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distributed cache

88 articles · Page 1 of 1
FunTester
FunTester
Aug 2, 2026 · Backend Development

Designing Effective API Caching: Strategies, Layers, and Best Practices

This guide explains API caching fundamentals, cache hit vs miss, multi‑layer cache hierarchies, common strategies such as cache‑aside and stale‑while‑revalidate, TTL tuning, event‑driven invalidation, avalanche prevention, HTTP cache directives, and key monitoring metrics to help engineers build resilient, high‑performance services.

API cachingCache invalidationCache strategies
0 likes · 10 min read
Designing Effective API Caching: Strategies, Layers, and Best Practices
Code Farming
Code Farming
Jul 30, 2026 · Backend Development

Can Your System Survive a Sudden 500K Live Viewers? 4 Proven Traffic‑Splitting Techniques

When a live broadcast suddenly attracts 500,000 viewers, the system faces 100,000 QPS likes and rapid reward transactions; this article breaks down a battle‑tested traffic‑splitting architecture—room‑based sharding, queue buffering, multi‑layer write caching, and consistent‑hash sharding—showing how each component controls load, ensures consistency, and enables seamless scaling.

System Designconsistent hashingdistributed cache
0 likes · 6 min read
Can Your System Survive a Sudden 500K Live Viewers? 4 Proven Traffic‑Splitting Techniques
liandk
liandk
Jul 24, 2026 · Fundamentals

Why Every Project Needs Caching – Master Local and Distributed Cache Basics

The article explains the fundamental purpose of caching—placing frequently accessed data in faster storage—to dramatically reduce database load, compares local memory caches with distributed solutions like Redis, outlines their pros, cons, suitable scenarios, and presents a two‑level cache pattern plus common pitfalls such as cache penetration, breakdown, and avalanche.

Rediscachingdistributed cache
0 likes · 6 min read
Why Every Project Needs Caching – Master Local and Distributed Cache Basics
Ray's Galactic Tech
Ray's Galactic Tech
Jul 21, 2026 · Backend Development

14 Painful Spring Boot Cache Pitfalls and How to Build a High‑Availability Architecture

This article walks through 14 real‑world failure scenarios of Spring Boot distributed caching, explains why high cache hit rates are misleading, and provides concrete analysis, code samples, and step‑by‑step recommendations for designing a resilient cache layer that isolates faults, handles hot keys, and ensures data consistency across Redis, local caches, and databases.

Cache invalidationHigh AvailabilityKubernetes
0 likes · 37 min read
14 Painful Spring Boot Cache Pitfalls and How to Build a High‑Availability Architecture
Java Tech Workshop
Java Tech Workshop
May 26, 2026 · Backend Development

How to Implement RabbitMQ Fanout Broadcast in Spring Boot

This guide explains the fanout (publish/subscribe) pattern in RabbitMQ, compares it with other exchange types, clarifies common misconceptions, and provides a step‑by‑step Spring Boot implementation—including configuration, producer, multiple consumers, testing, and best‑practice recommendations.

Message BroadcastingPublish-SubscribeSpring Boot
0 likes · 10 min read
How to Implement RabbitMQ Fanout Broadcast in Spring Boot
DataFunSummit
DataFunSummit
May 22, 2026 · Big Data

How OPPO Accelerates Multimodal Data & AI Fusion with Gravitino and Curvine

OPPO tackles explosive multimodal data growth by unifying metadata with Gravitino and boosting I/O performance using the open‑source Curvine cache, delivering a four‑layer data‑lake architecture that resolves data islands, metadata chaos, and bandwidth bottlenecks while achieving near‑commercial query speeds.

Cloud StorageCurvineGravitino
0 likes · 11 min read
How OPPO Accelerates Multimodal Data & AI Fusion with Gravitino and Curvine
DataFunSummit
DataFunSummit
Apr 19, 2026 · Big Data

How OPPO Built a Multi‑Modal Data Lake with Gravitino and Curvine

OPPO’s data‑lake team, led by David, detailed their transition from Hive‑Spark to a unified multi‑modal lake, leveraging Gravitino for cross‑engine metadata management and the open‑source Curvine cache to eliminate data silos, boost I/O performance, and support massive image, recommendation, and AI‑Agent workloads.

Big DataData LakeMultimodal
0 likes · 11 min read
How OPPO Built a Multi‑Modal Data Lake with Gravitino and Curvine
Code Wrench
Code Wrench
Mar 1, 2026 · Backend Development

Building a High‑Performance Go Distributed Cache: GoMemcache from Scratch

This article walks through designing and implementing GoMemcache, a lightweight Go‑based distributed cache, covering use‑case selection, concurrency lock optimization, consistent hashing, production‑grade code, and practical deployment best practices for ultra‑low latency services.

Gobackend developmentconcurrency
0 likes · 12 min read
Building a High‑Performance Go Distributed Cache: GoMemcache from Scratch
JD Tech
JD Tech
Nov 11, 2025 · Databases

How JIMDB’s Big‑Hot Key Strategy Boosts Cache Performance by 80%

JIMDB, a Redis‑based distributed cache, introduces the Big‑Hot Key concept and a multi‑layer proactive governance framework that dynamically identifies resource‑intensive keys, automatically mitigates them, and delivers up to an 80% performance gain while dramatically improving system stability.

Big-Hot KeyJimdbRedis
0 likes · 39 min read
How JIMDB’s Big‑Hot Key Strategy Boosts Cache Performance by 80%
JakartaEE China Community
JakartaEE China Community
Sep 2, 2025 · Backend Development

Choosing the Right Cache Solution: Key Criteria and Trade‑offs

This article explains why caching is a performance trade‑off, outlines essential cache features such as size limits, eviction policies, TTL, configuration, integration APIs, and distributed versus local modes, and provides a comprehensive checklist for evaluating cache providers.

