This article explains why oversized Redis keys (BigKeys) cause data skew, network blockage, slow queries, and high CPU load, shows how to detect them with redis-cli and other tools, and provides practical strategies—including lazy deletion, key splitting, and preventive design—to mitigate their impact on production systems.
This article explains Spring Boot's auto‑configuration mechanism, covering how @EnableAutoConfiguration loads configuration classes, the role of @AutoConfigurationPackage and @Import, the processing of spring.factories and metadata files, and how the main application class is registered in the IoC container.
The article explains why multiple independent systems hurt user experience, reviews traditional session and cookie based authentication, discusses session sharing problems in clustered environments, and presents centralized Redis storage and CAS‑based single sign‑on solutions with code examples and a comparison to OAuth2.
This article explains what constitutes a Redis BigKey, why oversized keys degrade performance through data skew, network blocking, slow queries and CPU pressure, and provides practical detection methods, open‑source tooling, and mitigation techniques such as lazy‑free deletion, incremental scans, and key sharding.
This article introduces Redisson, a Java framework built on Redis for distributed systems, detailing its extensive features such as distributed objects, locks, rate limiters, and task scheduling, and provides step‑by‑step guidance on integrating Redisson’s distributed lock into Spring Boot applications with code examples.
This article explains why Redis, despite being described as single‑threaded, achieves extremely high performance by using a single thread for network I/O and command execution, avoiding multithreading overhead, and leveraging efficient in‑memory data structures together with an event‑driven multiplexing I/O model.
This article walks through a real‑world R2M (Redis‑like) cache alert, detailing the email notification, large‑key analysis, code inspection, root‑cause identification, and both immediate and long‑term solutions that reduced cache usage by over 97% and prevented future incidents.
This article compares delayed and scheduled tasks, analyzes several implementation approaches—including database polling with Quartz, JDK DelayQueue, Netty's HashedWheelTimer, Redis ZSET and key‑space notifications, and RabbitMQ delayed queues—provides code examples, and discusses the advantages and drawbacks of each method for handling order timeout scenarios in payment systems.
The article details a week‑long investigation of a sandbox environment where Spring Boot APIs became unresponsive due to Redis connection pool blocking, describing the use of system tools, JVM thread analysis, and code inspection to identify mis‑configured pool settings and recommending proper connection handling with Spring's RedisTemplate.
This article explains Redis' client‑server request model, introduces the pipeline technique, compares normal and pipelined requests, and provides Spring Boot code examples that demonstrate a three‑fold speed improvement when writing 100,000 keys.
This article provides a comprehensive overview of Redis memory management, detailing how maxmemory limits trigger various eviction policies, explaining the internal freeMemoryIfNeeded algorithm, and describing expiration mechanisms—including active and lazy deletion—and offering guidance on selecting the appropriate eviction strategy for different workloads.
This article examines a Redis 3.x cluster failure caused by a master‑slave switch, detailing how improper Jedis timeout and retry settings triggered a service avalanche, and provides step‑by‑step analysis of the incident, code paths, and recommended configuration adjustments to prevent recurrence.
Redis is exploring a disk‑backed tiered storage architecture, allowing infrequently used data to move from memory to flash and back, a move aimed at reducing costs, improving scalability, and expanding its popularity among developers and gaming applications.
This article explains why Redis cache penetration occurs, how malicious requests can overload databases, and presents two effective mitigation strategies—caching empty objects and employing Bloom filters—detailing their implementation, advantages, and drawbacks.
This article introduces a simplified Seckill (flash‑sale) system built with SpringBoot, detailing its overall architecture, key backend techniques such as distributed sessions, Redis caching, RabbitMQ asynchronous ordering, security measures, oversell prevention, rate limiting, and provides essential code snippets and deployment screenshots.
This article details the design and implementation of a Java-based Seckill (flash‑sale) platform built with SpringBoot, MySQL, Redis, RabbitMQ, and front‑end technologies, covering password hashing, distributed sessions, caching strategies, asynchronous order processing, oversell prevention, rate limiting, and provides code snippets and deployment screenshots.
