This article revisits RocketMQ's Name Server, detailing its core components, how it registers brokers, maintains routing information, handles client queries, and uses heartbeat mechanisms to ensure high availability and dynamic scaling in distributed messaging systems.
This article explains why Zookeeper's watch mechanism triggers only once, outlines the performance, reliability, and design reasons behind it, describes its asynchronous eventual consistency, and provides Java code examples for basic watches, manual re‑registration, and using the Curator framework for persistent listeners.
This article explains how to integrate WebSocket into a Spring Boot project to create a lightweight instant‑messaging system, covering dependency setup, configuration classes, core server implementation, required modules, common deployment issues, and practical solutions with complete code examples.
This article explains how to extend a single‑process Human‑in‑the‑Loop (HITL) agent to a distributed, multi‑user API service using FastAPI, detailing session management, interrupt handling, client and server fault‑recovery strategies, and providing concrete code snippets and architectural diagrams.
To replace long UUIDs with short, sequential numeric account IDs, the article explores the limitations of Snowflake’s 64‑bit IDs, evaluates MySQL auto‑increment and REPLACE INTO approaches, identifies deadlock issues, and ultimately proposes a segmented free‑ID table with batch allocation to achieve compact, ordered IDs.
This article explains the role of consensus algorithms in achieving high‑availability through redundancy and automatic failover, clarifies distributed consistency, explores the CAP theorem and its C component, and introduces the BASE theory as a practical complement for eventual consistency in modern distributed systems.
The article examines the challenges of generating short, user‑friendly numeric account IDs, evaluates Snowflake and MySQL auto‑increment approaches, discusses deadlock issues with REPLACE INTO, and presents a final segment‑based solution that allocates ID blocks per login server while avoiding waste and concurrency problems.
Chaos engineering, a scientific method for improving system resilience, is explored through an overview of leading tools such as Gremlin, ChaosBlade, Chaos Mesh, Chaos Toolkit, and ChaosMeta, alongside core concepts, real-world case studies, common misconceptions, and the practical value of controlled fault injection in distributed systems.
This article explores how to build fault‑tolerant distributed systems by formalizing consensus, outlines its core properties, explains the FLP impossibility theorem, and shows how algorithms like Raft sidestep its limits through timing constraints and recovery mechanisms.
Chaos engineering is a discipline that deliberately injects faults into distributed systems to test and improve resilience, tracing its evolution from Netflix's Chaos Monkey to modern platforms, outlining its operational workflow, benefits, and core principles for reliable system design.
This article explains the Cookie + Session mechanism for maintaining user state, discusses its limitations such as size, performance and security, examines challenges in distributed environments, and reviews common solutions including session replication, sticky load balancing, centralized storage, and the use of ThreadLocal for small‑scale backend applications.
This article dissects the classic Eight Fallacies of Distributed Computing, explaining each mistaken assumption about network reliability, latency, bandwidth, security, topology, administration, cost, and homogeneity, and provides real‑world case studies and practical recommendations to help engineers design more resilient distributed systems.
The article examines the 60‑year coding career of OceanBase founder Yang Zhenkun, outlining five concrete strategies—deep technical focus, embracing change, building soft‑skill influence, maintaining health, and proactive career planning—that enable programmers to sustain relevance and vitality in a fast‑moving industry.
Mooncake, an open‑source large‑model inference platform, introduces a KVCache‑centric architecture that dramatically improves throughput, reduces latency and cuts inference costs by up to 20%, while integrating with frameworks like SGLang and vLLM and leveraging Alibaba Cloud’s eRDMA and GPUDirect technologies for scalable, high‑performance deployments.
This article explores how fencing tokens can provide safety and liveness guarantees in distributed lock services, illustrating fault scenarios, token-based conflict resolution, and abstract system models that help engineers prioritize correctness while tolerating temporary unavailability.
Distributed systems suffer from network unreliability—including packet loss, out‑of‑order delivery, variable latency, and ambiguous node failures—making timeout settings and fault detection challenging, and this article explains these issues, compares synchronous and asynchronous networks, and discusses strategies to balance latency and resource utilization.
This article examines the unreliability of physical clocks in distributed systems, compares synchronous and asynchronous network timing, explains the roles of wall and monotonic clocks, and explores logical clocks, snapshot isolation, and practical solutions such as Google Spanner's TrueTime to ensure data consistency.