JCacheSpring CacheTTL
0 likes · 12 min read
Choosing the Right Cache Solution: Key Criteria and Trade‑offs
Su San Talks Tech
Su San Talks Tech
Jun 28, 2025 · Backend Development

Essential Microservice Architecture Components: From Nginx to Distributed Storage

This article outlines the key building blocks of a microservice architecture—including Nginx as the traffic entry, Spring Cloud Gateway, service registries, Redis caching, MySQL persistence, Elasticsearch, message queues, ELK logging, distributed schedulers, and object storage—explaining their roles, deployment patterns, and common technology choices.

Backend ArchitectureNginxdistributed cache
0 likes · 10 min read
Essential Microservice Architecture Components: From Nginx to Distributed Storage
DataFunTalk
DataFunTalk
Jun 4, 2025 · Artificial Intelligence

Coupang’s Distributed Cache Architecture Accelerates AI/ML Model Training

Coupang’s AI platform replaces costly data‑copy steps with a distributed cache that automatically pulls data from a central lake, boosts GPU utilization across regions, cuts storage and operational expenses, and speeds up model training by up to 40% while simplifying deployment via Kubernetes.

AIData LakeGPU
0 likes · 9 min read
Coupang’s Distributed Cache Architecture Accelerates AI/ML Model Training
IT Architects Alliance
IT Architects Alliance
Apr 2, 2025 · Backend Development

Designing High‑Concurrency Backend Architecture for E‑commerce Platforms

The article explains how to design a scalable, highly available backend system capable of handling millions of requests per second by defining key performance metrics, estimating traffic with the 2/8 rule, and applying architectural patterns such as load‑balanced clusters, vertical service splitting, distributed caching, and database master‑slave replication, illustrated with a Taobao case study.

Backend ArchitectureDatabase ReplicationLoad Balancing
0 likes · 14 min read
Designing High‑Concurrency Backend Architecture for E‑commerce Platforms
Lobster Programming
Lobster Programming
Jan 20, 2025 · Backend Development

Boost High‑Concurrency Performance: When to Use Redis vs. Local Cache

This article explains why traditional relational databases falter under high‑concurrency loads, introduces caching as a solution, compares Redis distributed caching with local in‑process caching, and shows how combining them into a multi‑level cache can dramatically improve performance and reliability.

Rediscachingdistributed cache
0 likes · 5 min read
Boost High‑Concurrency Performance: When to Use Redis vs. Local Cache
Programmer XiaoFu
Programmer XiaoFu
Nov 16, 2024 · Backend Development

How Leading Companies Implement Distributed Caching – Lessons and Pitfalls

The article examines the benefits and hidden risks of using distributed caches, analyzes real‑world failure cases from Facebook, Google and AWS, and provides detailed strategies to mitigate availability and consistency problems through careful refresh policies, incremental updates, and compensation mechanisms.

Cache ConsistencyCache Designavailability risk
0 likes · 19 min read
How Leading Companies Implement Distributed Caching – Lessons and Pitfalls
Alibaba Cloud Native
Alibaba Cloud Native
Sep 27, 2024 · Cloud Native

How SAE’s Cloud‑Native Event Center Tackles Data Explosion and Real‑Time Alerts

The article explains the design and implementation of the Serverless Application Engine (SAE) Event Center, highlighting its cloud‑native architecture, the distinction from traditional monitoring, challenges like data explosion and full GC, and the distributed‑cache solution that enables efficient real‑time event aggregation, notification, and future AI‑driven diagnostics.

Data ExplosionMonitoringSAE
0 likes · 10 min read
How SAE’s Cloud‑Native Event Center Tackles Data Explosion and Real‑Time Alerts
Practical DevOps Architecture
Practical DevOps Architecture
Sep 5, 2024 · Backend Development

Common Cache Issues and Their Solutions

This article explains four typical cache problems—penetration, avalanche, breakdown, and distributed cache efficiency—describing their causes and offering practical mitigation strategies such as top‑level filtering, Bloom filters, staggered expirations, null caching, and locking mechanisms.

Cache AvalancheCache BreakdownCache Penetration
0 likes · 3 min read
Common Cache Issues and Their Solutions
FunTester
FunTester
Jul 17, 2024 · Backend Development

Mastering Backend Caching: Strategies, Types, and Common Pitfalls

This article provides a comprehensive guide to backend caching, covering fundamental concepts, usage scenarios, read‑through and cache‑aside strategies, local and distributed cache types, popular services like Redis and Memcached, eviction algorithms such as FIFO, LRU, LFU, and common issues like consistency, avalanche, penetration, and stampede, along with practical mitigation techniques.

Cache EvictionCache strategiesbackend development
0 likes · 14 min read
Mastering Backend Caching: Strategies, Types, and Common Pitfalls
Tencent Cloud Developer
Tencent Cloud Developer
Jul 2, 2024 · Backend Development

Mastering Backend Caching: Strategies, Types, Eviction & Common Pitfalls

An in‑depth guide to backend caching covers read‑through and cache‑aside strategies, local versus distributed caches (including Redis and Memcached), eviction algorithms such as FIFO, LRU and LFU, and tackles consistency, avalanche, penetration and breakdown issues with practical mitigation techniques.

Cache strategiesMemcachedRedis
0 likes · 12 min read
Mastering Backend Caching: Strategies, Types, Eviction & Common Pitfalls
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Jun 5, 2024 · Backend Development

Design and Implementation of a Multi‑Level Cache Component Library in Go

This article explains the motivation, design principles, class diagram, and core Go code for a multi‑level cache library that supports in‑memory and distributed caches (Redis, Memcached) using adapter, builder, and responsibility‑chain patterns, and discusses cache‑database consistency strategies.

