This article explains why rate limiting is essential for system stability, compares it with caching and degradation, details three core algorithms—counter, leaky bucket, and token bucket—and provides concrete Guava, Java, and Nginx + Lua code examples for implementing both local and distributed throttling.
A real‑world incident with ActiveMQ’s high‑availability setup shows that focusing on component reliability without business‑level capacity planning, monitoring, and graceful degradation can cripple services, highlighting that true high availability must prioritize overall system and user experience.
The article records a video interview where the candidate answers technical questions on MySQL isolation levels, InnoDB indexing, locking, distributed locks, Redis sharding, PHP‑FPM architecture, RabbitMQ, AOP, Hyperf, and other backend topics, reflecting on the challenges faced during the session.
This article explains the fundamental message exchange architectures and routing patterns—including publish‑subscribe, fan‑out, unidirectional and bidirectional streaming, as well as unicast, broadcast, multicast, and anycast—illustrated with diagrams and practical examples for modern backend systems.
By illustrating how to replace simple HashMap caching with Redis‑based distributed caches and locks—using SETNX, Lua scripts, and Redisson—the article shows Spring Boot developers how to prevent cache breakdown, ensure data consistency, and dramatically improve throughput in high‑concurrency web applications.
This article provides a comprehensive introduction to Apache Kafka, covering its core concepts, terminology, data flow, configuration options such as compression and partitioning, producer and consumer behavior, replication, consumer groups, offset management, and log retention strategies.
This article explains how Vipshop built the Hera data service since 2019 to provide a unified API for warehouse access, detailing its background, architecture, core features such as multi‑engine queries, adaptive execution, custom Lisp syntax, task scheduling, metrics collection, and performance gains for both B‑to‑B and B‑to‑C workloads.
This article explains how to transform single‑node Elastic Job Lite deployments into highly available solutions, covering Zookeeper‑based sharding, active‑standby strategies for dual‑data‑center setups, custom sharding implementations, and priority scheduling to ensure tasks run reliably across both primary and backup sites.
This article explains the design and architecture of a cloud-based shopping cart system, covering its functional modules, layered and cluster designs, distributed goals such as stability and elasticity, three-level caching, asynchronous checks, heterogeneous storage, payment solutions, and anti‑scalping measures.
This article explains the split‑brain phenomenon in distributed clusters, uses Zookeeper as a case study to illustrate how network partitions can create multiple leaders, and details Zookeeper's majority‑quorum mechanism, node count considerations, and common strategies for avoiding split‑brain scenarios.
This article explains why session sharing is needed in micro‑service architectures, outlines common Nginx reverse‑proxy strategies, and presents four practical solutions—Nginx ip_hash load balancing, Tomcat session replication, Redis centralized cache, and cookie‑based sharing—detailing their implementations and trade‑offs.
This article explains the circuit breaker pattern, its three-state lifecycle, and provides a detailed Go implementation with code examples, state transition logic, metric tracking, and known limitations for improving service stability.
This article presents a comprehensive visual overview of microservice concepts and architecture evolution, detailing the transition from monolithic to SOA and microservice styles, and introduces Spring Cloud’s core components—including Eureka, Ribbon, Feign, Hystrix, Zuul, Gateway, Config, Bus, OAuth2, and Sleuth—illustrated with 19 mind‑map diagrams.
This article traces the historical development of microservice architecture from monolithic to distributed services, outlines its advantages and drawbacks, and presents a comprehensive technology stack—including service communication, API gateways, authentication, fault tolerance, logging, configuration, containerization, orchestration, and CI/CD—to guide practitioners in building robust, scalable backend systems.
This article provides a comprehensive overview of distributed system fundamentals, covering concepts such as nodes, replicas, consistency models, data distribution strategies, lease and quorum mechanisms, two‑phase commit, MVCC, Paxos, and the CAP theorem, while discussing their practical engineering trade‑offs and failure handling.
The article introduces Youzan's Transparent Multilevel Cache (TMC), detailing its three‑layer architecture, hotspot detection and local caching mechanisms, integration approaches for Java applications, stability and consistency features, and performance results from real‑world e‑commerce campaigns.
Edge computing, the latest computing paradigm beyond distributed, grid, and cloud models, integrates cloud, network, and intelligent edge devices to provide globally coordinated, low‑latency, intelligent services, and its various reference architectures—ETSI MEC, Intel MEC, ECC, and OpenFog—illustrate its resource‑centric, collaborative, and heterogeneous design.
