Consistent hashing maps both servers and keys onto a virtual hash ring, allowing keys to be assigned to the nearest clockwise server, which minimizes data movement during node addition or removal, improves load distribution with virtual nodes, and is widely used in distributed caching and load balancing systems.
This article explains the business model, capabilities, service types, order lifecycle, and detailed architectural evolution of Baidu's transaction middle‑platform order system, covering instruction orchestration, performance optimizations such as caching, async execution, ThreadLocal handling, and database sharding for high‑throughput scenarios.
From early monolithic MVC setups to growth‑stage distributed systems and finally fully cloud‑native microservice architectures, this article outlines each phase’s characteristics, technology choices, scaling strategies, and operational practices such as CDN, load balancing, Redis Cluster, Kubernetes auto‑scaling, and unified configuration management.
This article explains Elasticsearch’s distributed cluster design, covering core concepts such as nodes, indices, shards, and replicas, compares mixed and tiered deployment models, examines data‑layer storage options, and discusses two typical distributed system architectures with their trade‑offs.
This article provides a comprehensive technical guide on building large‑scale distributed websites, covering characteristics, architectural goals, patterns, performance, high‑availability, scalability, extensibility, security, agility, and a detailed e‑commerce case study with practical diagrams and capacity estimations.
This article explains Zookeeper's ZAB (Zookeeper Atomic Broadcast) protocol, detailing node roles, the leader election process during startup and failure, the two‑phase commit data synchronization, ordering guarantees, and scenarios of leader crash and data loss, providing clear diagrams and code examples.
This article provides a comprehensive technical overview of large‑scale distributed website architecture, covering characteristics, design goals, architectural patterns, performance, high availability, scalability, extensibility, security, agility, evolution stages, capacity estimation, and practical optimization techniques for e‑commerce platforms.
This article details the design and implementation of a high‑availability membership system, covering Elasticsearch dual‑center master‑slave clusters, traffic‑isolated three‑cluster ES architecture, Redis multi‑center caching, MySQL dual‑center partitioning, data migration strategies, and refined flow‑control and degradation mechanisms to ensure stable, low‑latency service under massive concurrent load.
This article demystifies consensus algorithms by explaining the difference between consistency and consensus, introducing the replicated state machine concept, and providing a concise, step‑by‑step walkthrough of the Raft algorithm—including state simplification, leader election, log replication, and safety guarantees.
This article examines the characteristics of Redis and Memcached, identifies typical design mistakes such as consistency, cache avalanche, hot‑key, penetration and breakdown issues, and presents practical mitigation strategies—including consistent hashing, binlog‑driven cache invalidation, distributed locking, and multi‑node replication—to help backend engineers build reliable high‑concurrency cache layers.
This article presents thirty practical architecture principles—from keeping designs simple and avoiding unnecessary features to embracing distributed, stateless systems and thoughtful configuration—offering a comprehensive guide for architects to lead, mentor, and build resilient, user‑focused software.
The article details Meituan's five‑year journey in building a highly available, low‑latency distributed instant‑logistics platform, describing its architectural evolution from vertical services to micro‑services, the integration of AI for cost‑efficiency‑experience optimization, and the operational challenges and solutions for scaling, consistency, and fault tolerance.
This article provides a comprehensive guide to cache usage, covering its performance benefits and costs, various update strategies, granularity control, and detailed optimizations for issues such as penetration, avalanche, hot key reconstruction, and distributed batch operations.
This article presents sixteen practical Redis use cases—including caching, distributed sessions, locks, global IDs, counters, rate limiting, bitmaps, shopping carts, timelines, queues, lotteries, likes, tags, filtering, follow models, and ranking—illustrating how to leverage Redis data structures for high‑performance, scalable backend applications.
This article provides a comprehensive overview of microservice architecture, covering its definition, history, differences from monolithic development, key characteristics, comparison with SOA, practical implementation steps, common design patterns, and the pros and cons of adopting microservices in modern software systems.
Shopee’s Real‑time Checking System provides configurable, non‑intrusive data consistency verification for micro‑services by capturing change events via CDC, streaming them through Kafka, applying flexible rules and expressions, and instantly alerting mismatches, delivering second‑level detection while scaling to tens of thousands of checks per second.