Design PatternsRedisadapter pattern
0 likes · 21 min read
Design and Implementation of a Multi‑Level Cache Component Library in Go
Mike Chen's Internet Architecture
Mike Chen's Internet Architecture
Apr 17, 2024 · Backend Development

Mastering High Concurrency: Boost Your Backend Performance

This article explains what high concurrency is, why it matters for large‑scale systems, and presents practical techniques such as distributed caching, load balancing, database optimization, traffic shaping, and distributed architecture to dramatically improve a backend's ability to handle massive simultaneous requests.

Backend PerformanceLoad Balancingdatabase optimization
0 likes · 9 min read
Mastering High Concurrency: Boost Your Backend Performance
IT Architects Alliance
IT Architects Alliance
Jan 9, 2024 · Backend Development

Design Principles and Best Practices for Distributed Cache Architecture

This article explains the core design goals, sharding strategies, replication models, communication protocols, cache selection, and monitoring techniques needed to build high‑performance, highly available, and scalable distributed cache systems for large‑scale internet applications.

Backend ArchitectureMemcachedRedis
0 likes · 5 min read
Design Principles and Best Practices for Distributed Cache Architecture
DataFunSummit
DataFunSummit
Dec 23, 2023 · Databases

REDTao: A Scalable Graph Storage System for Trillion‑Scale Social Networks at Xiaohongshu

This article presents REDTao, Xiaohongshu's self‑built graph storage solution that unifies graph queries, reduces development duplication, and delivers low‑latency, high‑availability access to a trillion‑scale social graph through a three‑layer architecture, distributed cache, and cloud‑native deployment.

Cloud NativeGraph DatabaseHigh Availability
0 likes · 15 min read
REDTao: A Scalable Graph Storage System for Trillion‑Scale Social Networks at Xiaohongshu
Sohu Tech Products
Sohu Tech Products
Dec 13, 2023 · Big Data

Alluxio Edge: Edge Caching Solution for Trino and PrestoDB

Alluxio Edge is a library that runs inside Trino or PrestoDB workers, using local SSD or memory to cache data from cloud storage, which restores data locality, cuts storage egress, and delivers up to ten‑fold IO speed gains and up to ten‑fold query performance improvements in real deployments.

Alluxio EdgeBig DataEdge computing
0 likes · 14 min read
Alluxio Edge: Edge Caching Solution for Trino and PrestoDB
Programmer DD
Programmer DD
Dec 8, 2023 · Backend Development

Mastering Distributed Caching with Redis: Strategies, Types, and Pitfalls

Redis serves as a powerful in‑memory key‑value store for distributed caching, offering various data structures, persistence options, deployment modes, eviction policies, and update strategies, while addressing consistency challenges, cache miss scenarios, and failure modes such as penetration, breakdown, and avalanche.

Cache ConsistencyCache EvictionRedis
0 likes · 13 min read
Mastering Distributed Caching with Redis: Strategies, Types, and Pitfalls
JavaEdge
JavaEdge
Dec 6, 2023 · Backend Development

Choosing and Implementing Caching for Spring Boot Microservices

This article explains why caching is crucial for Spring Boot applications, examines its impact on microservice architectures, outlines criteria for selecting the right cache—usability, speed, availability, observability—and compares local, distributed, and hierarchical caches with practical strategies and code examples.

Spring Bootbackenddistributed cache
0 likes · 7 min read
Choosing and Implementing Caching for Spring Boot Microservices
Architect
Architect
Nov 26, 2023 · Databases

How REDtao Powers Xiaohongshu’s Trillion‑Edge Social Graph: Architecture, Performance, and Lessons

This article details the design and implementation of REDtao, a self‑built graph storage system for Xiaohongshu that replaces MySQL with a three‑layer architecture, distributed cache, cross‑cloud multi‑active support, and delivers trillion‑edge scale, 150 M QPS, 90% cache hit rate, and significant cost reductions.

Cloud NativeGraph DatabaseREDtao
0 likes · 21 min read
How REDtao Powers Xiaohongshu’s Trillion‑Edge Social Graph: Architecture, Performance, and Lessons
Ximalaya Technology Team
Ximalaya Technology Team
Jul 13, 2023 · Databases

Evolution of Ximalaya KV Storage and XCache Architecture

Ximalaya’s KV storage progressed from a simple Redis master‑slave setup to client‑side sharding, then adopted Codis clustering for elastic scaling, integrated Pika’s disk‑based store with cold‑hot separation, introduced KV‑blob separation, fast‑slow command pools, second‑level expansion, ehash fields, large‑key circuit breaking, multi‑active data‑center replication, and now targets cloud‑native deployment, advanced features, and AI‑driven operations.

CodisHigh AvailabilityKV storage
0 likes · 19 min read
Evolution of Ximalaya KV Storage and XCache Architecture
Selected Java Interview Questions
Selected Java Interview Questions
Jul 11, 2023 · Backend Development

Design and Implementation of a High‑Performance Distributed Cache with Redis and Caffeine for Spring Boot Services

This article outlines the design goals, architecture, and implementation details of a high‑performance distributed caching solution for Spring Boot applications, combining Redis as a first‑level cache with Caffeine as a second‑level cache, and provides configuration, usage examples, and future enhancement plans.

AOPCaffeineRedis
0 likes · 11 min read
Design and Implementation of a High‑Performance Distributed Cache with Redis and Caffeine for Spring Boot Services
Architect's Guide
Architect's Guide
Jul 7, 2023 · Artificial Intelligence

Evaluating GPT‑4’s Ability to Design and Implement a Distributed Cache System for Uber

An in‑depth case study shows how GPT‑4, demonstrated by former Google engineer Naman Bhalla, tackles a simulated Uber interview by generating software requirements, design specifications, Java code snippets, and JUnit tests for a distributed cache system, revealing both its strengths and current limitations.

