This article explains why and how to shard a MySQL database, covering vertical and horizontal partitioning, distributed transaction handling, unique ID generation, a real‑world e‑commerce case study, and future considerations for distributed architectures.
LinkedIn, the creator of Kafka, has largely abandoned Kafka in favor of a new log storage system called Northguard, whose design mirrors Apache Pulsar with features like storage‑compute separation, log striping, and a multi‑layer data model, offering superior scalability, operability, consistency, and durability for massive data streams.
This article presents nine practical strategies—including load balancing, database sharding, read‑write separation, caching, index tuning, CDN usage, asynchronous processing, code refinement, and algorithm selection—to dramatically improve the performance and scalability of large‑scale backend architectures.
This article explains single‑layer, double‑layer, and multi‑layer load‑balancing architectures, outlining their structures, advantages, disadvantages, and suitable use cases for building highly available and scalable backend systems in modern cloud environments and enterprise.
Over ten years, Alibaba’s data engineers transformed a modest Hadoop‑based system into a globally‑scalable, high‑performance big data platform—ODPS/MaxCompute—supporting massive offline and real‑time workloads, pioneering innovations like the 5K cluster expansion, Blink streaming, and the unified ‘Moon’ migration.
This article explains how to build a unified, enterprise‑grade push platform that consolidates email, SMS, chat, DingTalk, WeChat and other social channels, outlines its evolutionary stages from modular modules to a full‑blown service, and details the functional, non‑functional and architectural components required for high‑performance, scalable notification delivery.
Spine‑Leaf is a two‑layer data‑center network topology that replaces traditional three‑tier designs, reducing latency and hops by connecting every leaf switch to every spine switch, thereby improving redundancy, scalability, and cost efficiency for east‑west traffic.
This article examines why many applications set overly large database connection pools, proposes a standard of ten connections per instance based on load‑testing results, and validates the recommendation through single‑interface and link‑level performance experiments that show no throughput degradation at lower connection counts.
The article details the consistent hashing algorithm, describing how a hash ring and virtual nodes distribute keys across servers, minimize data movement during node changes, compare it with simple modulo hashing, and outline typical use cases such as load balancing, distributed caches, storage systems, and database sharding.
Understanding system design trade‑offs is crucial for building robust software; this article examines ten common compromises—from vertical vs. horizontal scaling and SQL vs. NoSQL to CAP theorem, consistency models, REST vs. GraphQL, stateful vs. stateless architectures, caching strategies, and synchronous vs. asynchronous processing—highlighting their benefits and drawbacks.
This article examines how a ten‑year‑old financial accounting platform transformed from a monolithic design into a cloud‑native, micro‑service architecture that achieved massive scalability, high availability, and 24‑hour real‑time processing through distributed batch scheduling, elastic scaling, and intelligent fault‑tolerance.
Most performance bottlenecks arise not from code but from architectural flaws, such as overly layered designs, synchronous calls, misconfigured connection pools, cache pitfalls, and inadequate monitoring, and the article outlines these issues and offers best‑practice strategies like async patterns, proper DB design, caching tiers, and progressive refactoring.
The article reviews the evolution of Kuaishou's Tianshou front‑end quality assurance platform, its layered architecture, distributed scheduler, quality models, measurement functions, DMAIC process, and lessons learned in scaling to billions of DAU, offering a blueprint for building robust front‑end engineering systems.
This article chronicles Taobao's technical evolution—from a LAMP stack through Oracle migration, Java adoption, de‑IOE optimization, self‑built storage and caching systems, service‑oriented design, middleware integration, and finally a cloud‑native architecture—highlighting the challenges and solutions for scalability, performance, and cost reduction.
Serverless architecture shifts server management to cloud providers, offering on‑demand function‑as‑a‑service and backend‑as‑a‑service solutions that enable automatic scaling, cost efficiency, faster development, enhanced security, and versatile use cases across e‑commerce, IoT, mobile apps, and big‑data analytics.
This article explains system design fundamentals and shows how to use back‑of‑the‑envelope calculations to quickly estimate load, storage, cache, and bandwidth requirements, helping engineers make informed architectural decisions with simple math and practical examples.
This article outlines a comprehensive, step‑by‑step roadmap for preparing system design interviews, covering foundational concepts, interview templates, high‑level and detailed design choices, practical resources, mock interview platforms, and company‑specific tailoring to boost candidates' success.