This article provides a detailed introduction to microservices, covering its definition, core principles such as small independent services, lightweight communication, independent deployment and management, the advantages and disadvantages, suitable organizational contexts, and the essential components like service discovery, API gateways, configuration centers, monitoring, circuit breaking, container orchestration, and service mesh.
The article explains consistent hashing—using a circular 2^32 hash ring with virtual nodes to evenly distribute keys across dynamic cache servers—provides a complete Go implementation including host registration, key lookup, and a bounded‑load extension that tracks server load, demonstrates a proxy‑cache setup, and discusses practical testing and production‑grade enhancements.
The article details Meituan's five‑year journey in instant logistics, describing how distributed, high‑concurrency system architecture evolved through layered upgrades, microservices, fault‑tolerance mechanisms, AI‑driven optimization, and AIOps platforms to achieve scalability, low latency, high availability, and cost efficiency.
Meituan’s instant logistics platform evolved from vertical services to a micro‑service, distributed architecture that handles massive order‑rider matching, ultra‑low latency, and high availability, leveraging AI for pricing, ETA, scheduling, and employing robust scaling, consistency, and disaster‑recovery techniques.
Learn how to resolve WebSocket session sharing issues in load‑balanced Java applications by leveraging Redis’s publish/subscribe mechanism and Spring Session, with step‑by‑step configuration, code examples, and deployment instructions for multiple distributed environments.
The article outlines Ant Group's multi‑stage journey of building large‑scale distributed system stability, describing architectural evolutions, risk‑inspection mechanisms, high‑availability solutions such as LDC and fine‑grained traffic scheduling, and intelligent risk‑defense products that together enable resilient, cost‑effective operations.
The article describes Meituan's five‑year journey in instant logistics, detailing how its distributed, high‑concurrency architecture has evolved through layered upgrades, micro‑service adoption, and AI integration to achieve low latency, high availability, cost efficiency, and scalability while addressing challenges such as massive order matching, peak traffic, data consistency, and fault tolerance.
This article provides an in‑depth overview of Kafka, covering why messaging systems are needed, core concepts, cluster architecture, performance optimizations such as sequential disk writes and zero‑copy, resource planning, deployment steps, configuration details, operational tools, and advanced topics like custom partitioners and time‑wheel scheduling.
This article explains how to architect a highly scalable backend by starting with a simple single‑server setup, then applying vertical and horizontal scaling, database replication, sharding, caching, load balancing, CDN, GeoDNS and stateless design to support over a hundred million concurrent users.
This comprehensive guide explains why modern software systems need geo‑distributed multi‑active architectures, walks through the evolution from basic single‑node setups to master‑slave replication, same‑city disaster recovery, dual‑active, two‑city three‑center, and true multi‑active designs, and highlights the key principles, risks, and implementation strategies for achieving ultra‑high availability.
This article explains the ACID properties of database transactions, distinguishes between single‑node and distributed transactions, describes the two‑phase and three‑phase commit protocols, discusses transaction states, fault tolerance, and recovery mechanisms, and shows how replication and consensus can provide high availability for transaction processing.
The LUBAN MQ platform introduces a gray‑deployment extension for RocketMQ that isolates gray traffic by assigning configurable gray queues, adds a graySubscriptionTable and grayFlag in broker and Namesrv, uses shared consumer groups with a custom rebalance strategy, and ensures loss‑less offset merging and seamless switch‑over.
The article explains how distributed systems maintain request consistency by employing idempotent IDs, state‑machine tracking, snapshot recording, and coordinated error‑handling strategies—including retries, queries, and messaging—while also addressing read/write separation limits, reconciliation, and disaster‑recovery measures to prevent duplicate actions and state divergence.
This article provides a comprehensive guide to building a custom RPC framework, covering core concepts, architecture diagrams, registration with Zookeeper, Netty communication, custom message protocols, serialization, load balancing, handling TCP packet issues, and practical deployment steps with starter modules.
The article presents thirty practical architectural principles—ranging from simplicity, YAGNI, iterative development, automated testing, and ROI to server concurrency, distributed system design, user experience, and configuration management—aimed at guiding engineers and teams toward robust, scalable, and maintainable software solutions.
This article explains the challenges of session consistency in distributed web architectures, reviews several solutions such as session replication, client‑side storage, hash‑based load balancing, centralized backend storage, and demonstrates a practical implementation using Spring Session with Redis for reliable, scalable session sharing.