This article explains what RPC is, walks through each step of a remote procedure call—including stubs, routing, load balancing, serialization, encoding, and network transmission—and analyzes where latency originates to guide backend developers in performance optimization.
This article explains how to abstract business functions into a middle platform through 0‑level and 1‑level modeling, defines domain capabilities and centers, outlines eight service design principles, and describes essential distributed mechanisms such as service registration, elastic scaling, rate limiting, gray release, messaging, and distributed transactions.
This article outlines the design principles, layered and cluster architecture, technical requirements, caching strategies, and payment integration of a cloud‑based shopping cart system, highlighting how distributed backend components ensure stability, high performance, elasticity, and anti‑fraud measures.
This article details how a rapidly growing Chinese children's programming platform tackled the complexity of distributed system observability by adopting SkyWalking, Prometheus, and Alibaba Cloud ARMS front‑end monitoring, achieving faster fault detection, reduced operational workload, and improved user experience.
This article explains Kafka's high‑availability mechanisms, covering multi‑replica design, ISR synchronization, leader election, acknowledgment settings, and the hidden risk of the __consumer_offset topic's single‑replica configuration that can cause an entire cluster to become unavailable when one broker fails.
This article traces the evolution of a high‑concurrency backend architecture from a single‑machine setup to cloud‑native microservices, detailing ten‑plus stages such as separating Tomcat and DB, adding caches, load‑balancing with Nginx/LVS, read‑write splitting, sharding, containerization, and finally deploying on public cloud, while also summarizing key design principles.
The Transparent Multilevel Cache (TMC) solution adds application‑level hotspot detection, local caching, and hit‑rate statistics to a standard distributed cache stack, enabling automatic hotspot discovery, reducing load on backend cache clusters, and improving system stability and latency during traffic spikes.
This article explains how microservices evolved from monolithic systems, compares them with SOA, discusses data fragmentation, CAP theory, distributed transactions, service partitioning, circuit breakers, API gateways, configuration management, tracing, and reviews popular frameworks like Spring Cloud and Dubbo.
This article explores the challenges of log aggregation in micro‑service architectures, introduces a globally unique log identifier (logid) with its required properties, compares various logid generation schemes, and presents end‑to‑end solutions for log distribution, aggregation, and analysis using custom tools such as ylog and watcher.
This article details NetEase Cloud's backend engineering solutions for supporting ten‑thousand‑user concurrent mic connections, covering distributed signaling architecture, QUIC‑based weak‑network handling, server‑side audio routing, video QoS strategies, and a global transmission network (WE‑CAN) to achieve high availability and scalability.
The article compares the architectures of NSQ (YouZan branch), Kafka, and RocketMQ—detailing their coordination mechanisms, storage models, consistency guarantees, and operational trade‑offs—while recommending Kafka for log‑big‑data workloads, RocketMQ for massive topic counts, and NSQ for extensibility and lightweight deployment.
The article outlines the challenges of real‑time messaging in live‑streaming education, presents a multi‑stage backend architecture—including AccessServer, MessageServer, and specialized services—along with caching, clustering, and future enhancements such as connection migration and QUIC to achieve high reliability, low latency, and massive concurrency.
Analyzing Hystrix’s source code reveals how its circuit‑breaker, bulkhead isolation (semaphore or thread‑pool), timeout detection, fallback logic, and sliding‑window health metrics work together to prevent cascading failures in distributed systems, as illustrated by an e‑commerce order service calling multiple downstream services.
This article explains the purpose, scenarios, and detailed implementations of common rate‑limiting algorithms—including counter (fixed window), sliding window, token bucket, and leaky bucket—highlighting their advantages, drawbacks, and sample Python code for each.
This article analyzes Bilibili's recent service disruption, explains the concept and quantitative metrics of high availability, and outlines practical techniques such as rate limiting, isolation, failover, timeout control, circuit breaking, degradation, and multi‑region active‑active deployments to improve system reliability.
This article explains how to use chaos engineering with Gremlin to design, execute, and analyze four experiments that test Kafka broker load, message loss, split‑brain scenarios, and ZooKeeper outages, helping improve the reliability and resilience of Kafka deployments.
This article explains how adopting ten essential microservice best practices—such as single responsibility, independent data stores, asynchronous communication, circuit breakers, API gateways, backward‑compatible APIs, versioning, dedicated infrastructure, independent release pipelines, and organizational efficiency—helps build a loosely‑coupled, scalable, and maintainable backend system.