AI codingGPT-4Software Design
0 likes · 11 min read
Evaluating GPT‑4’s Ability to Design and Implement a Distributed Cache System for Uber
DataFunTalk
DataFunTalk
May 25, 2023 · Artificial Intelligence

Optimizing Distributed Cache for Large-Scale Deep Learning Training with Alluxio and SiloD

This article examines the storage bottlenecks in large‑scale AI training, evaluates local‑disk and Alluxio‑based distributed caching strategies, proposes uniform cache eviction and replica‑aware global policies, and introduces the SiloD framework for coordinated compute‑storage scheduling to dramatically improve GPU utilization and overall cluster throughput.

AI trainingAlluxioCache Eviction
0 likes · 16 min read
Optimizing Distributed Cache for Large-Scale Deep Learning Training with Alluxio and SiloD
Sanyou's Java Diary
Sanyou's Java Diary
May 8, 2023 · Backend Development

Choosing the Right Cache: Local vs Distributed Strategies Explained

This article explores how caching accelerates high‑concurrency systems by reducing CPU and I/O load, compares local and distributed cache types, reviews Java cache implementations and frameworks, and presents real‑world multi‑level cache designs and pitfalls to help you select the optimal solution.

cachingdistributed cachelocal cache
0 likes · 12 min read
Choosing the Right Cache: Local vs Distributed Strategies Explained
ITPUB
ITPUB
Jan 25, 2023 · Backend Development

Mastering Distributed Caching with Redis and Memcached in Spring Boot

This article explains the fundamentals, characteristics, and use‑cases of distributed caching, compares Memcached and Redis, and provides a step‑by‑step Spring Boot implementation with code samples, testing guidance, and solutions to common cache pitfalls such as hot keys, penetration, and avalanche.

Cache DesignRedisSpring Boot
0 likes · 20 min read
Mastering Distributed Caching with Redis and Memcached in Spring Boot
Java High-Performance Architecture
Java High-Performance Architecture
Dec 20, 2022 · Backend Development

Mastering Cache: Concepts, Types, and Best Practices for High‑Performance Systems

Cache stores frequently accessed hot data in memory to reduce database load, improving performance and handling high‑concurrency scenarios; this article explains cache fundamentals, why Redis is preferred, classifications such as local, distributed, and multi‑level caches, their advantages, drawbacks, and implementation tips.

distributed cacheperformance
0 likes · 8 min read
Mastering Cache: Concepts, Types, and Best Practices for High‑Performance Systems
Top Architect
Top Architect
Dec 14, 2022 · Backend Development

Cache Basics: Concepts, Types, Advantages, and Implementation Strategies

This article explains the fundamentals of caching, why caches (especially Redis) are essential for high‑performance and high‑concurrency scenarios, describes local, distributed, and multi‑level cache architectures, outlines their pros and cons, and provides practical implementation guidance.

Multi-Level CacheRedisdistributed cache
0 likes · 10 min read
Cache Basics: Concepts, Types, Advantages, and Implementation Strategies
IT Architects Alliance
IT Architects Alliance
Aug 21, 2022 · Backend Development

Consistent Hashing Algorithm: Principles, Java Implementation, and Optimizations for Distributed Cache Load Balancing

This article explains the fundamentals of consistent hashing, its application in load‑balancing distributed caches, analyzes common issues such as data skew and cache avalanche, introduces virtual nodes for uniform distribution, provides Java code examples, and compares it with Redis's HashSlot approach.

Algorithmconsistent hashingdistributed cache
0 likes · 20 min read
Consistent Hashing Algorithm: Principles, Java Implementation, and Optimizations for Distributed Cache Load Balancing
Architecture Digest
Architecture Digest
Jun 9, 2022 · Backend Development

Comprehensive Guide to Caching: Principles, Types, Strategies, and Best Practices

This article provides an in‑depth overview of caching, covering its definition, when to use it, core concepts, various cache types (client, server, CDN, reverse‑proxy, in‑process, distributed), eviction policies, multi‑level cache architectures, common pitfalls such as cache avalanche, penetration and breakdown, and practical mitigation techniques.

Cache Evictionbackendcaching
0 likes · 30 min read
Comprehensive Guide to Caching: Principles, Types, Strategies, and Best Practices
Zuoyebang Tech Team
Zuoyebang Tech Team
Apr 7, 2022 · Cloud Native

How Fluid Transforms Large‑Scale Data Retrieval on Kubernetes

This article explains how Zuoyebang redesigned its massive data retrieval platform by separating compute and storage with the Fluid project on Kubernetes, achieving minute‑level hundred‑TB distribution, elastic caching, and improved stability for real‑time educational services.

Compute-Storage SeparationData RetrievalFluid
0 likes · 8 min read
How Fluid Transforms Large‑Scale Data Retrieval on Kubernetes
Yanxuan Tech Team
Yanxuan Tech Team
Apr 7, 2022 · Backend Development

Mastering Server‑Side Caching: From Local to Distributed Multilevel Strategies

This article explains why caching is essential for reducing CPU and I/O pressure, outlines key cache attributes such as throughput and hit rate, compares popular local cache libraries, describes distributed cache options, and details the design, consistency, monitoring, and hot‑key handling of a transparent multilevel cache architecture.

Heliosconsistencydistributed cache
0 likes · 20 min read
Mastering Server‑Side Caching: From Local to Distributed Multilevel Strategies
NetEase Yanxuan Technology Product Team
NetEase Yanxuan Technology Product Team
Apr 6, 2022 · Backend Development

Server-Side Caching: Local, Distributed, and Multi-Level Cache Architecture Practices

Server‑side caching improves performance by trading space for time, using local caches like HashMap, Guava, Ehcache, and Caffeine, distributed caches such as Redis, and multi‑level architectures that combine in‑process, distributed, and database layers, while employing consistency patterns, monitoring, and hot‑key detection.