This article explains how to import 1 billion 1 KB log records stored in HDFS or S3 into MySQL by analyzing single‑table limits, using batch inserts, choosing storage engines, sharding, optimizing file‑reading methods, and coordinating distributed tasks with Redis, Redisson, and Zookeeper to ensure ordered, reliable, and high‑throughput data loading.
This article examines six different leaderboard implementation strategies—from simple database sorting and cache‑plus‑scheduled tasks to Redis sorted sets, sharded Redis clusters, pre‑computed layered caches, and real‑time stream processing with Flink—detailing their suitable scenarios, advantages, disadvantages, and architectural diagrams to help engineers choose the most appropriate solution.
This article explains how to use SLF4J's MDC with Logback to assign a unique trace ID to each request, propagate it across threads and services, and configure log patterns so that logs become fully traceable for easier debugging in distributed systems.
The article explains how the Agricultural Bank of China successfully shut down its IBM mainframe, detailing the mainframe's high‑performance architecture, redundancy features, software ecosystem, and why its replacement with a distributed micro‑service core using TDSQL marks a significant shift for banking IT infrastructure.
This article examines how unreliable physical clocks—both wall and monotonic—affect distributed systems, compares synchronous and asynchronous network timing, illustrates conflicts caused by timestamp drift, and presents logical clocks and Google’s TrueTime as robust solutions for achieving consistent ordering and data reliability.
This article explains the motivation, design choices, and implementation details of a custom distributed job scheduling framework, covering its architecture, load‑balancing strategy, message‑queue handling, persistence mechanisms, and key code snippets, while comparing it to existing solutions like Quartz, XXL‑Job, and PowerJob.
This article compiles essential interview questions covering TCP connection termination, multi‑port listening, page load workflow, Redis data structures, Kafka consumer sizing and at‑most‑once semantics, the CAP theorem, Singleton usage, C++ map complexity, and a doubly linked list reversal algorithm, providing concise explanations and code examples.
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.
The article examines China's rapid shift toward domestic databases across finance, government, and energy sectors, highlighting how DBAs must upgrade from reactive fire‑fighting to strategic architects by mastering distributed systems, AI‑driven automation, cloud‑native tools, and open‑source community collaboration.
This article explains RocketMQ's transactional message mechanism, covering half‑message storage, three transaction states, status‑check procedures, key APIs, storage reliability, and the two‑phase commit process that guarantees eventual consistency in distributed systems.
The article examines the Agricultural Bank of China's successful shutdown of its IBM mainframe, detailing the z14's specifications, redundancy and virtualization features, the shift to a high‑concurrency distributed micro‑service architecture with TDSQL, and the broader impact on banking and IBM’s presence in China.
This article critically examines the popular claims surrounding microservices, tracing their historical roots, debunking each touted benefit, exposing distributed‑computing fallacies, and highlighting the real organizational challenges, ultimately concluding that microservices are simply modular components rather than a revolutionary architecture.
This article explains TDMQ RocketMQ's distributed rate‑limiting mechanism, covering conversion rules, fast‑fail behavior, token‑based implementation, counting periods, client best practices, elastic TPS options, code examples for different SDK versions, monitoring tips, and answers to common throttling questions.
Microservices are small, autonomous services that replace monolithic codebases by emphasizing loose coupling, high cohesion, bounded contexts, technology-agnostic integration via REST, RPC, or events, disciplined code governance, semantic versioning, local transactions with eventual consistency, and robust scaling patterns such as timeouts, circuit breakers, and auto-scaling, while reflecting organizational structure and avoiding premature complexity.
JD’s advertising platform replaces rule‑based recall with a generative large‑model pipeline that unifies e‑commerce knowledge, multimodal user intent, and semantic IDs across recall, coarse‑ranking, fine‑ranking and creative optimization, while meeting sub‑100 ms latency and sub‑¥1‑per‑million‑token cost through quantization, parallelism, caching, and joint generative‑discriminative inference, delivering double‑digit performance gains and paving the way for domain‑specific foundation models.
The article explains how network failures such as packet loss, reordering, latency, and ambiguous node failures make distributed systems unreliable, compares synchronous and asynchronous networks, and discusses the trade‑off between timeout settings and resource utilization.