This article explains why distributed systems need consistency algorithms, compares weak and strong consistency, outlines the challenges of unreliable networks and clocks, and provides a detailed walkthrough of the Raft consensus protocol, its node states, state variables, RPCs, and a practical lab implementation for leader election.
The article compares four popular service registration centers—Eureka, Zookeeper, Consul, and Nacos—by outlining each system’s architecture, core principles, and operational mechanisms, with an in‑depth source‑code‑level examination of Nacos’s pull/push discovery, Raft‑based leader election, and concurrent instance management, and concludes with a comparative table of consistency, availability, and partition‑tolerance characteristics.
ClickHouse is an MPP column‑oriented DBMS that combines full DBMS functionality, advanced columnar storage with high compression, SIMD‑based vectorized execution, a rich relational SQL interface, diverse table engines, multi‑master clustering, and flexible sharding and distributed query capabilities, making it exceptionally fast for analytical workloads.
This article walks through the motivation, core components, technology choices, architecture, and implementation details—including service registration, provider and consumer modules, custom protocol design, serialization, load balancing, and Netty-based I/O—of a self‑written distributed RPC framework, and presents performance test results.
This comprehensive guide explores microservice architecture—from its historical roots and core characteristics to ten vital design patterns such as database per service, event sourcing, CQRS, Saga, BFF, API gateway, Strangler, circuit breaker, externalized configuration, and consumer‑driven contract testing—detailing their advantages, drawbacks, and practical usage scenarios.
This article walks through implementing a lightweight single‑machine MapReduce framework inspired by the original MapReduce paper, covering the abstract Map/Reduce model, task scheduling between master and workers, core Go code for map, reduce, worker, and coordinator, and a brief reflection on its limitations.
From a fresh Java junior engineer to a seasoned architect, this guide outlines the essential skills, technologies, and responsibilities at each career stage—1‑3 years, 3‑5 years, and 5‑8 years—highlighting data structures, algorithms, frameworks, distributed systems, and database expertise needed for backend development.
The article introduces the DCS_FunTester framework, explains its naming, provides Swagger API access, details local deployment steps, describes a header‑based authentication change, outlines asynchronous test execution, multi‑request handling, progress tracking, and includes relevant Java code snippets for building and running the system.
Zhou Jing shares his journey from backend architecture to leading Alibaba Cloud's edge cloud native container platform, discussing recent projects, technical challenges, design principles, emerging trends like ServiceMesh and WebAssembly, and his role in the GIAC 5G edge computing conference.
The article explains how to abstract remote data location logic using an RPC framework built on Spring and Dubbo, demonstrates proxy injection and service registration, and shows how similar principles are applied to Redis Cluster to reduce request redirection and improve scalability.
This article explains the fundamentals of message queues, their role in asynchronous processing and system decoupling, introduces Java Message Service (JMS), compares point‑to‑point and publish‑subscribe models, and provides an overview of common MQ implementations such as RabbitMQ and Kafka.
This article chronicles my step‑by‑step journey of learning Apache RocketMQ, from downloading the source and building it with Maven, configuring mirrors, launching NameServer, Broker, Producer and Consumer on Windows, to exploring the system’s architecture and design principles.
This article outlines the architecture of a high‑traffic user center system, detailing core requirements, distributed session and transaction handling, caching strategies with Redis and local caches, common challenges such as hot data and high‑frequency queries, and provides practical solutions and a concise summary.
This guide explains how to integrate the Java‑based Snowflake UIDGenerator into a Spring Boot 2.3 application, covering algorithm fundamentals, RingBuffer optimization, database setup, Maven dependencies, configuration beans, and a test case to generate high‑throughput unique IDs.
This comprehensive article explains the microservices architectural style, contrasts it with monolithic (integrated) architecture, outlines the problems solved by microservices, details design principles, splitting strategies, patterns such as Strangler and Rehab, and provides a complete Java SpringBoot example with code snippets and deployment instructions.
This article introduces key microservice architecture design patterns—including Database per Service, Event Sourcing, CQRS, Saga, BFF, API Gateway, Strangler, Circuit Breaker, Externalized Configuration, and Consumer‑Driven Contract Testing—explaining their advantages, drawbacks, appropriate usage scenarios, and example technologies to guide scalable, resilient system design.