This article breaks down a mature e‑commerce platform into six layered modules—user reach, business operation, transaction fulfillment, supply chain, infrastructure, and BI—detailing core functions, design considerations, and data‑driven processes to guide scalable system design.
This article explains the essential role of load balancing in modern distributed systems and walks through single‑layer, double‑layer, and billion‑scale architectures, highlighting their design principles, benefits, trade‑offs, and typical deployment scenarios for high‑availability and high‑performance applications.
This article explains the concept, design goals, evolution, core components, real‑world scenarios, and key challenges of distributed architecture, illustrating how load balancing, sharding, consensus algorithms and modern cloud‑native tools enable scalable, highly available systems.
The article enumerates common pitfalls of Retrieval‑Augmented Generation—such as missing content, low‑rank document misses, context limits, format errors, incomplete answers, scalability bottlenecks, complex PDF extraction, data‑quality issues, domain adaptation gaps, hallucinations, and feedback‑loop deficiencies—and offers concrete mitigation strategies ranging from data cleaning and prompt design to hybrid search, hierarchical retrieval, document compression, and automated evaluation.
This article introduces the fundamentals of database sharding, outlines architectural evolution, explains vertical and horizontal splitting dimensions and strategies, discusses middleware choices, and presents real‑world case studies while addressing common challenges such as ID generation, join queries, pagination, and distributed transactions.
This article examines three strategies for checking username uniqueness at massive scale—direct database queries, Redis caching, and Bloom filter techniques—detailing their implementations, performance trade‑offs, memory consumption, and suitability for billions of users.
The whitepaper explains that AI model training and inference rely on massive data computation, with model sizes reaching billions of parameters, demanding low‑latency, high‑bandwidth, stable, scalable, and manageable networks; it compares RDMA‑based InfiniBand and RoCE solutions and offers design recommendations for future AI compute clusters.
This article outlines practical microservice best practices—including the Single Responsibility Principle, cross‑functional teams, appropriate tooling, asynchronous communication, DevSecOps, isolated data stores, independent deployment, orchestration, and monitoring—to help developers build maintainable, scalable, and secure cloud‑native applications.
This article examines the architecture and innovations of Alibaba Cloud's PolarDB MySQL Limitless multi‑master cluster, detailing its cloud‑native design, high‑performance horizontal scaling, distributed transaction mechanisms, multi‑node DDL, high‑availability strategies, and record‑breaking TPC‑C benchmark results.
This article examines the difficulties of adding new fields to a core billion‑row MySQL table—including locking, page splitting, and index degradation—and presents a configuration‑driven, three‑layer architecture that uses JSON extension fields, extension tables, and Elasticsearch to achieve safe, scalable dynamic schema evolution.
This article explores how to build a scalable, high‑performance leaderboard for hundreds of millions of users by comparing traditional database ORDER BY approaches with Redis sorted sets, addressing challenges such as hot keys, memory pressure, persistence risks, and presenting a divide‑and‑conquer implementation strategy.
When an Ingress gateway faces traffic exceeding 100,000 QPS, this guide outlines systematic performance optimizations, configuration tweaks, distributed architecture designs, traffic management, monitoring, and disaster‑recovery strategies—including hardware scaling, kernel tuning, DPDK, rate limiting, horizontal scaling, service mesh integration, and CDN offloading—to achieve high concurrency and high availability.
The article describes how a large‑scale dispatch system was re‑engineered with NVIDIA TritonServer to unify GPU‑accelerated operations‑research kernels and deep‑learning models, detailing a three‑stage architecture (in‑process, cross‑process, cross‑node), the performance, stability and memory challenges addressed, and future plans for heterogeneous GPU scaling.
This article objectively compares middleware‑based sharding with NewSQL distributed databases, examining architecture, distributed transactions, performance, high availability, scaling, SQL support, storage engines, and ecosystem maturity to help architects decide which solution fits their specific workload and operational constraints.
This article examines tag systems as the neural network of digital content, comparing them with traditional hierarchies, tracing their evolution, outlining business‑driven design steps, and detailing architectural components, non‑functional requirements, integration patterns, and future AI‑enhanced trends.