A friend who landed a 16K job in a first‑tier city shares more than 30 interview questions he encountered across ten+ companies, covering JVM internals, performance tuning, concurrency, design patterns, database locking, distributed transactions, and system reliability.
This article explains chaos engineering—its definition, core principles, experimental workflow, tool selection, AI‑driven enhancements, and practical case studies—providing a comprehensive guide for building resilient distributed systems across backend, cloud‑native, mobile, and AI‑enabled environments.
Using a local message table, developers can break down distributed transactions into local database operations and asynchronous MQ messages, ensuring eventual consistency, simplifying implementation, and handling retries, while balancing advantages like simplicity and compatibility against drawbacks such as added maintenance and potential queue dependencies.
The article recounts the authors' participation in EuroSys'25 in Rotterdam, detailing the conference schedule, their presentation of the Atlas network verification paper, technical insights into distributed verification, interactions with peers, and memorable social and cultural experiences during the five‑day event.
The article explains how RocketMQ ensures strict message ordering through global FIFO queues and partitioned ordering, covering use cases, key implementation techniques on the producer, broker, and consumer sides, as well as lock mechanisms, retry strategies, and fault‑tolerance design.
This article explores the challenges of data consistency in RPC timeout scenarios, especially when idempotency fails, and introduces a lightweight mock/spy tool that can dynamically configure mock responses for any method call, helping restore consistency without full transaction support.
This article explains how RocketMQ achieves high availability and data reliability through its master‑slave broker design, covering synchronous and asynchronous replication, flush strategies, transaction messaging, automatic failover with Dledger, and read‑write separation for load balancing in distributed systems.
This article explains why fault testing is essential for modern distributed and cloud environments, outlines core goals, design principles, common fault categories, practical implementation strategies such as chaos engineering and gray releases, and shows how to analyze results to continuously improve system reliability.
The article explains how to guarantee that messages are processed only once in high‑concurrency environments by combining production‑side idempotent publishing, broker‑level deduplication with unique IDs, and consumption‑side business idempotency such as database constraints or distributed locks, while also recommending monitoring, metrics, and reconciliation as safety nets.
This article explains the fundamentals of distributed transactions, covering ACID properties, the CAP theorem, two‑phase commit, TCC compensation, and a message‑queue based eventual consistency approach, while highlighting their advantages, drawbacks, and practical application scenarios.
This article explains various approaches to delayed task handling—such as database polling, JDK DelayQueue, Redis expiration listeners, Redisson delay queues, RocketMQ delayed messages, and RabbitMQ dead‑letter queues—evaluating their advantages, drawbacks, and best‑practice recommendations for reliable order‑expiration workflows.
This article explains how RocketMQ, a Chinese‑origin message queue, simplifies Kafka’s architecture while adding powerful features such as tag‑based filtering, transactional messaging, delayed and dead‑letter queues, and a unified commit‑log storage model, making delayed processing and high‑throughput scenarios easier to implement.
This article provides a comprehensive overview of RabbitMQ, an open-source AMQP-based message broker, detailing its core components—producers, exchanges, queues, consumers, and broker—along with auxiliary elements like bindings, connections, channels, virtual hosts, and key architectural features such as decoupling, flexible routing, reliability, and scalability.
This article explains the fundamentals and practical implementations of common rate‑limiting algorithms—including fixed‑window, sliding‑window, leaky‑bucket, and token‑bucket—provides Java and Redis code samples, discusses their advantages, pitfalls, and real‑world production scenarios, and offers performance‑tuning tips.
This article explains why rate limiting is essential for high‑traffic services, compares four classic algorithms (fixed‑window, sliding‑window, leaky‑bucket, token‑bucket), provides Java and Redis implementations, shares production case studies, highlights common pitfalls, and offers performance‑tuning tips for robust backend systems.
Ray Flow Insight is an Ant Group open‑source tool that visualizes Ray's distributed programming primitives—Actors, Tasks, and Objects—to turn complex reinforcement‑learning systems from opaque "black boxes" into transparent, debuggable workflows, providing logical, physical, distributed stack, and flame‑graph views for performance analysis and optimization.
This article explains the CAP theorem and its practical extension BASE, describing their core concepts, trade‑off combinations, typical components such as Zookeeper, Eureka, and Nacos, and engineering techniques like asynchronous replication, Saga, and idempotent design for building highly available distributed systems.