This article analyzes the design of Vivo's push notification platform, detailing its high‑concurrency requirements, three‑region long‑connection deployment, traffic‑scheduling bypass layer, and layered storage disaster‑recovery solutions, while explaining the trade‑offs and performance metrics behind each architectural decision.
This tutorial walks through creating the directory structure, defining variables, writing task files, and executing an Ansible playbook to automate the installation, compilation, configuration, and startup of Redis on target hosts.
After encountering latency spikes in a service, the article walks through systematic troubleshooting steps—examining module performance, resource metrics, and network latency—followed by detailed Redis diagnostics using metrics, latency commands, and profiling tools, ultimately recommending scaling, rate limiting, and caching strategies to resolve the issue.
The article explains how concurrent database updates can cause Redis cache inconsistency, introduces the delayed double‑delete solution, details each step of the algorithm, provides full Spring Boot AOP implementation code, demonstrates verification with test cases, and shares the complete project repository.
This article explains how Redis can be used to implement distributed locks, outlines common pitfalls such as non‑atomic operations, lock expiration, incorrect unlocking, lack of re‑entrancy and waiting mechanisms, and presents Lua scripts, Java examples, and cluster‑level considerations to mitigate these issues.
This article provides a comprehensive overview of Redis, covering its common application scenarios, detailed comparisons with Memcached, internal data structures, implementation details, and practical usage patterns such as caching, leaderboards, counters, and real‑time analytics for modern backend systems.
A load test revealed Redis latency soaring to 1.2 seconds, and a systematic investigation traced the root cause to mis‑configured JedisPool parameters, leading to excessive connection wait times and churn, which were fixed by aligning pool settings and enabling proper eviction, dramatically improving latency.
The article examines various delayed‑task solutions for order timeout handling in Java, including database polling with Quartz, JDK DelayQueue, Netty's HashedWheelTimer, Redis sorted‑set and key‑space notifications, and RabbitMQ delayed queues, analyzing their implementation steps, advantages, and drawbacks.
This article walks through practical methods for troubleshooting slow service alerts, diagnosing Redis performance bottlenecks, and reproducing issues with local demos and load simulations, offering concrete metrics, command‑line checks, and mitigation strategies such as scaling, rate‑limiting, and pipeline optimization.
The article recounts a developer's painful experience with un‑preheated Redis cache that caused severe latency spikes, then outlines practical cache warm‑up techniques such as gray‑release traffic, database scanning, and ETL‑driven data pipelines to prevent performance degradation and cache snowball effects.
This article explains the fundamentals of finite state machines, demonstrates how to model order lifecycle states and transitions in Java using Spring StateMachine, and provides detailed code examples for persistence, event handling, and advanced error‑handling techniques such as AOP and Redis storage.
This article introduces Redisson, a high‑performance Java Redis client built on Netty, explains its key advantages, and provides a detailed walkthrough of the RedissonLock implementation—including tryLock, blocking lock, unlock logic, associated Lua scripts, and the automatic watchdog renewal mechanism.
The article details how a Dubbo thread‑pool exhaustion incident was traced to a deadlock in Redis Cluster pipeline usage, caused by Jedis pools lacking a borrow timeout, which let threads block indefinitely while holding cross‑node connections, and recommends configuring maxWaitMillis or enlarging the pool to prevent recurrence.
This article explains how Redis uses the maxmemory setting to trigger memory eviction, details the various eviction policies (including LRU and LFU), shows how to query and modify these settings with config commands, and briefly mentions promotional offers for a ChatGPT community.
This tutorial demonstrates how to use Redis' GEO data structure together with Docker, RedisInsight, and a NestJS backend to store location data, perform distance calculations and radius searches, and finally display nearby points on a web map using AMap and Axios.
The article details how a Go service’s 300‑second Redis call timeout was traced to a gateway’s full‑NAT session‑table loss, and explains how targeted retries, proper timeout settings, and rate‑limiting can prevent similar cascading failures in distributed systems.
This article analyzes a MongoDB replication failure caused by missing oplog entries, compares logical initialization repair methods with Redis replication, and provides practical steps—including oplog size adjustment and snapshot techniques—to restore synchronization and prevent similar issues in production environments.
