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This article explains why MongoDB sharding is required for scaling storage and performance, describes the shard, config server, and mongos components, outlines range, hash, and compound sharding strategies, and provides practical guidance on shard key selection, balancing, backup, tuning, and security.
This article explains common data‑migration strategies such as hash‑modulo, time‑range and ID‑range sharding, and compares practical migration solutions including downtime migration, dual‑write, and an MQ + Redis approach, with detailed workflow diagrams and implementation tips.
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Redis can become a bottleneck when a hot key concentrates traffic on a single shard; this article explains how to split such hot keys into multiple sub‑keys, distribute them across cluster nodes using CRC16 slot mapping, and implement the approach in high‑concurrency scenarios like coupon grabs or real‑time leaderboards.
This extensive series of 50 video lessons covers fundamental and advanced topics such as technology selection, capacity planning, micro‑service design, database scaling, caching strategies, load balancing, decoupling, layering, and service mesh, providing engineers with the knowledge needed to become proficient architects.
The article walks through every stage of a web request—from IPv4 addressing, NAT, and DNS resolution through CDN proximity and TCP stream handling, to HTTP framing, CGI versus FastCGI processing, stateless versus stateful server models, and finally database scaling techniques such as sharding and Redis caching.
This article explains how to build high‑concurrency systems by analyzing hardware and code optimizations on a single machine, exploring multi‑machine scaling, database and business‑application considerations, and presenting a practical inventory‑stock case that evolves from simple locking to partitioned, asynchronous, Redis‑based designs.
The tutorial project showcases how to implement database sharding with ShardingSphere-JDBC (versions 4 and 5) in a SpringBoot O2O order service, providing modules for sharding, a gRPC ID generator, detailed configuration of four data sources, sharding algorithms, and Swagger-based testing of order creation and queries.
The article analyzes a recent outage of Ant's internal flash‑sale service built with AI‑generated low‑code, explains why the AI‑written business logic was not the cause, details the database capacity bottleneck that triggered a snowball effect, and discusses future automation and operational strategies to prevent similar failures.
This article presents five expansion strategies—shutdown, write‑stop, log‑based, dual‑write, and smooth 2N—detailing step‑by‑step procedures for MariaDB installation, master‑master replication, dynamic data‑source configuration, and Keepalived high‑availability setup, enabling seamless horizontal scaling and minimal service disruption for large‑scale databases.
The article describes how a finance team tackled a 50‑million‑row MySQL transaction table by analyzing the pain points, defining split goals, selecting sharding‑jdbc, designing multi‑source transaction handling, pagination across shards, data migration strategies, and a staged rollout to ensure stability and performance.
This article details how a finance team tackled a 50‑million‑row MySQL transaction table by designing a horizontal sharding strategy with Sharding‑JDBC, addressing performance bottlenecks, multi‑source transaction handling, pagination across shards, and a phased data migration and rollout plan.
This technical guide explains how to scale a sharded database horizontally by introducing five expansion schemes—including shutdown, write‑stop, log‑based, dual‑write, and smooth 2N approaches—covers MariaDB installation, master‑master replication setup, dynamic data‑source configuration with ShardingJDBC, and detailed Keepalived high‑availability configuration for seamless service continuity.
The article explains the limitations of standalone MySQL for large‑scale workloads, explores sharding, read/write separation, and middleware approaches, and argues that modern distributed databases and cloud‑native solutions are the sustainable path forward for data‑intensive applications.
The article explains the limitations of standalone MySQL, outlines common scaling problems such as oversized tables and high read traffic, and compares middleware‑based sharding solutions with modern distributed databases, highlighting why the latter are becoming the preferred choice for growing applications.
The technical‑assurance team secured Bilibili’s high‑write live‑stream gift system by expanding capacity, isolating hot keys, refactoring pipelines, adding asynchronous writes, employing horizontal scaling and full‑link load testing, converting uncertain dependencies into graceful fallbacks, and deploying dual‑active, chaos‑engineered disaster‑resilience architecture aligned with business usage patterns.
This article explains the evolution from single‑node MySQL databases to master‑slave replication, various replication modes, high‑availability strategies, and both vertical and horizontal sharding techniques, while discussing the associated challenges such as distributed transactions, routing, and operational complexity.
This article explains why single‑node databases cannot keep up with rapid business growth and describes MySQL replication methods, high‑availability solutions such as MHA and MGR, and the challenges and techniques of vertical and horizontal sharding for large‑scale systems.
This article explains the evolution from single‑node MySQL to master‑slave replication, various replication modes, high‑availability solutions such as MHA and MGR, and the challenges and techniques of vertical and horizontal sharding for scaling large‑scale internet applications.