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547 articles · Page 6 of 6
Architecture Digest
Architecture Digest
Aug 13, 2018 · Backend Development

Cache Consistency, Concurrency, Penetration, Avalanche, and Bottomless Pit Issues and Mitigation Strategies

The article explains various cache problems—including consistency, concurrency, penetration, avalanche, and the bottomless‑pit phenomenon—and presents practical mitigation techniques such as active updates, locking, empty‑object caching, request filtering, consistent hashing, and multi‑level caching to ensure reliable high‑performance systems.

Caching Strategiesavalanchecache
0 likes · 8 min read
Cache Consistency, Concurrency, Penetration, Avalanche, and Bottomless Pit Issues and Mitigation Strategies
Architect's Tech Stack
Architect's Tech Stack
Aug 12, 2018 · Backend Development

Investigating MyBatis SqlSession.clearCache() Ineffectiveness and Transaction Isolation Level Solution

Through detailed debugging and source code analysis, the author discovers that MyBatis's SqlSession.clearCache() does clear the first‑level cache, but the observed stale query results are caused by MySQL's default REPEATABLE‑READ isolation level, which can be resolved by setting the transaction isolation to READ COMMITTED.

DebuggingMyBatisSQL
0 likes · 8 min read
Investigating MyBatis SqlSession.clearCache() Ineffectiveness and Transaction Isolation Level Solution
dbaplus Community
dbaplus Community
Jun 4, 2018 · Backend Development

How Weibo Scales to Billions: Inside Its Multi‑Layer Cache Architecture

This article explains how Weibo handles massive daily traffic of over a hundred billion requests by employing a five‑layer feed system and a six‑layer cache architecture that evolved from simple KV storage to sophisticated counter and existence‑check services, highlighting design choices, performance optimizations, and future directions.

Weibocachedistributed systems
0 likes · 16 min read
How Weibo Scales to Billions: Inside Its Multi‑Layer Cache Architecture
Java Captain
Java Captain
May 31, 2018 · Backend Development

Cache Update Strategies: Analysis, Drawbacks, and Improvement Solutions

This article examines three common cache‑update strategies, explains their concurrency and performance drawbacks, and proposes practical improvement techniques such as delayed double‑delete, asynchronous retries, and binlog‑based messaging to maintain consistency between cache and database.

cacheconsistencystrategy
0 likes · 10 min read
Cache Update Strategies: Analysis, Drawbacks, and Improvement Solutions
Java Backend Technology
Java Backend Technology
May 20, 2018 · Backend Development

Which Cache Update Strategy Guarantees Consistency? A Deep Dive into DB‑Cache Synchronization

This article examines three common cache‑update approaches—updating the cache after the database, deleting the cache before updating the database, and updating the database then deleting the cache—analyzes their drawbacks, and presents practical solutions such as delayed double‑delete and retry mechanisms to ensure data consistency.

Cache invalidationbackendcache
0 likes · 10 min read
Which Cache Update Strategy Guarantees Consistency? A Deep Dive into DB‑Cache Synchronization
dbaplus Community
dbaplus Community
May 13, 2018 · Backend Development

Mastering Distributed Cache: Programming Techniques, Sharding Strategies, and Migration Plans

This article explains why distributed caching is essential for high‑traffic services, presents three programming approaches (direct code, Spring‑Data‑Redis injection, and annotation‑based), compares three cache‑access patterns, details sharding models, outlines smooth and offline migration steps, and addresses cache penetration, concurrency, avalanche, and transaction support with concrete code examples.

MigrationRedisSharding
0 likes · 22 min read
Mastering Distributed Cache: Programming Techniques, Sharding Strategies, and Migration Plans
ITPUB
ITPUB
Feb 8, 2018 · Fundamentals

Why Linux Seems to Eat Your RAM—and How Buffers & Cache Actually Boost Performance

Linux’s free command often shows high memory usage, leading many to think the OS consumes RAM, but understanding buffers, cache, and the distinction between used and free memory reveals that Linux efficiently utilizes idle memory to improve I/O performance, as demonstrated by simple read‑speed experiments.