This guide explains how to claim Alibaba Cloud's free ECS credits, use them to spin up multiple machines for hands‑on Redis cluster experiments, and outlines a step‑by‑step learning path from basic Nginx setups to advanced high‑availability and multi‑service architectures.
This article explains key PHP performance optimization strategies—including database query tuning, efficient coding practices, and various caching methods such as Redis and file‑based page caching—providing concrete code examples to improve response time and system stability.
This article explains the fundamentals of finite‑state machines, introduces Spring Statemachine, demonstrates how to model an order lifecycle, configure persistence with in‑memory and Redis stores, and provides complete Java code for enums, configuration, services, controllers, listeners, testing, and exception‑handling improvements.
This article explains why rate limiting is essential for high‑traffic Java services, compares common strategies such as Hystrix, Sentinel, token‑bucket algorithms, and Redis‑based counters, and provides concrete Spring‑Boot code examples for implementing both local and distributed throttling.
This article demonstrates how to implement a captcha‑based login mechanism in a Spring Boot application with a front‑end/back‑end separation, detailing the traditional session‑based approach, the new Redis‑backed token solution, and providing complete code examples for configuration, service, controller, and data objects.
This article explores five common Redis applications—caching, session storage, distributed locking, rate limiting, and leaderboards—explaining how each leverages Redis’s in‑memory speed, atomic commands, and data structures to improve performance, scalability, and reliability of modern web services.
This article explains how to build a distributed task scheduling and dispatch system for PHP microservices by leveraging Redis and RabbitMQ, covering queue creation, node subscription, and providing complete code examples for both tools.
This article explains JWT payload claims, lists standard and custom claims, shows how to generate a token with expiration in Java, and compares single‑token and double‑token renewal strategies—including OAuth 2.0 approaches and Redis‑based storage—to manage token expiration securely.
This article walks through a real‑world e‑commerce scenario where billions of daily browsing events generate over 100K TPS writes, evaluates storage options on reliability, cost, read/write performance and implementation difficulty, and ultimately recommends Tair after detailed analysis of List, Sorted‑Set and Hash structures, code examples, and concurrency controls.
When a Redis‑backed service suddenly experiences high response times, this guide walks through systematic troubleshooting steps—checking server resources, network latency, Redis metrics, slow‑log, memory fragmentation, big keys, and hot keys—culminating in practical solutions such as pipelining, read/write splitting, and cache layering.
The article outlines a systematic three‑step workflow—general service diagnostics, Redis‑specific checks, and reproducible load testing—to pinpoint a hot‑key‑driven CPU bottleneck, then evaluates mitigation options such as read‑write separation, pipelining, and an application‑level cache, ultimately showing the cache’s effectiveness in cutting latency and CPU usage.
This article explains Redis’s five core data object types—strings, lists, hashes, sets, and sorted sets—detailing their encoding schemes, underlying memory structures such as SDS, ziplist, linkedlist, hashtable, and skiplist, and how Redis optimizes storage and access performance.
This guide walks through installing MySQL in Docker, configuring master‑slave replication, verifying synchronization, deploying a Canal server, and integrating it with a Spring Boot application to automatically push database changes into Redis.
This article explains the concept of distributed locks for ensuring data consistency in clustered environments, outlines common implementation approaches, and provides a comprehensive guide to using Redisson in Java—including Maven setup, YAML configuration, core source‑code analysis, Lua scripts for lock and unlock operations, and practical test cases.
This article provides a comprehensive technical walkthrough of Redis, covering its core concepts, data structures, performance tricks, caching pitfalls, persistence options, high‑availability architectures, distributed locking mechanisms, and consistency strategies, all illustrated with concrete examples and code snippets.
This article details the design and implementation of a custom, high‑throughput data migration framework that handles petabyte‑scale transaction data, supports heterogeneous source/target schemas, ensures zero‑downtime operation, and provides robust scheduling, checkpointing, and fault‑tolerance mechanisms.
The article explains how a meeting control system tackled severe storage pressure from high concurrent traffic by introducing a proxy layer, multi‑active disaster‑recovery, identity‑based data isolation, dynamic‑static key separation, multi‑level caching, overload protection, sharding with dual‑write migration, and extensive monitoring to meet 100k QPS and ensure reliability.