Cache ConsistencyCaffeineHot Key Detection
0 likes · 16 min read
Server-Side Caching: Local, Distributed, and Multi-Level Cache Architecture Practices
DataFunTalk
DataFunTalk
Jan 19, 2022 · Artificial Intelligence

Alluxio for AI and Machine Learning: Architecture, Optimizations, and Performance Evaluation

This article presents a comprehensive technical overview of Alluxio, covering its role as a distributed data orchestration layer for AI workloads, core features such as caching and unified namespace, performance challenges in large‑scale machine‑learning pipelines, and the extensive optimizations and testing performed at Tencent to achieve high throughput and scalability.

AIAlluxioCephFS
0 likes · 23 min read
Alluxio for AI and Machine Learning: Architecture, Optimizations, and Performance Evaluation
Code Ape Tech Column
Code Ape Tech Column
Aug 25, 2021 · Backend Development

Common Pitfalls and Best Practices of Distributed Caching with Redis and Memcached

This article examines the characteristics of Redis and Memcached as distributed cache solutions, outlines common design pitfalls such as consistency, cache penetration, breakdown, avalanche, and hot‑key issues, and provides practical strategies—including consistent hashing, binlog‑driven invalidation, message‑queue indexing, and lock mechanisms—to build reliable and high‑performance caching layers in backend systems.

Cache ConsistencyCache invalidationMemcached
0 likes · 18 min read
Common Pitfalls and Best Practices of Distributed Caching with Redis and Memcached
IT Architects Alliance
IT Architects Alliance
Aug 23, 2021 · Backend Development

Choosing the Right Distributed Cache: Redis Cluster Deep Dive

This article examines the landscape of cache systems, compares four major categories, evaluates popular distributed caches such as Redis, Memcached, Tair and EvCache, explains Redis Cluster architectures and sharding strategies, and outlines common cache pitfalls with practical mitigation techniques.

Cache ClusterRedisbackend
0 likes · 13 min read
Choosing the Right Distributed Cache: Redis Cluster Deep Dive
Top Architect
Top Architect
Aug 15, 2021 · Backend Development

Choosing and Implementing Distributed Cache Systems with Redis

This article reviews various cache system types, compares popular distributed caches such as Memcache, Tair, and Redis, explains Redis cluster high‑availability mechanisms, discusses sharding strategies, and outlines common cache problems and solutions, providing practical configuration examples for Java backend developers.

Cache strategiesClusterRedis
0 likes · 12 min read
Choosing and Implementing Distributed Cache Systems with Redis
Ctrip Technology
Ctrip Technology
Jun 24, 2021 · Backend Development

Design and Implementation of Distributed Cache with Eventual and Strong Consistency at Ctrip Finance

This article presents Ctrip Finance's design of a unified high‑availability Redis cache service, covering both eventual‑consistency and strong‑consistency scenarios, the overall architecture, data‑accuracy, completeness and availability mechanisms, lock handling, fault‑tolerant updates, and operational recovery strategies.

High AvailabilityMySQLRedis
0 likes · 26 min read
Design and Implementation of Distributed Cache with Eventual and Strong Consistency at Ctrip Finance
New Oriental Technology
New Oriental Technology
Jun 17, 2021 · Backend Development

Cache Basics, Types, Patterns, and Common Issues

This article explains why caching is used, distinguishes between local and distributed caches, compares popular Java cache libraries, describes Redis and Memcached differences, outlines the Cache‑Aside pattern, and discusses common cache problems such as inconsistency, penetration, breakdown, avalanche, hot‑key detection, and their mitigation strategies.

Redisdistributed cachejava
0 likes · 15 min read
Cache Basics, Types, Patterns, and Common Issues
Alibaba Cloud Developer
Alibaba Cloud Developer
Jun 9, 2021 · Backend Development

Mastering Cache Optimization: From Distributed to CPU Cache and Beyond

This article explores the fundamentals and advanced techniques of cache optimization, covering multi‑level caching, read/write performance gains, cache miss handling, consistency strategies, heap versus direct memory, CPU cache effects, false sharing, and practical mitigation patterns.

CPU cacheMemory Managementcaching
0 likes · 13 min read
Mastering Cache Optimization: From Distributed to CPU Cache and Beyond
DeWu Technology
DeWu Technology
May 14, 2021 · Backend Development

Local and Distributed Caching: Concepts and Implementations

In high‑traffic e‑commerce systems, caching—ranging from simple in‑JVM HashMap caches to Guava, Caffeine, and Redis distributed stores—reduces latency by applying eviction policies such as FIFO, LRU, LFU, or W‑TinyLFU, while employing consistency strategies like expiration, write‑through, and cache‑aside to mitigate breakdown, avalanche, and penetration issues.

CaffeineGuavaRedis
0 likes · 20 min read
Local and Distributed Caching: Concepts and Implementations
Alibaba Cloud Native
Alibaba Cloud Native
Mar 5, 2021 · Artificial Intelligence

How Alluxio Supercharges Cloud Deep Learning: Benchmarks, Architecture, and Tuning

This article examines why accelerating cloud‑based deep learning is essential, presents benchmark results comparing GPU generations and distributed training, introduces Alluxio as a distributed memory‑level cache, details its architecture on Kubernetes, and offers concrete tuning strategies to overcome I/O bottlenecks and boost training performance.