This article provides a detailed overview of the evolution of software architecture from monolithic to microservices, discusses the advantages and drawbacks of each stage, and outlines essential microservice technologies such as service discovery, API gateways, authentication, logging, containerization, orchestration, and CI/CD pipelines.
This comprehensive guide explains caching fundamentals, motivations, and hardware/software perspectives, details client, network, and server cache types, addresses common problems like breakdown, avalanche, and penetration with solutions, and covers strategies, consistency, expiration policies, distributed architectures, design best practices, and implementation examples.
This article presents thirty practical software architecture principles—ranging from simplicity and YAGNI to distributed system design, user experience, and configuration management—offered by architect Srinath to guide teams in making better technical decisions and fostering collaborative, high‑quality product development.
This article explains various cache layers—from browser and client caches to CDN, reverse‑proxy, local (disk, CPU, application) and distributed caches—detailing their mechanisms, use cases, common strategies, hit‑rate monitoring, and typical challenges such as penetration, breakdown, avalanche, and consistency.
This article presents thirty concise architectural principles—ranging from KISS and YAGNI to distributed system design, user experience, and configuration management—explaining each rule, offering practical commentary, and showing how they guide architects to build simple, maintainable, and scalable software systems.
The article explains why caching is essential for high‑concurrency distributed systems, analyzes its benefits and costs, and then details various cache‑update, penetration‑prevention, bottom‑hole, avalanche, and hot‑key‑rebuild optimization techniques, offering practical guidance for reliable and performant backend architectures.
This article details the end‑to‑end evolution of ZuanZuan's push notification platform, covering terminology, architecture, large‑scale holiday pushes, real‑time data handling, performance optimizations, multi‑channel integration, AB testing, and monitoring to achieve high throughput and reliability.
This article explains the fundamental definition of software architecture, distinguishes systems, subsystems, modules, components, frameworks, and various architecture layers, and examines how architectures evolve from monoliths to distributed services and micro‑services while highlighting common pitfalls and evaluation criteria.
This article details a practical reproduction of a large‑scale WeChat red‑packet service, describing the design goals, hardware and software setup, concurrency architecture, monitoring tools, and performance results that demonstrate a single‑machine handling one million connections and up to sixty thousand queries per second.
This article examines the role of caching in high‑concurrency distributed systems, outlining its benefits and costs, various update policies such as LRU/LFU/FIFO, timeout eviction, active refresh, and advanced techniques like cache penetration protection, no‑hole, avalanche, and hot‑key mitigation.
This article explains the role of caching in high‑concurrency distributed systems, detailing its benefits, costs, various update strategies, and advanced optimizations such as penetration protection, bottom‑hole mitigation, avalanche prevention, and hot‑key rebuild handling.
The article details Meituan's five‑year journey in instant logistics, describing how its distributed high‑concurrency architecture, AI‑driven optimization, micro‑service evolution, and reliability engineering practices have been continuously refined to achieve low latency, high availability, and cost‑effective scaling.
The article describes Meituan's five‑year journey in instant logistics, detailing the challenges of massive order‑rider matching, high traffic spikes, ultra‑low latency requirements, and how a layered, micro‑service‑based distributed architecture combined with AI techniques was progressively adopted to achieve scalability, reliability, and cost efficiency.
This article traces the evolution of system architecture from monolithic applications through vertical splitting, distributed services and SOA to modern microservices, explaining their advantages, challenges, design principles, governance, observability, automation, and remote‑call mechanisms such as RPC.
This article explains the fundamentals of scheduled tasks in Java, compares Timer, ScheduledExecutorService, Quartz and Spring @Schedule, discusses why distributed scheduling is needed in clustered environments, reviews popular frameworks, and provides a step‑by‑step guide to integrating the XXL‑JOB framework into the Austin project for dynamic task management.
This article provides a comprehensive technical overview of large‑scale distributed website architecture, covering characteristics, goals, patterns, high‑performance, high‑availability, scalability, extensibility, security, and agility considerations, and walks through the evolution of an e‑commerce system with concrete examples and diagrams.
This article traces the evolution of software architecture from monolithic to microservice models, explains key concepts such as service mesh, distributed tracing, and container orchestration, and lists the essential tools and frameworks—including Docker, Kubernetes, Ocelot, Consul, and Jenkins—required to build and operate modern cloud‑native microservice systems.