This article explains how to design a practical feed‑flow system for enterprises, covering core concepts, feed types, initialization, push‑pull versus pure push strategies, and provides key Java code snippets that illustrate Redis‑based storage and update mechanisms.
This article introduces Redis as a high‑performance in‑memory NoSQL database, explains its rich data structures, core design that makes it fast, key advantages, common use cases such as caching and messaging, and provides step‑by‑step installation and basic command examples.
This article introduces Redis as an open‑source, high‑performance in‑memory key‑value store, explains its rich data structures, underlying implementations, performance advantages, common use cases such as caching and messaging, and provides step‑by‑step installation and basic command examples for Ubuntu systems.
BigKey and HotKey issues in Redis clusters arise when oversized keys block processing or a single key receives excessive requests, causing timeouts, memory overflow, shard collapse, and performance degradation, but can be detected during testing using Redis commands, visual clients, and open‑source analysis tools.
This article investigates why a Spring Boot application using JedisPool experiences high connection‑acquisition latency, analyzes the Evictor logic and mis‑configured pool parameters, and presents a custom configuration solution that stabilizes the pool and eliminates repeated connection creation and destruction.
This article explains why public APIs need protection, outlines anti‑tampering and anti‑replay strategies using timestamps and nonces, and provides complete SpringBoot code—including request signing, filter implementation, and Redis utilities—to safeguard API calls from manipulation and replay attacks.
A developer recounts a painful production incident caused by an un‑preheated Redis cache, explains why cache warm‑up is essential for high‑traffic services, and outlines practical techniques such as gray releases, database scanning, and ETL pipelines to safely preheat caches.
This article explains why using Redis List for a message queue is limited, introduces Redis Stream as a purpose‑built MQ with consumer groups, ACKs, and persistence, and dives into its internal Radix‑Tree and listpack structures, command usage, and memory‑saving techniques.
This article explores comprehensive strategies for handling hot‑key bottlenecks in high‑traffic flash‑sale scenarios, covering DB, Redis, sharding, local cache, failure handling, and scaling techniques across various QPS ranges to ensure reliable inventory control and user experience.
The Aikexing Open Source Community weekly newsletter shares curated database articles, technical insights on MySQL, OceanBase, and Redis, announces SQLE 2.2309.0‑pre2 release with Feishu integration, recaps recent events like QCon Beijing, and promotes upcoming meetups and open‑source projects.
This article introduces Redis as a high‑performance in‑memory key‑value store, explains its core features, data types, caching usage in Spring Boot, and discusses common cache problems such as consistency, avalanche, penetration, and breakdown along with mitigation strategies, plus details on persistence, replication, and Sentinel.
This guide explains how to combine local and remote caches using Alibaba's JetCache in a Spring Boot project, covering dependency setup, configuration files, annotation‑based usage, advanced API methods, testing procedures, and common troubleshooting tips for a robust multi‑level caching solution.
This article explains how distributed locks solve data‑consistency problems in clustered environments, introduces Redisson as a Redis‑based locking library, provides Maven and YAML configuration, shows Java code for Redisson setup and test cases, and analyses the underlying Lua scripts and source‑code mechanisms.
Redis is a high-performance, open-source in-memory key-value database offering rich data structures, persistence options, and advanced features like replication, clustering, and pub/sub, making it ideal for caching, counters, message queues, leaderboards, and session storage in demanding, high-concurrency applications.
This article explains how Redis 7.0.11’s multithreading mode is enabled through two configuration options, describes when the mode is activated or deactivated based on client write‑backlog, and outlines the read and write processing flow in multithreaded and single‑threaded stages.
This article explains how to use Redis BitMap to build an efficient sign‑in feature and continuous‑sign‑in statistics in a Spring Boot microservice, covering basic BitMap commands, integration steps, core source code, and a cache‑penetration solution using BitMap hashing.
This guide demonstrates how to integrate Spring Boot 2 with OAuth2 for unified authentication, configure a Redis-backed token store, implement a resource server with custom security settings, and test protected endpoints, providing complete code snippets and configuration details.
This article introduces Redis as an open‑source in‑memory key‑value store, explains its data‑structure server nature, outlines common deployment options—including single instance, high‑availability, Sentinel, and Cluster—describes replication mechanisms, and details persistence models such as RDB, AOF, and hybrid approaches.
