This article chronicles the evolution of a LNMP‑based website from a single‑machine setup to a multi‑server architecture handling millions of daily visits, detailing each scaling stage—including adding a database server, introducing memcached, implementing MySQL read‑write separation, load balancing, and NoSQL integration.
This article chronicles the step‑by‑step evolution of a LNMP‑based website, detailing how increasing traffic drove architectural changes such as separating web and database servers, adding memcached, implementing MySQL master‑slave replication, load balancing, NFS sharing, and finally integrating NoSQL caching to handle millions of daily visits.
The article outlines how a Discuz website’s MySQL infrastructure progresses through five stages—from a single‑machine setup for low traffic to multi‑master, read‑write split, and finally sharding and partitioning—to handle daily page views growing from under ten thousand to ten million.
In this talk, Alibaba senior wireless expert Sun Bing details Xianyu's journey from a small startup to a massive P2P community, revealing the evolving technical architecture, key design principles, dynamic front‑end/back‑end integration, service‑bus implementation, and data‑driven strategies that powered its rapid growth.
This article explains how to standardize and automate MySQL operations—including multi‑instance deployment, metadata collection, monitoring, backup, and high‑availability using Zookeeper—so that large‑scale database services can be provisioned, managed, and scaled with minimal human intervention.
This article explores core database design concepts, covering normalization principles, denormalization tactics, schema simplification, MySQL architecture, various data partitioning methods—including vertical, horizontal, logical, and time‑based sharding—and practical routing and storage optimizations for high‑performance systems.
This article explains practical techniques for improving web service availability—such as static‑dynamic separation, CDN acceleration, distributed file systems, service decomposition, and database sharding—while minimizing code changes and addressing common scaling challenges.
This article compiles diverse viewpoints on forming reliable core members, scaling from a minimal team, balancing speed with architecture, leveraging mature tools, standardizing and automating operations, and addressing the evolving needs of small‑team development and DevOps practices.
This article introduces Docker 1.12’s Swarm mode, detailing its new features such as service creation, health checks, scaling, scheduling constraints, load balancing, service discovery, and rolling updates, and provides step‑by‑step instructions for building a multi‑node Swarm cluster, deploying services, and handling node failures.
Qihoo 360 shares how it grew from a 2011 MongoDB adopter to running over 1500 instances handling 200 billion queries per day, detailing its architecture, key applications, migration decisions, backup strategies, scaling best practices, and lessons for future MongoDB projects.
This article provides a comprehensive overview of Elasticsearch 2.x, covering its distributed architecture, core concepts such as clusters, nodes, indices, shards and replicas, the ZenDiscovery master‑election process, scaling mechanisms, recovery, query features, and the underlying system components like Guice, Netty, and thread‑pool designs.
The article examines how oversized Redis instances cause catastrophic failures during primary node crashes, scaling bursts, and network issues, explains the costly re‑synchronization steps, presents real‑world timing data, and offers practical memory‑reduction strategies to keep Redis operations reliable.
This article explores the fundamentals and advanced techniques of load balancing, compares DNS round‑robin with dedicated load balancers, discusses scaling strategies, health‑check mechanisms, and introduces Alibaba’s VIPServer as a modern mid‑tier solution addressing real‑world operational challenges.
This article shares VIPShop's extensive production experience with Redis Cluster, covering use cases, storage architecture evolution, detailed best‑practice guidelines, common pitfalls, operational automation, monitoring strategies, and useful open‑source tools for large‑scale deployments.
This article explains how to build a micro‑blogging social system using Redis, covering core data models, read‑through replication, Sentinel failover, and write‑side sharding techniques that enable the platform to handle hundreds of millions of users and massive traffic.
The 2016 ATF Alibaba Technology Forum presented a comprehensive overview of Alibaba's mobile e‑commerce platform, detailing massive scale challenges, user‑experience driven innovations, container‑based client architecture, the Weex framework, and future directions such as live video, VR/AR, and high‑performance mobile networking.