This article details the design and implementation of an online customer service instant messaging system, covering requirements analysis, client‑server network model, HTTP and WebSocket protocols, distributed architecture choices such as routing rules, Redis shared memory, server‑master sync, and message‑queue broadcasting, and explains why Netty was selected as the development framework.
This article explains three Redis‑based rate‑limiting techniques—setnx with expiration, a sliding‑window implementation using sorted sets, and a token‑bucket algorithm with lists—complete with Java code examples and discussion of their advantages and limitations for high‑concurrency backend services.
This article explains the benefits, costs, and various update, penetration, bottom‑hole, avalanche, and hot‑key rebuilding strategies for caches in high‑concurrency distributed systems, offering practical guidance on choosing eviction algorithms, using Bloom filters, and improving overall system performance and reliability.
This article reviews the historical evolution of system architecture—from single‑application monoliths through vertical splitting, distributed services, SOA, and finally microservices—explaining their advantages, drawbacks, design principles, remote‑call mechanisms, automation, monitoring, and the relationship between SOA and microservices.
This article explains the design goals, exactly‑once semantics, Java transaction API, internal components such as the coordinator and transaction log, data‑flow interactions, performance considerations, and best‑practice tips for using Apache Kafka transactions in stream‑processing applications.
This article traces the evolution of system architecture—from simple monolithic applications through vertical splitting, distributed services, SOA, and finally microservices—explaining their advantages, drawbacks, design principles, remote‑call mechanisms, and the operational practices needed for modern backend development.
This article explains the principles of high availability in internet systems, covering redundancy, automatic failover, availability metrics, and detailed HA designs for each architectural layer such as load balancers, microservices, middleware, and databases.
This article explains the concept and classifications of edge computing, compares it with central cloud, outlines deployment models, discusses the challenges of running Kubernetes at the edge, and presents OpenYurt as an open‑source platform that extends native Kubernetes capabilities to distributed edge environments.
This article explains the concept of API idempotency, why duplicate requests occur in distributed systems, and presents a comprehensive set of server‑side and client‑side techniques—including token mechanisms, PRG pattern, unique indexes, optimistic locking, distributed locks, and idempotent state machines—to guarantee that repeated calls produce only a single effect.
This guide compares Kafka, Pulsar, RocketMQ, RabbitMQ, and NSQ across architecture, consumption models, delay and dead‑letter support, persistence, ordering, multi‑tenant isolation, and performance, recommending Kafka for high‑throughput log processing, Pulsar for transactional delayed messaging and disaster recovery, and NSQ for Go‑centric custom solutions.
The article discusses the importance of caching in high‑concurrency distributed systems, outlining its benefits and costs, various update policies such as LRU/LFU/FIFO, expiration, active refresh, and advanced optimizations like penetration protection, hole mitigation, avalanche prevention, and hot‑key rebuild techniques.
The article explains why caching is essential in high‑concurrency distributed systems, analyzes its benefits and costs, and then details various cache update, penetration, no‑hole, avalanche, and hot‑key rebuilding techniques, offering practical guidance for backend engineers.
Cloud‑native databases have shifted from simple containerized services to comprehensive, elastic solutions that integrate multiple engines and distributed technologies, offering horizontal scaling, fine‑grained billing, and high‑performance architectures, while enterprises must evaluate vendor perspectives and choose between public‑cloud services or private‑cloud implementations.
This article explains the key concepts, simple design, practical steps, and multiple solution patterns—including front‑end scaling, cache‑based concurrency control, and database handling—used to build a reliable high‑traffic flash‑sale system.
This article walks through the design and practical implementation of a high‑throughput red‑envelope service capable of handling 10 billion requests, covering target load calculations, hardware and software choices, client‑server coordination, performance testing, monitoring, and key takeaways for building scalable backend systems.
This article presents thirty concise software architecture principles—ranging from KISS and YAGNI to distributed system consistency and user‑experience guidelines—offered by architect Srinath to help teams adopt a gardener‑like, iterative, and pragmatic approach to building scalable, maintainable, and user‑centric systems.