Microservices are independently deployable services modeled around business domains, offering benefits like smaller deployments, reduced risk, faster release cycles, and clear data ownership, while also introducing challenges such as distributed system complexity, operational overhead, and data consistency, requiring careful design of communication and scaling strategies.
This article explains what microservices are, outlines their key advantages such as scalability and resilience, details the inherent challenges like complexity and security, and introduces essential design patterns—including Database‑Per‑Service, API Gateway, BFF, CQRS, Event Sourcing, Saga, Sidecar, Circuit Breaker, ACL, and Aggregator—to help architects build robust, maintainable systems.
The article examines how the COVID‑19 pandemic accelerated digital transformation, highlighting four lessons for technology leaders—understanding consumer expectations, eliminating infrastructure fragmentation, building resilience through scalability, and embracing AI with high‑quality data—to create a secure, interoperable ecosystem that drives better customer experiences.
The article explains why modern AI agent systems need horizontal and vertical scaling, outlines the engineering challenges such as state consistency, scheduling, protocol design, and message efficiency, and compares three collaboration approaches—AutoGen's distributed runtime, classic RPC/MCP, and Google's A2A—while providing concrete code examples and deployment steps.
This article objectively compares middleware‑based sharding with NewSQL distributed databases, examining their architectural differences, transaction models, high‑availability mechanisms, scaling, SQL support, storage engines, and maturity to help practitioners decide which approach best fits their workload and operational constraints.
The article explains RocketMQ NameServer's lightweight, stateless design, its core routing and metadata management functions, AP‑oriented architecture, fault‑tolerant mechanisms, scalability features, and practical optimization techniques for high availability and low operational cost.
This article analyzes the essential requirements of massive‑scale game leaderboards, explains how Redis sorted sets and hash tables provide fast ranking and lookup, and presents a multi‑layered architecture—including hot‑key sharding, dynamic partitioning, tiered storage, read/write separation, pipeline batching, and hybrid persistence—to achieve real‑time, billion‑user performance.
Kafka 4.0 marks a milestone release that replaces ZooKeeper with the KRaft consensus engine, improves scalability and performance, introduces a server‑side consumer‑group protocol, adds shared‑group queue capabilities, and updates Java requirements and documentation, delivering a more robust and flexible streaming platform.
This article explains MySQL's replication mechanism, detailing master‑slave architecture, key threads, binlog formats (statement, row, mixed), common application scenarios such as backup, read/write splitting, and data migration, and highlights important considerations like network latency, consistency, delay, and security.
The article objectively compares NewSQL distributed databases with middleware‑plus‑sharding solutions, covering architectural differences, distributed transaction handling, high‑availability, scaling, SQL support, storage engines, maturity, and provides a decision‑making checklist to help engineers select the most suitable approach for their workloads.
Hyper‑Converged Infrastructure (HCI) integrates compute, storage, networking, and virtualization into a single software‑defined platform, simplifying deployment, management, and scaling while offering high availability, cost efficiency, and flexibility, though it entails higher upfront investment and potential performance limits.
This article explains how modern data‑intensive applications are built, detailing a complete data‑flow architecture—from API requests, caching, database queries, change capture, search indexing, and message queues—to core system concerns such as reliability, scalability, and maintainability, offering practical insights for architects.
This article objectively compares NewSQL databases with middleware‑based sharding, dissecting their core architectures, distributed transaction handling, high‑availability designs, scaling mechanisms, SQL support, storage engines, and maturity to help engineers decide the most suitable solution for their workloads.
NAVER migrated its massive analytics platform from ClickHouse to StarRocks, achieving dramatic improvements in multi‑table JOIN performance, real‑time aggregation speed, and horizontal scalability while simplifying data integration across heterogeneous sources on a Kubernetes‑based architecture.
An in‑depth comparison of NewSQL databases and middleware‑based sharding reveals each approach’s architectural strengths, distributed transaction handling, scalability, HA mechanisms, storage engine design, and ecosystem maturity, guiding readers on when to adopt NewSQL versus traditional sharding solutions.
This article analyzes how Tencent Channel builds a scalable Feeds system for a massive multi‑level community by presenting a three‑layer architecture, core design principles, and read/write diffusion strategies to handle sub‑channel lists, post squares, and personal feeds while mitigating empty‑pull and moderation challenges.