AIAlluxioKubernetes
0 likes · 16 min read
How Alluxio Supercharges Cloud Deep Learning: Benchmarks, Architecture, and Tuning
Code Ape Tech Column
Code Ape Tech Column
Jan 19, 2021 · Backend Development

Avoid Common Pitfalls in Distributed Caching with Redis and Memcached

This article analyzes the characteristics of Redis and Memcached, explains typical design mistakes such as inconsistent hashing, cache avalanche, penetration, and hot‑key issues, and provides practical solutions like consistent hashing, binlog‑driven cache invalidation, key versioning, and distributed locking to improve cache reliability and performance.

Cache AvalancheCache ConsistencyCache Penetration
0 likes · 22 min read
Avoid Common Pitfalls in Distributed Caching with Redis and Memcached
Qunar Tech Salon
Qunar Tech Salon
Jan 7, 2021 · Backend Development

Cache Strategies: From Local Page Cache to Distributed Multi‑Level Caching

This article shares a senior architect’s ten‑year journey with caching, covering local page and object caches, refresh policies, distributed solutions like Redis and Memcached, pagination caching techniques, multi‑level cache architectures, common pitfalls, and practical optimization lessons for high‑performance backend systems.

cachingdistributed cachemultilevel-cache
0 likes · 12 min read
Cache Strategies: From Local Page Cache to Distributed Multi‑Level Caching
dbaplus Community
dbaplus Community
Jan 1, 2021 · Backend Development

Mastering Cache: From Local to Multi‑Level Strategies for High‑Performance Systems

This article shares a senior architect’s decade‑long journey with caching, covering page‑level and object caches, refresh mechanisms, distributed solutions like Redis and Memcached, pagination caching techniques, and multi‑level cache architectures, while highlighting practical pitfalls and performance gains.

backenddistributed cachemultilevel-cache
0 likes · 12 min read
Mastering Cache: From Local to Multi‑Level Strategies for High‑Performance Systems
ITFLY8 Architecture Home
ITFLY8 Architecture Home
Dec 1, 2020 · Backend Development

Mastering Cache: Core Concepts, Pitfalls, and Patterns for Scalable Systems

Cache leverages the space‑time trade‑off to boost performance, but introduces complexity; this guide explains its fundamental idea, local vs distributed solutions, popular Java caching libraries, and key read/write patterns such as Cache‑Aside, Read‑Through, and Write‑Behind, highlighting benefits, drawbacks, and best‑practice considerations.

System Designcache patternscaching
0 likes · 13 min read
Mastering Cache: Core Concepts, Pitfalls, and Patterns for Scalable Systems
Programmer DD
Programmer DD
Sep 15, 2020 · Backend Development

Solving Distributed Cache Consistency: Cache‑Aside Pattern & Lazy Update Strategies

This article explains the classic Cache‑Aside pattern, analyzes common cache‑database consistency problems in high‑traffic systems, and presents practical solutions—including delete‑first updates, internal JVM queues, lazy recomputation, and routing considerations—to ensure reliable data synchronization under heavy concurrency.

Backend ArchitectureCache AsideData Consistency
0 likes · 11 min read
Solving Distributed Cache Consistency: Cache‑Aside Pattern & Lazy Update Strategies
Top Architect
Top Architect
Sep 13, 2020 · Backend Development

Java Distributed Caching with Redis and Redisson

This article explains why caching is essential for Java distributed applications, introduces Redis as an in‑memory data store, and demonstrates how the Redisson framework provides distributed cache implementations—including RMapCache, Spring Cache integration, and JCache support—complete with code examples and configuration details.

JCacheRedissonSpring Cache
0 likes · 8 min read
Java Distributed Caching with Redis and Redisson
Programmer DD
Programmer DD
Jul 18, 2020 · Backend Development

How to Build an EhCache Cluster for Spring Boot: A Step‑by‑Step Guide

This tutorial explains how to configure EhCache for distributed caching in a Spring Boot application, covering serialization, XML cluster settings, deployment parameters, REST endpoints for testing, and strategies to keep cache data consistent across multiple JVM instances.

Cache ClusteringEhcacheRMI
0 likes · 9 min read
How to Build an EhCache Cluster for Spring Boot: A Step‑by‑Step Guide
Ctrip Technology
Ctrip Technology
May 14, 2020 · Backend Development

Improving Ctrip's AB Experiment Splitter: Design, Performance Optimization, and Backend Architecture

The article details Ctrip's challenges with multiple AB testing splitters, presents performance gains after migrating to a new splitter, and explains the comprehensive redesign covering overall architecture, interface consolidation, SDK slimming, and a custom distributed cache backend to achieve higher throughput and lower latency.

AB testingCtripbackend design
0 likes · 12 min read
Improving Ctrip's AB Experiment Splitter: Design, Performance Optimization, and Backend Architecture
Top Architect
Top Architect
Apr 27, 2020 · Backend Development

Consistent Hashing: Principles, Optimizations, Graceful Scaling and Comparison with Redis HashSlot

This article explains the concept of consistent hashing, its application in distributed cache load balancing, analyzes issues like data skew and cache avalanche, presents virtual‑node optimizations with Java test code, discusses graceful scaling strategies, and compares it to Redis’s HashSlot and P2P approaches.

Hash Slotconsistent hashingdistributed cache
0 likes · 21 min read
Consistent Hashing: Principles, Optimizations, Graceful Scaling and Comparison with Redis HashSlot
Java Captain
Java Captain
Dec 20, 2019 · Backend Development

Using Redisson for Distributed Caching in Java Applications

This article explains why caching is essential for Java distributed applications, introduces Redis and Redisson, and demonstrates how to implement distributed caches using Redisson Maps, Spring Cache integration, and the JCache API with practical code examples.