This article introduces Apache Kafka’s KRaft (Kafka Raft) mode, explains its architectural differences from ZooKeeper‑based deployments, details essential configuration parameters, and provides a complete step‑by‑step procedure—including commands and utility tools—to set up and operate a KRaft cluster.
This article provides a comprehensive guide to using Apache RocketMQ with Spring Boot, covering core components, basic concepts, key features, step‑by‑step configuration, producer and consumer code examples, advanced message types, transaction handling, and common interview questions for distributed messaging systems.
The article analyzes the limitations of using ZooKeeper for service discovery, compares it with Alibaba's ConfigServer, discusses CAP trade‑offs, scalability, health‑check design, disaster recovery, and provides practical guidance on when to choose alternative registration solutions.
The article examines how large‑scale systems at Google, eBay, Twitter and Amazon have converged on multi‑language microservice architectures, describing their evolution, service ecosystems, incentive mechanisms, standards, operational challenges, and best practices for building, maintaining and deprecating services.
This article explains Netty's role as a mature I/O framework, outlines the end‑to‑end remote‑call workflow of a distributed service, details protocol design, shares performance‑tuning tricks, and presents best practices for building scalable, low‑latency backend systems.
This article explains the core principles of distributed consistency, covering CAP, ACID, BASE, and detailed walkthroughs of 2PC, 3PC, Paxos, Raft, Gossip, NWR, Quorum, and Lease mechanisms, highlighting their trade‑offs, failure scenarios, and practical usage in modern systems.
This article explains what Netty is, how to design a distributed service framework using it, details the RPC call flow, discusses protocol design, showcases performance‑boosting features and best practices, and provides deep insights into Netty's architecture, threading model, and low‑level optimizations.
Nebula Graph is a high‑performance, open‑source distributed graph database that separates storage and compute, supports billions of vertices, and offers millisecond query latency, while its cloud‑native DBaaS deployment faces multi‑cloud resource, performance, and operational challenges addressed through Kubernetes, KubeSphere, and custom operators.
This article explains what a big data platform is, outlines its seven‑component overall architecture, details the technical stack from data sources to applications, and describes the key subsystems such as catalog management, data integration, governance, storage, processing, sharing, development, and analysis.
The article explains how to detect and prevent message loss, guarantee reliable delivery, handle duplicate consumption, manage message backlog, and implement distributed transaction messages in systems like Kafka, RocketMQ, and RabbitMQ, providing practical code examples and best‑practice guidelines.
This article provides a comprehensive overview of caching in large‑scale distributed systems, covering cache fundamentals, classification, major implementations such as CDN, reverse‑proxy, local, and distributed caches, detailed analyses of Memcached and Redis, common design challenges, and real‑world industry solutions.
This article explains the challenges of distributed consistency in decentralized environments and provides an in‑depth overview of classic consensus algorithms such as PBFT, Proof‑of‑Work, and Proof‑of‑Stake, including their mechanisms, limitations, and suitable application scenarios.
The article explains three frequent pitfalls when adopting microservices—complex remote communication, asynchronous processing challenges, and distributed transaction difficulties—and shows how fast‑fail, retries, timeouts, compensation, lightweight workflow engines, and idempotency can reduce complexity and improve resilience.
The article compares four consistent‑hashing algorithms—Ketama’s ring with virtual nodes, Rendezvous’s highest‑random‑weight method, Google’s Jump Consistent Hash, and Maglev’s lookup‑table approach—evaluating their balance, monotonicity, stability, scalability, and time complexity, and concludes that Ketama and Jump offer the best overall trade‑off.
This article explains the core mechanisms of the Raft consensus algorithm—including leader election, log replication, safety guarantees, message structures, state transitions, and key Go implementations in etcd-raft—providing code examples and detailed analysis of functions such as becomeLeader, tickElection, and appendEntry.
This article explains the design, architecture, and implementation of Transparent Multilevel Cache (TMC), a solution that adds application‑level hotspot detection and local caching to reduce cache hot‑spot pressure, improve consistency, and boost performance for Java services in high‑traffic scenarios.
This article explains the fundamental message exchange architectures—such as publish‑subscribe, fan‑out, unidirectional and bidirectional streaming, unicast, broadcast, multicast, and anycast—and how they are used in systems like Redis, Kafka, RabbitMQ, ZeroMQ and IBM MQ to simplify communication between architects and developers.