Redis achieves exceptional speed by storing all data in memory, using a single‑threaded event‑driven architecture with epoll/kqueue, employing efficient I/O multiplexing, optimizing data structures such as strings, hashes and sorted sets, and providing flexible persistence and high‑availability options, all of which are detailed in this article.
The article critically examines the hype around microservices, arguing that their true value lies in promoting modularity, clear ownership, and organizational clarity rather than solving inherent technical problems, and it traces these ideas back to classic software engineering principles and modern operational challenges.
The article compares Golang and Python for AI development, highlighting Golang’s superior scalability, performance, and concurrency while acknowledging Python’s extensive libraries, community support, and accessibility, and concludes that both languages have distinct strengths rather than one completely supplanting the other.
Notion tackled severe PostgreSQL performance limits by sharding its Block table and related tables across 480 logical shards on 32 physical databases, using workspace IDs as shard keys, a dual‑write migration, and rigorous validation to achieve near‑zero downtime and faster response times.
This article explains how Google Cloud Spanner combines relational database features with NoSQL scalability, using multi‑version storage, TrueTime, Paxos consensus, and dynamic sharding to deliver a globally distributed, strongly consistent, high‑availability database solution.
This article explains the three major Redis cache issues—cache avalanche, cache breakdown, and cache penetration—how they can overload databases, and provides practical solutions such as high‑availability deployment, appropriate key expiration, local caches, mutex locks, empty‑object caching, request validation, and Bloom filters.
The article explores the evolution, architecture, and massive scalability of China’s 12306 railway ticketing system, highlighting its real‑time processing, distributed three‑tier design, historical development from Unix to modern CS platforms, and the unique challenges that make it one of the world’s most robust backend systems.
Web3.0 introduces decentralized, blockchain‑based internet services that create performance bottlenecks, scalability, interoperability, and standardization challenges, and the article outlines how upgraded high‑performance blockchains, edge computing, modular micro‑service designs, cross‑chain solutions, and advanced security measures can help IT architectures meet these demands.
Microservices break monoliths into focused services, while serverless offloads infrastructure management to cloud providers; together they boost agility, scalability, cost efficiency, and security, as illustrated by real-world cases from ride‑hailing and e‑commerce, and the article outlines adoption challenges and future opportunities.
When the U.S. TikTok ban drove millions of users to Xiaohongshu, the app saw a massive traffic spike, prompting a detailed Operations guide covering unitized architecture, monitoring, load balancing, caching, database optimization, CI/CD automation, and emergency response planning.
This article explores multiple in‑memory strategies—using a simple map with timers, per‑driver goroutine management, and especially a Go‑implemented timing wheel—to identify Uber drivers who haven’t reported for ten minutes, comparing their complexities, memory usage, and suitability for large‑scale systems.
This article details Zhihu's security anti‑fraud system challenges with its self‑managed MongoDB cluster, the strategic move to Alibaba Cloud MongoDB services, the step‑by‑step migration plan, and the operational and performance benefits achieved after the successful cloud transition.
In an era of exploding data volumes, distributed architecture offers unparalleled scalability, fault tolerance, and parallel performance through sharding, replication, batch and stream processing, with real‑world examples from e‑commerce and social media giants illustrating its practical impact.
The article examines how the shift from centralized Web2.0 to decentralized Web3.0 creates major architectural challenges—data scattering, smart‑contract security, high concurrency, and cross‑chain interoperability—and proposes technical solutions such as distributed storage, consistency algorithms, code auditing, caching, load balancing, and cross‑chain standards.
This article details the background, challenges, and technical solutions behind the partitioning redesign of the KPOS reporting system on OceanBase, covering deployment choices, parameter tuning, data migration, phased rollout, performance gains, encountered issues, and future scaling plans.
This article examines the modern challenges of IT architecture and presents proven techniques—microservices, container orchestration, distributed caching, redundancy, load balancing, and automated fault recovery—illustrated with Amazon and Google case studies, while forecasting future AI and cloud‑native trends.
The article examines monolithic architecture’s early popularity, its simplicity and deployment ease, then details its scalability and maintenance drawbacks, and explains how distributed architectures—through decoupling, redundancy, scalability, and mechanisms like caching and load balancing—address these issues, outlining practical migration steps.