This article examines data consistency between Redis cache and MySQL database, explains common cache execution strategies such as Cache‑Aside, Read‑Through, Write‑Through, and Write‑Behind, analyzes four update sequences for consistency risks, and proposes solutions like delayed double‑delete, transactional guarantees, retry mechanisms, and binlog‑based cache invalidation.
This article examines the challenges of scaling inventory pre‑allocation in fast‑growing logistics platforms, outlines architectural principles for a lightweight, Redis‑driven solution that replaces MySQL bottlenecks, details data structures, consistency mechanisms, and performance results, and provides a roadmap for future capacity growth.
This tutorial walks through creating a full‑featured OAuth2 authorization server using Spring Boot 2.4.12, storing tokens in Redis, defining client and user entities in MySQL, configuring grant types, and testing the authorization, password, client‑credentials, and implicit flows.
This article explains how to leverage Redis Set, Sorted Set, Bitmap, and HyperLogLog data structures for various statistical scenarios such as user sign‑in tracking, friend recommendations, comment ranking, and UV counting, while addressing performance and memory considerations.
This article introduces Alibaba's JetCache Java caching framework, explains how to combine local and Redis remote caches for multi‑level caching, provides Maven dependencies, configuration examples, three usage patterns (AOP, API, advanced API), testing steps, and common troubleshooting tips for Spring Boot projects.
This comprehensive guide explains Redis fundamentals, its rich data types, differences from Memcached, thread model, persistence mechanisms (AOF, RDB, hybrid), memory eviction policies, clustering for high availability, cache design patterns, distributed locking, Redlock algorithm, and practical techniques for identifying and safely deleting big keys.
This article explains how to create Redis‑based distributed locks, discusses common pitfalls such as deadlocks and accidental deletions, and provides practical solutions including atomic expiration commands, Lua scripts, and a complete Redisson Java example for acquiring and releasing locks safely.
This article explains how to prevent duplicate API calls and achieve idempotency in Spring Boot 3.0.5 by using unique tokens, timestamps, or Spring AOP, and provides complete code examples for custom annotations, AOP aspects, interceptors, and Redis‑based token management.
During a Redis 3.x cluster master‑slave failover, the default Jedis connection timeout of two seconds combined with six automatic retries caused each request’s Redis calls to accumulate up to sixty seconds of latency, triggering Nginx timeouts and a service‑avalanche, which was resolved by lowering timeout and retry settings.
This article examines three practical approaches for preventing external exposure of specific APIs—service isolation, gateway‑based Redis whitelist, and gateway‑plus‑AOP—evaluates their trade‑offs, and provides step‑by‑step Java code to implement the preferred AOP solution in a Spring Cloud environment.
This article presents a full set of Java backend interview questions—ranging from self‑introduction and challenging projects to abstract classes, HashMap internals, B+‑tree characteristics, MySQL vs. skip‑list indexing, Redis skip‑list usage, large‑table optimization, join queries, JVM memory model, and Survivor space—along with detailed English explanations and sample code.
Redis 7.2, the first Unified Redis Release, introduces extensive AI support, vector database capabilities, scalable search, server‑side Triggers and Functions, enhanced geospatial queries, performance‑boosted sorted sets, and the Redis Data Integration tool, while expanding client and protocol compatibility.
This guide explains why API rate limiting is essential, outlines common algorithms, and walks through three practical implementations in Spring Boot 3—using Guava, Spring Cloud Gateway with RedisRateLimiter, and a custom annotation‑based solution with Redis backing.
This article explains how Redis handles memory exhaustion by distinguishing expiration and eviction policies, detailing the maxmemory setting, enumerating all eviction strategies—including LRU and LFU algorithms—and showing how to view and modify these policies for optimal cache performance.
This article analyzes the high‑concurrency contract‑query workload of JD Logistics, examines call sources, query dimensions and volume patterns, and proposes a three‑layer protection architecture—Bloom filter, Redis cache, and database fallback—along with strategies for cache penetration, breakdown, and avalanche mitigation.