This visual guide walks readers through Elasticsearch fundamentals—from architecture and indexing to clustering, query DSL, aggregations, and performance tuning—using comic-style illustrations that simplify each concept for easy understanding, and security considerations, multilingual support, and real‑time search capabilities.
This article explains three Elasticsearch data‑synchronization methods, compares their pros and cons, and then dives into ES cluster structure, node roles, shard allocation, distributed queries, split‑brain handling, and fault‑tolerance mechanisms, providing a comprehensive guide for developers and ops engineers.
Kafka 4.0 introduces KRaft, a ZooKeeper‑free metadata layer built on the Raft consensus algorithm, detailing role transitions, leader election, log replication, controller and broker responsibilities, and fault‑tolerance mechanisms, enabling a more scalable and self‑managed architecture for large‑scale distributed streaming.
This article compares Kafka, RocketMQ, and RabbitMQ, detailing their architectures, performance characteristics, strengths, and ideal use‑cases to help engineers select the most suitable message‑queue solution for high‑throughput, fault‑tolerant, and real‑time processing scenarios.
By replacing the legacy FLV recorder with an m3u8‑based service, introducing a short‑segment, state‑machine transcoder, and deploying an event‑driven proxy and instant‑clipping UI, the team cut the 4‑hour‑40‑minute Spring Festival Gala’s live‑to‑VOD processing from 41 minutes to about eight minutes, achieving roughly a five‑fold speedup.
The article traces the evolution of AI training stability from early manual operations on small GPU clusters to sophisticated, fault‑tolerant infrastructures for thousand‑card and ten‑thousand‑card models, detailing Baidu Baige’s metrics, monitoring, eBPF‑based diagnostics, and checkpoint strategies that reduce invalid training time and accelerate fault recovery.
This article provides an in‑depth overview of Apache Zookeeper, covering its core concepts, common application scenarios such as pub/sub, configuration management and naming services, detailed architecture including znodes and node types, the watch mechanism, ZAB consensus protocol, and practical usage examples with Maven dependencies, Java client code, and command‑line operations.
This article provides a comprehensive overview of Apache Kafka, covering its core concepts, architecture, common use cases, installation steps, and essential command-line operations for managing topics and brokers in production environments and ensuring reliability.
The article explains how to construct a comprehensive fault‑isolation and protection system for modern distributed applications, covering entry‑side rate limiting, exit‑side circuit breaking, internal resource isolation, monitoring, chaos‑engineering validation, and automatic self‑healing mechanisms using tools such as Sentinel, Nginx, Hystrix, SkyWalking, Prometheus and Kubernetes.
This article traces the decade‑long evolution of AI training stability—from early small‑model manual operations to large‑scale, multi‑thousand‑GPU clusters—detailing metrics like invalid training time, fault‑tolerance architectures, eBPF‑based hidden‑fault detection, BCCL enhancements, multi‑level restart strategies, and trigger‑based checkpointing that together shrink downtime from minutes to seconds.
This article examines how delayed or inconsistent inventory synchronization leads to costly overselling and deadstock in e‑commerce, presents three destructive synchronization patterns, and offers a step‑by‑step guide—including real‑time messaging, distributed locks, rule‑engine integration, and intelligent alerts—to transform inventory management from a liability into a self‑healing system.
This article explains the concept of idempotency, outlines scenarios where it is essential, analyzes common causes of idempotency problems, and presents a comprehensive set of solutions—including unique constraints, optimistic and pessimistic locks, distributed locks, token mechanisms, state machines, deduplication tables, and global request IDs—accompanied by practical code examples and database design guidelines.
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.
This guide explains the key port configurations of Apache RocketMQ brokers, details essential mqadmin commands for managing topics, checking status, and monitoring consumer progress, and provides practical examples to help administrators efficiently operate and troubleshoot RocketMQ clusters.
Consistent hashing, a cornerstone of distributed systems, balances load, enhances scalability, and minimizes data migration; this article explains its fundamentals, the drawbacks of basic implementations, the role of virtual nodes, and provides a complete Go-language example with code for adding, removing, and locating nodes.
This article presents a comprehensive overview of a typical payment system architecture, detailing the division between transaction and payment cores, their interactions, service governance, data consistency, asynchronous processing, and practical production practices for building stable, scalable backend payment services.