The article examines how database services must evolve to meet the high‑availability, real‑time response, horizontal scalability, application agility, security compliance, and cost‑optimization demands of modern online businesses, using Ant Group’s multi‑generation architecture and technologies such as distributed middleware, HTAP/HSAP, and polyglot persistence as examples.
This article explains what a feed stream is, why it exists, how it evolved from RSS to modern social feeds, classifies different feed models, outlines the challenges of real‑time delivery, and provides a detailed backend architecture, data structures, storage design, pagination strategy, and core publish‑read workflows to help engineers build reliable, high‑performance feed systems.
This article details the design, high‑availability mechanisms, traffic isolation, performance optimizations, caching, database migration, and refined flow‑control and degradation strategies employed to keep a billion‑user membership system reliable and performant under extreme load.
This article systematically dispels ten widespread myths about PHP—covering threading, project scale, security, modern relevance, usage scope, code quality, performance, object‑oriented support, learning depth, and scalability—showing that modern PHP remains a powerful, secure, and versatile backend technology.
This article explains how Kubernetes’ native scalability, resource optimization, performance tuning, portability, and fault‑tolerance features align with the demands of AI inference, helping organizations run large ML models efficiently, cost‑effectively, and reliably across diverse environments.
This article examines why scalability is a core requirement for AIGC products and presents a comprehensive engineering architecture—including modular design, distributed systems, resource scheduling, queue management, and layered architecture—to achieve high performance, cost efficiency, and long‑term maintainability.
The article outlines twelve major performance and architectural issues in Magento 2—including a heavy core codebase, inefficient EAV database design, slow admin UI, over‑reliance on caching, poor front‑end performance, resource‑intensive cloud requirements, indexing bottlenecks, limited scalability, third‑party extension risks, testing difficulties, slow deployment, and a steep developer learning curve.
This article explores the fundamentals of distributed systems, compares stateful and stateless services, examines monolithic, SOA, and microservice models, and provides practical guidance on access layers, fault tolerance, service discovery, scaling, and data storage for building robust cloud‑native architectures.
This article introduces feed streams, explains their evolution from RSS to modern social feeds, classifies them by aggregation logic and display, discusses challenges such as real‑time performance and massive data, and presents a backend architecture with data models, pagination, write/read diffusion, and core publishing/reading workflows.
This article explores whether Node.js can handle millions of concurrent users, explains the core non‑blocking architecture, outlines challenges such as the single‑thread model and memory leaks, and provides practical scaling tactics like clustering, load balancing, caching, and database optimization.
This article details the architecture, challenges, and optimization techniques of an app operation platform, covering its dual-engine design, caching strategies, and high‑availability principles that reduce response time to under 4 ms while supporting massive concurrent traffic.
This article examines the fundamental drawbacks of MySQL sharding in large‑scale e‑commerce, highlighting distributed transaction challenges, limited cross‑shard queries, global key constraints, scaling difficulties, operational overhead, and why distributed databases may be a better long‑term solution.
The article compares RedisSearch and Elasticsearch across definition, storage model, performance, query capabilities, scalability, ease of integration, and operational considerations, helping readers decide which solution best matches requirements such as real‑time response, data volume, query complexity, and existing tech stacks.
Performance testing involves monitoring various metrics to assess system behavior under different conditions, including response time, throughput, CPU usage, memory utilization, and error rates.
The article traces the evolution of an e‑commerce batch‑processing system—from an initial centralized workflow with reusable components, through a platform‑driven configuration and SPI registration, to a localized, asynchronous task‑reporting architecture employing priority queues and isolated thread pools—to balance flexibility, scalability, and operational risk.
This article explains how to construct a ChatGPT‑like conversational system by detailing the core dialogue flow, adding session and history management with a database, defining REST APIs, and exploring extensions such as caching, elastic scaling, and production‑ready deployment considerations.
Xiaohongshu replaced its RocketMQ‑based online messaging platform with Apache Pulsar, achieving up to 48% total cost reduction, 43% higher CPU utilization, 30% resource savings, and a latency drop from 20.2 ms to 5.7 ms through cloud‑native, elastic scaling and a phased migration strategy.
This article analyzes the motivations, benefits, and challenges of building stateful distributed systems, compares monolithic, SOA, and microservice models, and provides detailed guidance on access layers, service discovery, fault tolerance, scaling, and data storage for cloud‑native architectures.
