considerations with diagrams and analysis.
This article explains the background of server load balancing (SLB), compares layer‑4 and layer‑7 approaches, and details the three SLB transmission modes—reverse proxy, transparent pass‑through, and triangle—including packet‑level analysis and practical considerations.
This article explains the background, three transmission modes of server load balancing (SLB), and detailed packet‑capture analysis for reverse‑proxy, transparent, and triangle modes, illustrating how traffic is rewritten and forwarded between clients, the load balancer, and real servers.
This article explains the background of Server Load Balancing (SLB), describes its three transmission modes—reverse‑proxy, transparent, and triangular—and provides detailed packet‑level analysis of TCP/HTTP interactions for each mode, highlighting configuration nuances and security considerations.
This article explains the purpose of Server Load Balancing (SLB), describes its three transmission modes—reverse proxy, transparent, and triangle—detailing packet flows, TCP handshakes, and HTTP interactions captured with Tcpdump and Wireshark, and discusses security considerations for each mode.
This article explains the background of Server Load Balancing (SLB), details its three transmission modes—reverse‑proxy, transparent, and triangle—and analyzes packet exchanges using Tcpdump and Wireshark to illustrate how client requests are processed and responses returned in each mode.
This article explains Alibaba Cloud's Server Load Balancer (SLB) architecture and its four-tier high‑availability design—application processing, cluster forwarding, cross‑zone disaster recovery, and cross‑region disaster recovery—detailing both product features and user‑side best practices.
This article reviews Ctrip's two‑year architecture transformation, describing how the company replaced hardware load balancers with a software‑defined SLB, introduced application‑level grouping, multi‑update mechanisms, health‑check sharing, monitoring, and the TARS release platform to achieve faster, more reliable deployments.
The article summarizes Dr. Zhang Wensong’s 2014 ArchSummit keynote on the challenges, architectural design, storage strategies, performance optimizations, monitoring, and future directions of Alibaba Cloud’s large‑scale distributed cloud computing platform, covering ECS, SLB, RDS, OCS and full‑link analytics.