This article compiles sixteen categories of learning materials, detailing the number of books for each topic—including Java, databases, caching, messaging, MongoDB, search, Zookeeper, networking, design patterns, data structures and algorithms, distributed systems, cloud‑native microservices, containers, service mesh, DevOps, and operating systems—along with a Baidu link and extraction code for access.
This article explains how to guarantee that messages are never lost when using MQ middleware such as Kafka, RabbitMQ, or RocketMQ, outlines the key interview points, and provides practical design patterns, detection mechanisms, idempotency, and scaling strategies for reliable message delivery.
The article explains why service rate limiting is essential for high‑concurrency systems, compares it with service degradation, describes common algorithms such as counter, leaky bucket and token bucket, and shows how to implement distributed rate limiting using Redis.
This article examines the role of caching in high‑concurrency distributed systems, outlining its performance benefits and associated costs, and detailing various cache‑update strategies—including LRU/LFU/FIFO, expiration, active refresh, Bloom‑filter protection, and solutions for penetration, avalanche, hot‑key rebuild, and the “no‑bottom‑hole” problem.
This article explains how Kafka 2.8 removes its dependency on Zookeeper, describes the roles of brokers, topics, partitions, and the controller in the Zookeeper‑based architecture, and outlines the KIP‑500 upgrade that replaces Zookeeper with a quorum‑based KRaft controller to improve scalability and operational simplicity.
This article explains why service rate limiting is essential for high‑concurrency systems, compares it with service degradation, introduces common limiting algorithms such as counter, leaky‑bucket and token‑bucket, and shows how to implement distributed rate limiting using Redis for real‑world backend services.
This article explains how to design microservices using domain‑driven design principles, covering bounded contexts, aggregates, context mapping, event storming, service communication patterns, and the BFF approach to achieve loosely‑coupled, highly‑cohesive backend systems.
This article explains the core concepts of SchedulerX, a cloud‑native distributed task scheduling platform, covering its resource model, visual control features, distributed batch processing capabilities, practical use‑case scenarios, and step‑by‑step integration with a SpringBoot application.
This article details the design, goals, hardware and software choices, implementation techniques, performance testing phases, and analysis of a prototype backend capable of handling one million concurrent connections and up to 60 k QPS to simulate the massive load of ten billion WeChat red‑envelope requests.
This article presents a comprehensive guide to building high‑concurrency systems for e‑commerce, covering server architecture, load balancing, database clustering, caching strategies, concurrency testing tools, message‑queue based solutions, first‑level caches, static data handling, layered and distributed designs, as well as redundancy and automation practices.
This article surveys common delayed‑message solutions in distributed messaging, compares implementations based on external storage (MySQL, RocksDB, Redis) and built‑in MQ features (RocketMQ, Pulsar, QMQ), and analyzes their advantages, disadvantages, and design considerations.
This article details a practical backend design and stress‑test that simulates 1 million concurrent users handling 100 billion WeChat red‑packet requests, covering load calculations, Go‑based implementation, QPS targets, monitoring, and performance analysis.
2021 marked a pivotal year for databases, with rapid cloud adoption, the rise of HTAP architectures, the decline of Hadoop, and open‑source becoming mainstream, while PingCAP’s TiDB exemplifies DBaaS implementation through cloud‑native design, cost optimization, security, automation, and multi‑region compliance.
Covering essential high‑availability techniques, the article examines disaster‑recovery architectures from same‑city dual‑center to cross‑country active‑passive deployments, compares five patterns, details three multi‑active models, outlines required traffic‑scheduling, replication, and database layers, and provides design methodology, practical safeguards, and key HA metrics.
This article examines common delayed (scheduled) message implementations in distributed systems, comparing external storage approaches using databases, RocksDB, and Redis, as well as built-in solutions in open-source MQs like RocketMQ, Pulsar, and QMQ, and discusses their advantages, drawbacks, and design considerations.
The article explains the CAP theorem’s origin, formal proof, detailed definitions of consistency, availability and partition tolerance, its impact on relational and NoSQL databases, various consistency models, and practical trade‑offs for designing distributed data systems.
This article explains the business scenarios that require delayed processing, compares several existing delayed‑queue solutions, and details a Redis‑backed delayed‑queue design—including its data structures, message format, multi‑node deployment, and runtime workflow—providing practical guidance for building scalable backend systems.
This article traces the history of data management from early manual and file‑system storage through relational models to modern distributed databases, covering key concepts like CAP theorem, distributed transactions, HTAP, and cloud‑native deployment trends.