The article presents a comprehensive checklist of critical questions covering API design, system architecture, performance tuning, data consistency, reliability, automation, and advanced features that guide backend developers toward building scalable, secure, and high‑performance services.
To meet soaring marketing‑tool demand with limited front‑end staff, the team built a three‑layer, micro‑frontend architecture—page container, scenario template, and business customization—augmented by a plugin‑style micro‑kernel, enabling over 50 % faster development, consistent UI, and configurable blocks, while acknowledging added complexity and performance trade‑offs.
The article clarifies that DevOps is not defined by specific tools like Kubernetes or Jenkins, but by the ability to design robust systems that ensure smooth deployments, effortless scaling, reliable operation, early issue detection, and effective team collaboration, emphasizing enduring principles over changing technologies.
This article recounts the evolution of Ctrip's vacation product log platform—from a single‑table DB solution to a platformized ES + HBase architecture—detailing the challenges of massive data volume, the design of RowKey, write and query flows, and the subsequent business and supplier empowerment.
This article explores strategies for efficiently verifying username uniqueness at massive scale, comparing direct database queries, Redis caching, and memory‑efficient Bloom filter techniques, complete with Java code examples and analysis of performance, load, scalability, and memory trade‑offs.
This article details the evolution of Ctrip's vacation product log system—from a simple single‑table DB in 2019, through a platformized ES + HBase architecture with custom RowKey design, to a V3.0 version that adds business and supplier empowerment, scalable storage, advanced search, and flexible data presentation for billions of daily change records.
This article presents a comprehensive backend engineering methodology for building "three‑high" systems that simultaneously achieve high performance, high concurrency, and high availability, covering performance tuning, horizontal and vertical scaling, hot‑key mitigation, fault‑tolerance mechanisms, isolation strategies, and practical DDD‑driven design.
This article shares a backend engineer’s comprehensive methodology and practical experiences for building systems that simultaneously achieve high performance, high concurrency, and high availability, covering performance optimization, caching strategies, scaling techniques, fault tolerance, and operational best practices across application, storage, and deployment layers.
This article explains how message queues decouple and buffer tasks such as payment processing, inventory updates, and notifications in high‑traffic online stores, improving reliability, scalability, and fault tolerance through asynchronous communication.
This article objectively compares NewSQL distributed databases with traditional middleware‑based sharding solutions, examining their architectural differences, transaction support, scalability, HA, storage engines, and ecosystem maturity, to help readers decide which approach best fits their performance, consistency, and operational needs.
This article compares monolithic and microservice architectures across latency, complexity, reliability, resource usage, scalability, throughput, deployment speed, and communication cost, revealing where each approach excels and offering guidance on choosing the right style for different team sizes and workloads.
This article examines the debate over sharing versus isolating databases in microservice architectures, presents arguments from both sides, shares a detailed incident from an online education platform, and outlines best‑practice recommendations for balancing availability, cost, and development efficiency.
PayPal’s rapid growth forced a shift from simple hardware upgrades to a sophisticated, actor‑based architecture built on Akka, enabling efficient resource utilization, fault tolerance, and high‑throughput processing, ultimately allowing the company to handle billions of daily transactions using only eight virtual machines.
Canva’s media service, handling billions of assets, evolved from a MySQL‑based microservice architecture to a DynamoDB‑backed solution by incrementally migrating metadata, sharding tables, employing real‑time dual writes via SQS, and implementing zero‑downtime cut‑over, dramatically improving latency and scalability.
This article outlines the progressive evolution of database architectures—from simple monolithic designs to cold‑hot separation, read‑write splitting, and horizontal sharding—explaining each pattern, its components, and the performance and scalability benefits they bring to large‑scale systems.
Kubernetes aligns perfectly with AI inference demands by offering built‑in scalability, resource and performance optimization, seamless portability across clouds, and robust fault‑tolerance, making it a cost‑effective, high‑availability foundation for deploying large‑scale machine‑learning models.
This article examines why the unified content platform switched from MongoDB to HBase, outlines HBase’s high‑performance, scalability, and consistency features, and details four optimization techniques—including cluster upgrade, connection pooling, column‑read strategy, and compaction tuning—that significantly improved read/write latency and operational stability.