Redis 7.2, the first Unified Redis Release, introduces AI‑ready vector indexing, hybrid semantic search, scalable RAG support, server‑side Triggers and Functions, enhanced geospatial queries, and a preview of high‑performance searchable indexes, while expanding client library support and integrating Redis Data Integration for seamless enterprise data pipelines.
This report details the design, deployment, and extensive performance testing of a Miop protocol‑based push service, describing the test environment, methodology, multi‑stage load tests up to one million concurrent connections, observed metrics, encountered issues, and recommendations for ensuring stability and scalability.
This article explains how to leverage Redis data structures such as Set, Sorted Set, Bitmap, and HyperLogLog to perform aggregation, sorted, binary‑state, and cardinality statistics efficiently in large‑scale applications, while addressing performance considerations and practical implementation details.
This article explains how to achieve idempotent order creation and updates in backend services by using unique request identifiers, database unique constraints, Redis flags, and optimistic locking with version columns, while also addressing the ABA problem with practical code examples and diagrams.
This article explains what Redis bigkeys are, their impact on performance and memory, how they are generated, methods to detect and analyze them—including built‑in commands, SCAN, memory usage, and RDB file inspection—and practical steps to mitigate their effects.
To improve stability and reduce costs during high‑traffic events, we replaced the Zookeeper‑dependent TBSchedule framework with a lightweight, Redis‑based distributed scheduler that decentralizes task execution, uses thread pools instead of timers, and supports dynamic scaling and seamless degradation for reliable order processing.
This article explains PHP data caching techniques—including memory, file, and database caches—provides practical code samples, and outlines key index design principles such as uniqueness, expiration, hotspot optimization, efficient updates, and hierarchical caching to improve performance.
This article explains the concept of idempotency, identifies naturally idempotent HTTP methods, discusses why idempotency is essential for retries, async callbacks, and message queues, and provides a complete Spring Boot implementation using a custom @Idempotent annotation, AOP, and Redis for token storage.
This article explains the common reasons why Redis performance degrades—such as network latency, high‑complexity commands, big keys, concentrated expirations, memory limits, fork overhead, huge pages, AOF settings, CPU binding, swap usage, and memory fragmentation—and provides detailed optimization and troubleshooting steps to restore low latency.
The article explains that Redis achieves exceptional performance through four main factors—its in‑memory storage, optimized data structures, a single‑threaded architecture, and non‑blocking I/O—detailing how each contributes to speed and efficiency.
The article explains why using the KEYS command on a large Redis dataset can block the server, introduces the SCAN command as a non‑blocking alternative with cursor‑based iteration, and provides usage examples and best‑practice tips for safely listing prefixed keys.
This article explains the concept of distributed global unique identifiers, outlines four essential characteristics of such IDs, and provides a detailed comparison of five generation schemes—UUID, database‑generated IDs, Redis, Zookeeper, and Snowflake—highlighting their advantages, drawbacks, and suitable use cases.
This article details the end‑to‑end high‑availability architecture—including dual‑center Elasticsearch clusters, Redis caching with distributed locks, and a dual‑center MySQL partitioned setup—that enables a membership platform serving billions of users to sustain massive traffic while ensuring data consistency and rapid recovery.
This article provides a detailed backend interview cheat‑sheet covering Redis data structures and performance issues, MySQL indexing and transaction principles, operating‑system process and thread concepts, TCP/UDP networking differences, and common Java garbage‑collection algorithms, all illustrated with examples and code snippets.
This article explains the importance of rate limiting in microservice systems, compares various governance frameworks such as Dubbo and Spring Cloud, and provides detailed implementations using Guava, Sentinel, Redis+Lua scripts, and a custom Spring Boot starter, complete with code examples and deployment steps.
This article walks through the importance of rate limiting in microservice architectures, compares Dubbo, Spring Cloud, and gateway approaches, explains token‑bucket, leaky‑bucket and sliding‑window algorithms, and provides step‑by‑step AOP implementations using Guava, Sentinel, and Redis with full code samples.
This article explains the Redis Sorted Set data type, its underlying storage mechanisms (listpack and skiplist + dict), the internal structures and algorithms, and demonstrates how to build a real‑time game leaderboard using ZADD, ZRANGE and ZREVRANK commands.