This article explains the evolution of message‑queue middleware by comparing the basic double‑ended queue implementation, Redis list usage, Kafka’s partitioned log architecture with segment files and sparse indexes, and Pulsar’s compute‑storage separation using BookKeeper, highlighting their designs, strengths, and trade‑offs.
This comprehensive guide explains why distributed locks are needed, walks through basic Redis lock implementations, reveals common dead‑lock and expiration issues, presents atomic solutions with SET EX NX and Lua scripts, evaluates the Redlock algorithm, examines expert debates, compares Zookeeper locks, and offers practical recommendations for safe usage.
The Apache SkyWalking Day offline meetup, co‑hosted by Tencent Cloud Tengyuanhui and the SkyWalking community on June 26 in Beijing, will feature industry experts presenting deep technical insights on distributed system observability and monitoring, while attendees can learn the latest ecosystem developments, performance‑management best practices, and enter giveaways such as AirPods Pro, Tencent figurines, and stickers.
This article compares popular message middleware such as Redis, Kafka, and Pulsar, explaining their underlying data structures, strengths and weaknesses, and how concepts like partitions, replication, cursors, and storage segmentation enable high performance, scalability, and reliability in modern distributed messaging systems.
This article explores the fundamental concepts of system architecture, scaling challenges, multi‑level caching, service decomposition, and monitoring techniques in massive web platforms, using Weibo’s evolution from LAMP to service‑oriented architecture as a detailed example.
The article presents the design and implementation of Transparent Multilevel Cache (TMC), a three‑layer caching solution that adds hotspot detection and local cache to reduce distributed cache pressure, explains its transparent Java integration, describes the sliding‑window hotspot discovery pipeline, and showcases performance gains in real‑world e‑commerce campaigns.
WE‑CAN, NetEase Cloud Communication's self‑developed large‑scale distributed transmission network, dramatically improves end‑to‑end data quality, reduces costs, and supports diverse real‑time communication scenarios through intelligent routing, layered decoupling, and global edge deployment, as demonstrated by extensive production metrics.
This article explains distributed consensus, compares Paxos, ZAB and Raft, details Raft's leader election, log replication and commit mechanics, introduces read‑optimisation techniques such as ReadIndex and Lease Read, and showcases the Java‑based SOFAJRaft library with its architecture, performance tricks and real‑world use cases.
The article presents a detailed overview of Tencent Advertising's real‑time strategy data framework, explaining its role in the ad system, the challenges of massive log volumes, and the architectural, performance, and high‑availability solutions implemented to achieve fast, reliable, and scalable ad decision making.
This article describes Dada Group’s evolution from a simple 1:1 test environment to a sophisticated machine‑labeling load‑testing solution, detailing core design, isolation techniques, custom testing platform, model construction, pre‑heat strategies, and post‑test analysis that ensure system stability during high‑traffic events.
The article introduces Transparent Multilevel Cache (TMC), a comprehensive caching solution that adds hotspot detection and local caching to existing distributed cache systems, explains its three‑layer architecture, transparent Java integration, real‑time hotspot discovery process, and demonstrates performance gains in high‑traffic e‑commerce scenarios.
The article introduces Youzan's Transparent Multilevel Cache (TMC), explains why hotspot cache access harms e‑commerce applications, describes its three‑layer architecture, details the Java client integration with Hermes‑SDK for automatic hotspot detection and local caching, and presents real‑world performance gains during large‑scale promotional events.
This article explains Redis Cluster's decentralized sharding design, the role of master‑slave replication for high availability, and how strong consistency is achieved using consensus protocols such as Raft, highlighting key concepts like global log indexes and commit pointers.
Gaode Ride‑Hailing created a comprehensive 360° observability platform—standardized logging, distributed tracing, multi‑domain metrics, visual dashboards, and an incident workflow—that transforms raw data into actionable insights, accelerates root‑cause analysis, and enables automated fault defense for its large‑scale cloud‑native microservice system.
This article explains the fundamentals of distributed system consistency, covering weak and strong consistency, the CAP theorem, ACID vs BASE, and detailed overviews of protocols such as 2PC, 3PC, Paxos, Raft, Gossip, NWR, Quorum, and Lease mechanisms.
This article examines the challenges of message loss in live‑streamed online classrooms, analyzes why pushes can fail, and proposes a comprehensive reliability strategy—including TCP fundamentals, multi‑channel redundancy, sequence‑based ordering, hole‑pulling, and configurable back‑end mechanisms—to achieve near‑100% delivery.