JCacheRedisRedisson
0 likes · 6 min read
Using Redisson for Distributed Caching in Java Applications
MaGe Linux Operations
MaGe Linux Operations
Oct 10, 2019 · Backend Development

Unlocking Performance: A Deep Dive into Modern Caching Strategies

This article explores the pervasive role of caching in modern systems—from browser and HTTP caches to CDN, load‑balancer, in‑process, and distributed caches—detailing their mechanisms, algorithms, common pitfalls like cache avalanche, penetration and breakdown, and practical mitigation techniques for robust backend performance.

CDNbackendcaching
0 likes · 18 min read
Unlocking Performance: A Deep Dive into Modern Caching Strategies
Amap Tech
Amap Tech
Aug 13, 2019 · Backend Development

Cache Strategies and Framework Selection for High‑Performance Systems

To achieve low‑latency, high‑throughput data access in systems like Gaode’s navigation service, the article advises evaluating CPU and I/O bottlenecks, choosing between local (HashMap/ConcurrentHashMap or Caffeine) and distributed caches (Redis preferred), applying appropriate eviction, TTL, and consistency patterns, and mitigating cache penetration, breakdown, and avalanche risks.

Cache strategiesRediscaching
0 likes · 26 min read
Cache Strategies and Framework Selection for High‑Performance Systems
Architecture Digest
Architecture Digest
May 29, 2019 · Backend Development

Design and Solutions for High Availability and High Concurrency in Weibo Short Video Service

The article presents a detailed analysis of Weibo's short‑video platform architecture, covering team background, business scenarios, micro‑service design, feed‑pull model, multi‑level distributed caching, multi‑datacenter HA deployment, circuit‑breaker mechanisms, and elastic scaling to achieve high availability under unpredictable traffic spikes.

Backend ArchitectureElastic ScalingWeibo
0 likes · 12 min read
Design and Solutions for High Availability and High Concurrency in Weibo Short Video Service
Qunar Tech Salon
Qunar Tech Salon
Oct 31, 2018 · Backend Development

Understanding Cache: Concepts, Types, and Performance Optimization in High-Concurrency Scenarios

This article explains cache fundamentals—from CPU and local caches to distributed systems—covers design principles, performance‑affecting factors, eviction algorithms, and common high‑concurrency issues such as penetration, stampede, and avalanche, and provides practical solutions for selecting and optimizing cache strategies.

CPU cacheCache Evictioncaching
0 likes · 16 min read
Understanding Cache: Concepts, Types, and Performance Optimization in High-Concurrency Scenarios
Architects' Tech Alliance
Architects' Tech Alliance
Aug 29, 2018 · Backend Development

Comprehensive Guide to Effective Caching Strategies and Best Practices

This article explains when caching is needed, how to choose appropriate in‑process and distributed caches, design multi‑level cache architectures, handle cache updates, avoid common pitfalls such as penetration, breakdown and avalanche, and provides practical advice on serialization, GC tuning, monitoring, and framework selection.

Cache strategiesdistributed cachelocal cache
0 likes · 19 min read
Comprehensive Guide to Effective Caching Strategies and Best Practices
dbaplus Community
dbaplus Community
Aug 16, 2018 · Backend Development

Mastering Cache Design: Reduce Database Load and Boost High‑Concurrency Performance

This article explains why cache design is essential for high‑concurrency systems, compares CPU and application caches, outlines multi‑level and distributed caching strategies, discusses write‑through/write‑behind patterns, cache synchronization methods, penetration protection, and eviction policies to alleviate database pressure.

Cache Evictiondistributed cachehigh concurrency
0 likes · 12 min read
Mastering Cache Design: Reduce Database Load and Boost High‑Concurrency Performance
Mike Chen's Internet Architecture
Mike Chen's Internet Architecture
Aug 7, 2018 · Backend Development

Understanding Distributed Caching: Use Cases, Memcached vs Redis Comparison, and Common Challenges

This article explains why distributed caching is essential for high‑concurrency systems, outlines typical use cases, compares Memcached and Redis across features and performance, and discusses common problems such as cache avalanche, penetration, warm‑up, update strategies, and degradation.

Backend PerformanceCaching StrategiesMemcached
0 likes · 8 min read
Understanding Distributed Caching: Use Cases, Memcached vs Redis Comparison, and Common Challenges
JD Tech
JD Tech
Jul 26, 2018 · Backend Development

Why Design Caches? Multi‑Level Cache Strategies, Synchronization Schemes, and Common Pitfalls

This article explains the motivation behind cache design, compares CPU and application‑level caches, discusses multi‑level and distributed caching, outlines synchronization methods, eviction policies, and answers frequent cache‑related questions to help reduce database load and improve system performance.

Backend PerformanceCache Evictioncache synchronization
0 likes · 13 min read
Why Design Caches? Multi‑Level Cache Strategies, Synchronization Schemes, and Common Pitfalls
Alibaba Cloud Developer
Alibaba Cloud Developer
Feb 28, 2018 · Databases

How Alibaba’s Tair Cache Engine Scaled to 500M QPS for Double 11

Alibaba’s Tair, a high‑performance distributed key/value cache, evolved through multiple versions to support massive traffic during Double 11, employing multi‑region deployment, hotspot hashing, memory merging, user‑space networking, and client optimizations that dramatically cut latency, improve scalability, and reduce operational costs.

AlibabaScalable SystemsTair
0 likes · 14 min read
How Alibaba’s Tair Cache Engine Scaled to 500M QPS for Double 11
ITFLY8 Architecture Home
ITFLY8 Architecture Home
Jan 25, 2018 · Backend Development

Why Modern Web Apps Need Caching: From Basics to Distributed Strategies

This article explains the fundamentals of caching, why it is essential for high‑traffic web services, compares cache components such as Memcached and Redis, and details design patterns, scalability, high‑availability, and operational practices for building robust distributed cache systems.