HighService, Alibaba’s Pythonic AI service framework, accelerates large‑model inference and maximizes GPU utilization by separating CPU‑GPU processes, offering out‑of‑the‑box quantization, parallelism and caching, and dynamically reallocating idle GPUs across clusters through a master‑worker scheduler to keep online latency low while boosting offline throughput for diffusion and LLM workloads.
This article explains RPC fundamentals, detailing a Java example that uses Spring for bean management, Netty for high‑performance network communication, and Zookeeper for service registration and discovery, and walks through both server and client implementations with code snippets and test results.
Designing distributed systems often falls prey to misconceptions such as assuming reliable networks, zero latency, unlimited bandwidth, inherent security, static topology, zero transmission cost, and full autonomy, but applying retries, idempotency, message queues, encryption, dynamic discovery, caching, and time protocols can mitigate these issues.
This article explores the retry pattern as a resilient design technique for distributed systems, detailing its fundamentals, a simple Node.js implementation, and advanced strategies such as exponential backoff with jitter, circuit breaker integration, comprehensive logging, and best‑practice guidelines for robust error handling.
This article presents a complete MongoDB migration solution, detailing the migration rhythm, code refactoring using a decorator pattern, data source replacement with JImKV, MySQL and ES, bulk and incremental data transfer strategies, and deployment safeguards such as monitoring, gray release, and rollback to ensure a seamless cut‑over without service disruption.
Rate limiting protects micro‑service stability by rejecting excess traffic, using algorithms such as fixed‑window, sliding‑window, leaky‑bucket and token‑bucket, and can be deployed locally or distributed via Redis, load‑balancers, or coordination services, each offering different trade‑offs in precision, scalability, and complexity.
This article explores practical strategies for handling the high‑concurrency inventory deduction problem in flash‑sale scenarios, covering lock‑based approaches, Redis caching, partitioned stock management, asynchronous updates, and distributed scaling techniques to prevent overselling and improve throughput.
This comprehensive guide explores the fundamentals of distributed systems, covering theoretical foundations, architecture design patterns, consistency models, scalability, deployment, operations, and practical engineering practices for building robust microservice‑based solutions.
This guide explains Apache RocketMQ’s ordinary message concept, its full lifecycle, how to create topics, Java code for sending and receiving messages, key configuration tips, and real‑world scenarios such as asynchronous decoupling and traffic‑shaping for micro‑service architectures.
This article explores how modern distributed databases treat logs as foundational storage components, examines industry best practices from Aurora DSQL, DynamoDB, and OceanBase, and abstracts the essential properties and design considerations for building a universal, durable, and linearizable log module.
This article explains the locality principle—time and space locality—and shows how applying these concepts to caching and data access in distributed systems can dramatically reduce database query volume, improve latency, and achieve up to 84% performance gains while managing memory and GC overhead.
This article analyzes the "write‑after‑immediate‑read" challenge in multi‑active disaster‑recovery setups, breaks down solution directions, presents a three‑city five‑center case study, and outlines a four‑step model—distinguish scenarios, mark written data, assess latency, and enable near‑by access—to achieve consistent, low‑latency reads.
This article explores the challenges of handling massive simultaneous requests in distributed architectures and presents practical solutions such as load balancing, distributed caching, asynchronous processing, and sharding, illustrated with case studies from major e‑commerce and social platforms.
In its 2024 year‑end review, vivo Internet Technology published 44 technical articles, delivered 19 presentations on cloud‑native, AI, security and more, joined major open‑source foundations such as Linux, CNCF and CCF, and grew a community of over 70,000 technical professionals.
The article explains why multi‑active (active‑active) architecture is essential for modern enterprises, outlines its evolution from single‑server setups, details core principles like redundancy and data synchronization, compares common deployment patterns, examines industry use cases, and discusses challenges and mitigation strategies.
This article examines seven typical challenges that arise after implementing database sharding—such as global ID conflicts, cross‑shard queries, distributed transactions, shard‑key design, data migration, pagination, and operational overhead—and provides practical solutions and code examples to address each issue.
An in‑depth guide explains the CAP theorem’s three pillars—Consistency, Availability, Partition Tolerance—illustrates why only two can be achieved simultaneously, and shows real‑world trade‑offs across e‑commerce, finance, and social platforms, while introducing the complementary BASE model for practical system design.
This article analyzes the architectural impact of cross‑city multi‑active deployments, focusing on data‑layer design, write latency, sharding strategies, replication topologies, and routing considerations to achieve high availability, performance, and scalability in large‑scale distributed systems.