The article analyzes the architecture of TDSQL, a MySQL‑based distributed SQL system designed for Tencent’s billing platform, detailing its transition from an in‑memory NoSQL solution to a high‑consistency, auto‑scaling, fault‑tolerant database with sharding, scheduler, agent, and gateway components.
This article explains how Booking.com solved MySQL master‑to‑hundreds‑of‑slaves bandwidth limits by introducing a Binlog Server component, detailing its design, advantages over traditional relay‑master setups, and multiple deployment scenarios for high‑availability and cross‑region replication.
The article chronicles Xiaomi Web's architectural journey from a simple three‑engineer monolith in 2011 through systematic service decomposition, asynchronous messaging, database sharding with Cobar, cloud‑native scaling, advanced caching, virtual inventory allocation, and sophisticated monitoring, illustrating practical lessons for building high‑performance e‑commerce platforms.
Pinterest grew from zero to over 100 billion monthly page views by rapidly expanding its infrastructure, adopting simple, mature technologies like MySQL, Redis, and Memcache, and transitioning from clustering to sharding, offering practical lessons on scaling, tool selection, ID design, and migration strategies for massive growth.
This article outlines how a startup progressively upgraded its image‑centric product architecture on Alibaba Cloud—from rapid ECS/RDS deployment, through OSS + CDN acceleration, to caching with Memcache and horizontal scaling with SLB load balancing—offering practical guidance for similar teams.
This article explains essential database design principles—including normalization, denormalization, join avoidance, and various sharding techniques—while also covering scaling strategies such as vertical upgrades, horizontal partitioning, and the use of flash storage to boost performance.
This article explains how a major e‑commerce platform built a horizontally scalable distributed search engine, designed efficient sharding and routing strategies, and implemented automated deployment, rapid scaling, and real‑time monitoring to handle the massive traffic of the 11.11 shopping festival.
Taobao’s File System (TFS) is a highly available, high‑performance distributed storage solution built on Linux servers, featuring name‑server and data‑server clusters, block‑level replication, HA mechanisms, client caching, seamless scaling, multi‑data‑center disaster recovery, and open‑source support for C++, Java, and Nginx integration.
This article explains how stateless application servers combined with load balancers form scalable clusters, detailing request routing, scaling strategies, and common implementations such as Nginx for HTTP forwarding and LVS for IP‑level balancing.
This article shares Snowball's (Xueqiu) high‑availability architecture, performance optimizations, and scaling strategies—including hybrid cloud migration, service decomposition, in‑memory caching, and metric‑driven monitoring—implemented to handle massive traffic spikes and operational challenges during a volatile stock market period.
This article walks through the full lifecycle of a MySQL database—from initial table design and single‑server deployment to performance tuning, kernel and hardware tweaks, scaling with replication, caching, sharding, partitioning, and essential maintenance tasks such as monitoring, slow‑query logging, backup and repair.
This article provides a comprehensive overview of Stack Overflow's infrastructure, detailing its vertically‑scaled hardware, use of Microsoft and Linux technologies, high‑availability design, caching layers, database strategies, deployment processes, monitoring, and the performance‑first philosophy that drives its efficient operation.
This article compiles the Q&A from a high‑level operations talk where experts discuss ELK cluster sizing, performance tuning, schema handling, integration with Hadoop and Splunk, and practical tips for managing massive log streams in production environments.
The article shares five practical insights—balancing hardware cost and capability, testing NoSQL yourself, monitoring memory and CPU metrics, accounting for network latency, and avoiding virtualization—to help engineers achieve cost‑effective, high‑performance scaling of distributed databases.
The article explains why adding servers and shifting traffic, often dismissed as low‑effort tricks, actually require substantial architectural planning, state management, load balancing, sharding, and multi‑datacenter coordination to reliably handle high‑traffic scenarios.
This article outlines the requirements, architecture, and implementation considerations for creating a private Docker registry, covering intelligent layer deduplication, a searchable web UI, horizontal scaling, and the underlying Python/Flask stack with various storage back‑ends.