Memcacheddistributed cacheperformance optimization
0 likes · 18 min read
Why Modern Web Apps Need Caching: From Basics to Distributed Strategies
Architects' Tech Alliance
Architects' Tech Alliance
Sep 23, 2017 · Operations

Understanding EMC vPlex Dual‑Active Storage Architecture and Distributed Cache Mechanisms

The article explains EMC vPlex's evolution, dual‑active Metro and Geo configurations, distributed cache coherence, storage virtualization, and integration with RecoverPoint, highlighting how these technologies enable high‑availability, low‑latency data access across multiple data‑center sites.

Dual-ActiveEMC vPlexHigh Availability
0 likes · 17 min read
Understanding EMC vPlex Dual‑Active Storage Architecture and Distributed Cache Mechanisms
Architecture Digest
Architecture Digest
Aug 8, 2017 · Backend Development

Scalability Design of Website Systems: Architecture and Load‑Balancing Strategies

This article explains how website systems achieve scalability through architectural designs such as physical function separation, server clustering, various load‑balancing techniques, distributed cache mechanisms, and both relational and NoSQL database scaling methods, providing practical guidance for large‑scale web deployments.

Backend ArchitectureDatabase ScalingLoad Balancing
0 likes · 13 min read
Scalability Design of Website Systems: Architecture and Load‑Balancing Strategies
ITPUB
ITPUB
May 18, 2017 · Backend Development

How to Prevent Cache Breakdown, Expiration, and Hot Key Issues in Distributed Systems

This article explains common problems of distributed caching such as cache breakdown, cache expiration, and hot‑key bottlenecks, and provides practical mitigation techniques including default null values, staggered expiration times, distributed locking, client‑side caching, and key sharding to maintain high‑concurrency performance.

Backend PerformanceCache BreakdownCaching Strategies
0 likes · 5 min read
How to Prevent Cache Breakdown, Expiration, and Hot Key Issues in Distributed Systems
MaGe Linux Operations
MaGe Linux Operations
Aug 20, 2016 · Backend Development

Design Scalable Website Architecture: Clusters, Load Balancing & Consistent Hashing

This article explains how to achieve website scalability through physical separation, server clustering, various load‑balancing techniques, consistent‑hashing for distributed caches, and scaling strategies for relational and NoSQL databases, providing practical guidance for building resilient back‑end systems.

consistent hashingdistributed cachescalability
0 likes · 16 min read
Design Scalable Website Architecture: Clusters, Load Balancing & Consistent Hashing
21CTO
21CTO
Jun 17, 2016 · Backend Development

How to Build a Scalable Web Architecture for Fast‑Growing Startups

This article explains how startup engineers can design a scalable web system by separating services onto multiple servers, using load balancers, distributed caches, master‑slave replication, and team‑splitting strategies, ensuring performance and reliability as user traffic and data volumes surge.

Database ReplicationLoad Balancingbackend development
0 likes · 15 min read
How to Build a Scalable Web Architecture for Fast‑Growing Startups
dbaplus Community
dbaplus Community
Dec 12, 2015 · Backend Development

How Memcached and Redis Work: Architecture, Protocols, and Memory Management

This article breaks down the core architecture, request protocols, and memory management mechanisms of Memcached and Redis, comparing their server models, highlighting their strengths and trade‑offs, and offering practical guidance for selecting and tuning these distributed caching solutions.

MemcachedRedisbackend
0 likes · 8 min read
How Memcached and Redis Work: Architecture, Protocols, and Memory Management
21CTO
21CTO
Oct 28, 2015 · Information Security

How Single Sign-On Works: Trust Storage, Validation, and Secure Implementation

This article explains the concept of Single Sign-On (SSO), why it’s essential for large web platforms, the core steps of storing and validating trust, common cookie‑based approaches, their security drawbacks, and how server‑side solutions using distributed caches and digital signatures can provide a robust, cross‑domain authentication system.

SSOSingle Sign-Onauthentication
0 likes · 5 min read
How Single Sign-On Works: Trust Storage, Validation, and Secure Implementation
Architect
Architect
Aug 26, 2015 · Backend Development

Design Considerations for Master/Slave Distributed Cache with Proxy and CAS

The article analyzes the use of a master/slave architecture for distributed caching, explains why two clusters, CAS, and proxy are employed, discusses consistency and availability challenges, and evaluates possible mitigation strategies for cache failures.

CASHigh Availabilityconsistency
0 likes · 7 min read
Design Considerations for Master/Slave Distributed Cache with Proxy and CAS
Qunar Tech Salon
Qunar Tech Salon
Jul 6, 2015 · Databases

Design, Deployment, and Lessons Learned from Codis and RebornDB: A Proxy‑Based Distributed Redis Solution

This article presents an in‑depth overview of Codis and its next‑generation project RebornDB, covering Redis, Redis Cluster, the proxy‑based architecture, consistency trade‑offs, production deployment experiences, operational pitfalls, and broader perspectives on distributed databases and architectures.

CodisHigh AvailabilityRebornDB
0 likes · 20 min read
Design, Deployment, and Lessons Learned from Codis and RebornDB: A Proxy‑Based Distributed Redis Solution
ITPUB
ITPUB
Feb 10, 2015 · Databases

Inside JD’s JimDB: How a Custom NoSQL Engine Powers Billion‑Scale E‑Commerce

This interview with JD’s distributed cache and NoSQL lead reveals how JimDB evolved from a Redis‑based engine to a two‑tier SSD‑optimized key‑value store, detailing fault‑tolerant design, online migration, scaling strategies, and the shifting role of DBAs in massive e‑commerce traffic.

JimdbNoSQLSSD optimization
0 likes · 11 min read
Inside JD’s JimDB: How a Custom NoSQL Engine Powers Billion‑Scale E‑Commerce