This article explains the origin of the CAP theorem, its formal definitions of consistency, availability, and partition tolerance, examines how it applies to relational and NoSQL databases, discusses trade‑offs and practical strategies for balancing these properties in distributed system design.
The article reviews major cache‑consistency strategies—Cache‑Aside, Read‑Through, Write‑Through, and Write‑Behind—detailing their performance and consistency trade‑offs, discusses compensation techniques such as delayed double‑delete and MySQL binlog‑based incremental parsing (DTS) for reliable deletion and HA, and advises selecting the appropriate approach based on specific business requirements.
This article explains service governance concepts, the challenges of managing thousands of micro‑services, introduces etcd and its Raft‑based consistency model, details BoltDB storage internals, and describes Baidu's large‑scale Tianlu platform with its high‑availability, performance, scalability, and operational metrics.
This article presents JD's comprehensive big‑data security framework and distributed permission system, detailing the overall planning of the security center, data lifecycle protection strategies, core modules such as subjects, resources, policy language, and high‑performance access control, and how they address national compliance, business scalability, and technical challenges.
This article surveys delayed‑queue implementations, comparing Kafka, RocketMQ, and Redis (Redisson) designs, outlining their architectures, pros and cons, integration details, timing‑wheel mechanisms, and practical considerations for building a reliable distributed delayed‑queue service.
This article explains the Bully election algorithm used by Elasticsearch versions prior to 7.x, describes phenomena such as false death and split‑brain, and provides a detailed walkthrough of the master‑election source code including key Java methods and configuration parameters.
This article explains the fundamentals of Remote Procedure Call (RPC), detailing the end‑to‑end workflow—from interface definition and dynamic proxy generation on the client, through service registration in ZooKeeper, to server‑side handling with Spring and Netty—accompanied by complete Java code snippets and configuration examples.
The article explains how Kafka implements delayed operations using a timing wheel with O(1) insertion and deletion, describes its parameters, multi‑level wheel design for large time spans, and the mechanism of advancing the wheel via DelayQueue and the ExpiredOperationReaper, contrasting it with Netty's approach.
This article details a step‑by‑step engineering effort to model and benchmark a high‑throughput red‑packet service capable of handling 10 billion requests, covering target metrics, hardware setup, Go implementation, load generation, monitoring, and performance analysis.
This article walks through the step‑by‑step evolution of a basic single‑server MVP architecture into a large‑scale distributed system, using a simulated Taobao example to illustrate ten‑plus architectural stages, key technologies, design principles, and the eventual shift to cloud‑native microservices.
The article details Tubi's Multimedia Processing Platform (TMPP), describing its architecture, processing stages, resource management, and distributed task scheduling for large‑scale video transcoding and delivery across multiple devices.
This article explains how to protect a Spring Boot API from traffic spikes by applying common rate‑limiting algorithms, configuring Redis for distributed throttling, writing Lua scripts for atomic counters, and integrating a custom @Limit annotation with AOP to enforce limits across a cluster.
This article explains the concept of consensus in blockchain, compares private, consortium and public environments, and introduces key algorithms such as Paxos, Raft, PBFT, Proof‑of‑Work and Proof‑of‑Stake, highlighting their challenges and solutions.
This article explains how Spring Cloud Alibaba provides a one‑stop microservices solution, details its components and migration costs, offers practical learning steps, and recommends resources for mastering the framework, making it ideal for businesses seeking rapid digital transformation.
This comprehensive guide outlines a step‑by‑step learning roadmap for aspiring big data professionals, covering fundamentals, programming languages, Linux, databases, distributed theory, networking, offline and real‑time computing, data governance, warehouses, toolchains, video/book recommendations, future industry trends, interview tips, and community resources.
The article introduces “Suffering‑Oriented Programming,” a risk‑averse development approach that prioritizes only truly painful problems, follows the three maxims “first make it possible, then make it beautiful, finally make it fast,” and illustrates its application in building Storm’s distributed stream‑processing system.
This article provides a comprehensive, step‑by‑step guide on why and how to split monolithic applications, prepare for migration, execute database vertical and horizontal sharding, handle schema changes, ensure consistency, and maintain stability during and after the split, enriched with real‑world pitfalls and solutions.