This article explains how to build a highly available distributed e‑commerce system by using load‑balancing, redundant servers, rate‑limiting techniques, circuit‑breaker patterns, and graceful degradation methods, and provides concrete Spring Cloud and Java code examples for each strategy.
This article examines the challenges of building multi‑active distributed systems, focusing on the data layer’s role in high availability, write‑latency, sharding, isolation, replication strategies, and routing decisions, and provides concrete architectural patterns and practical guidelines for robust backend design.
This article distills the key design patterns behind distributed systems—covering replication, partitioning, consensus, and fault‑tolerance—by presenting each pattern’s problem statement, concrete solution, trade‑offs, and technical considerations, all illustrated with real‑world examples from projects like Kafka and Cassandra.
The article examines China’s 12306 railway ticketing platform, tracing its evolution from early Unix‑based reservation software to a massive, real‑time, three‑tier distributed system that handles billions of requests during peak travel periods, highlighting its architectural challenges, high‑concurrency solutions, and unique national centralization.
This article introduces the motivation, architecture, technology choices, and key implementation details of a lightweight, highly extensible distributed job scheduling framework built on gRPC, Protobuf, a custom name‑server, and a bespoke message‑queue, addressing limitations of existing solutions like Quartz, XXL‑Job, and PowerJob.
This article explains why cache consistency is critical for Meta, how the company measures and monitors consistency, the design of the Polaris system that detects and resolves stale cache entries, and provides a concrete Python‑style example illustrating the challenges and solutions.
The article provides a detailed, informal yet informative overview of the evolution, architecture, and massive scale challenges of China’s 12306 railway ticketing platform, tracing its roots from early Unix‑based systems to modern distributed backend solutions handling billions of requests during peak travel periods.
Xiaohongshu built a lock‑free, non‑disruptive data‑consistency verification tool that automatically selects optimal methods, handles heterogeneous sources and dynamic changes, performs full and incremental checks via chunked checksums or row‑by‑row comparison, quickly isolates mismatches, and supports automatic remediation, ensuring reliable migrations and sharding.
DBOS, a Database‑Oriented Operating System proposed by Matei Zaharia and Michael Stonebrake, builds the OS atop a distributed, ACID‑compliant database, storing all system and application state in tables, which simplifies scaling, ensures strong consistency, improves debugging, and reduces attack surface for cloud‑native workloads.
This comprehensive guide explains Kafka’s architecture, core APIs, topics and partitions, deployment steps, multi‑broker clustering, and practical use cases such as messaging, log aggregation, stream processing, and data import/export with Kafka Connect, providing a hands‑on tutorial for developers and engineers.
The article examines five common rate‑limiting algorithms—Fixed Window, Sliding Window, Sliding Log, Leaky Bucket, and Token Bucket—detailing their principles, pros and cons, and providing complete C++ implementations to help developers choose the best approach for controlling traffic bursts and ensuring system stability.
This article examines the root causes of message queue disorder in distributed systems, illustrates real‑world impacts such as data loss during migration, and presents concrete mitigation strategies including ordered messaging, pre‑processing checks, state‑machine handling, and monitoring to improve system reliability.
Aeron is an open‑source, low‑latency, high‑throughput messaging framework that leverages zero‑copy memory, shared‑memory IPC and UDP transport to deliver microsecond‑level latency for finance, gaming, and distributed systems, offering a simple API and powerful performance features.
This article explains Apache RocketMQ's core components—including producers, topics, queues, and consumer groups—covers synchronous RPC versus asynchronous messaging, compares point‑to‑point and publish‑subscribe transmission models, and highlights their suitable scenarios and trade‑offs.
This article provides a comprehensive overview of Kafka, covering its overall structure, key components such as brokers, producers, consumers, topics, partitions, replicas, leader‑follower mechanics, logical and physical storage models, producer and consumer workflows, configuration parameters, partition assignment strategies, rebalancing, log retention and compaction, indexing, zero‑copy transmission, and the reliability concepts that ensure data durability.
Establishing an RDMA connection requires exchanging key parameters such as LID, QP number, and memory keys, and this article systematically outlines the essential information, compares six exchange methods—from static configuration to distributed services—and evaluates their advantages, drawbacks, and suitable scenarios.