The article defines cloud‑native data warehouses as storage‑compute separated systems that elastically scale across clouds, outlines their key traits, describes a three‑layer architecture, compares Snowflake and OushuDB implementations, and illustrates a large bank’s migration to such a platform.
This article explains how to build a highly available, high‑performance, easily extensible and secure large‑scale website architecture by evolving from a single‑server setup through application‑data separation, caching, server clustering, read‑write separation, CDN/reverse‑proxy, distributed storage, NoSQL, service decomposition, and various architectural patterns.
This article explores the definition of software architecture, reviews essential technologies such as distributed systems, clustering, caching, queues, multithreading, and rate limiting, discusses security threats like SQL injection and XSS, and highlights common design mistakes to avoid.
This article explains RabbitMQ's core messaging patterns—including simple, work queues, publish/subscribe, routing, topics, RPC, and publisher confirms—along with the four main exchange types, providing practical use‑case examples for each to help developers choose the appropriate pattern for their backend systems.
This article explains the role of a service registry in micro‑service architectures, compares Zookeeper (CP) and Eureka (AP) in terms of design, consistency, and availability, and provides detailed code and configuration examples for deploying both solutions in a high‑availability cluster.
This article reviews the seven‑year evolution of Ctrip's microservice service‑registry from manual data maintenance through an etcd‑based solution to the self‑developed Artemis system, detailing its architecture, consistent‑hash data partitioning, high‑availability design, and second‑level instance up/down mechanisms.
The article explains Youzan's Transparent Multilevel Cache (TMC), a solution that automatically detects cache hotspots, adds an application‑level local cache, and provides hit statistics to reduce load on distributed caches, improve consistency, and boost performance for high‑traffic e‑commerce scenarios.
The article explains how Kafka 2.8 removes its dependency on Zookeeper, detailing Kafka's core concepts, the role of Zookeeper in broker registration, load balancing, and controller election, the operational drawbacks of this coupling, and how KIP‑500 with a Quorum Controller modernizes the architecture.
This article explains the evolution of software architecture toward microservices, defines microservice architecture, outlines its key characteristics, advantages and disadvantages, and then details ten essential design patterns—including database per service, event sourcing, CQRS, Saga, BFF, API gateway, Strangler, circuit breaker, externalized configuration, and consumer‑driven contract testing—while advising when each should be applied.
The article explains Youzan’s Transparent Multilevel Cache (TMC), detailing its architecture, hotspot detection, local caching, consistency mechanisms, and real‑world performance gains during flash‑sale events, showing how it reduces cache pressure and improves latency for Java‑based services.
This article explains Kafka's core concepts, the challenges of consumer failures in microservice architectures, why naïve retry loops or message skipping are insufficient, and presents a nuanced approach that distinguishes recoverable from unrecoverable errors, using back‑off retries and hidden topics to preserve ordering and data integrity.
This article explains high availability in distributed systems, covering its definition, design objectives, key metrics such as MTBF, MTTR, SLA, and practical design elements like redundancy, monitoring, failover, as well as common Q&A on cost, relationship with other architecture attributes, and implementation considerations.
This article explains how to build a highly available, high‑performance, easily extensible, scalable and secure web application system by describing the evolution of large‑site architectures, common patterns such as layering, clustering, caching, asynchronous processing, and the core architectural factors of performance, availability, scalability, extensibility and security.
This article visually breaks down Kafka’s core concepts—including producers, consumers, topics, partitions, consumer groups, and cluster architecture—explaining how messages flow, are stored, and replicated across partitions and nodes, while highlighting the role of ZooKeeper in managing metadata.
This article outlines the planning, design, and Java implementation of a distributed load‑testing framework called FunTester, focusing on two test‑case schemes (case transmission and execution), an HttpRequestBase‑based demo, case creation, transmission, execution, and the complete FunRequest class code.
This article breaks down the design and source‑code implementation of RocketMQ's NameServer, detailing its core responsibilities, component interactions, and the seven Java classes that together provide network handling, connection management, routing, configuration, and startup logic.
This article compares Redis list, Kafka, and Pulsar as messaging middleware, explaining their architectures, strengths, and weaknesses—including queue fundamentals, partitioning, cursor management, consumer groups, high‑availability mechanisms, storage strategies, and consumption models—to help readers choose the right solution for large‑scale systems.