BuffersLinuxcache
0 likes · 8 min read
Why Linux Seems to Eat Your RAM—and How Buffers & Cache Actually Boost Performance
Architecture Digest
Architecture Digest
Feb 8, 2018 · Backend Development

High‑Performance Networking in Google Chrome: Architecture and Optimizations

The article explains Chrome's guiding principles, multi‑process architecture, network request lifecycle, and a suite of performance optimizations—including DNS pre‑fetch, TCP pre‑connect, caching strategies, and predictive pre‑rendering—that together reduce latency and make the browser faster as users continue to browse.

ChromeDNSMulti‑process
0 likes · 33 min read
High‑Performance Networking in Google Chrome: Architecture and Optimizations
Meituan Technology Team
Meituan Technology Team
Jan 18, 2018 · Backend Development

Analysis of MyBatis First‑Level and Second‑Level Cache Mechanisms

The article thoroughly examines MyBatis’s first‑level (session) and second‑level (namespace) caches, detailing their configurations, internal workflows, source‑code implementations, experimental behaviors, common pitfalls such as stale or dirty data, and advises disabling built‑in caching in favor of dedicated solutions for production.

MyBatisORMcache
0 likes · 25 min read
Analysis of MyBatis First‑Level and Second‑Level Cache Mechanisms
ITFLY8 Architecture Home
ITFLY8 Architecture Home
Oct 30, 2017 · Databases

Inside Memcached vs Redis: Architecture, Memory, and Persistence

An in‑depth comparison of Memcached and Redis reveals how both key‑value cache servers operate, covering their service models, event loops, memory allocation strategies, database implementations, persistence mechanisms, transaction support, and publish/subscribe features, highlighting the trade‑offs between simplicity and rich functionality.

PersistenceRediscache
0 likes · 33 min read
Inside Memcached vs Redis: Architecture, Memory, and Persistence
Architecture Digest
Architecture Digest
Oct 12, 2017 · Backend Development

Cache Eviction Strategies and Java Cache Implementations

This article explains various cache eviction strategies, compares heap, off‑heap, disk and distributed cache types, and provides concrete Java implementations using Guava Cache, EhCache 3.x and MapDB with code examples and usage patterns such as Cache‑Aside and Cache‑As‑SoR.

Cache EvictionEhcacheGuava
0 likes · 18 min read
Cache Eviction Strategies and Java Cache Implementations
ITPUB
ITPUB
Jun 23, 2017 · Fundamentals

How to Free Linux Memory Cache and Understand Buffer vs Cache

This guide explains Linux memory reporting with the free command, the roles of buffer and page caches, and provides step‑by‑step instructions to manually release cached memory using /proc/sys/vm/drop_caches, including practical command examples and clarifications of key concepts.

BufferMemory Managementcache
0 likes · 11 min read
How to Free Linux Memory Cache and Understand Buffer vs Cache
Efficient Ops
Efficient Ops
May 14, 2017 · Fundamentals

Understanding Linux Memory Management: Allocation, OOM, and Cache

This article explains Linux kernel memory management, covering process address space layout, memory allocation methods, OOM killer behavior, where different types of memory reside, and both manual and automatic memory reclamation techniques, illustrated with diagrams and command examples.

Memory ManagementOOMcache
0 likes · 18 min read
Understanding Linux Memory Management: Allocation, OOM, and Cache
ITPUB
ITPUB
Mar 27, 2017 · Backend Development

Mastering Cache Algorithms: From LRU to LFU and Beyond

This article explains why caching is essential, defines core concepts such as hits, misses, and costs, compares major replacement policies (LRU, LFU, FIFO, ARC, etc.), and provides Java code examples for implementing these algorithms in a backend system.

LFULRUbackend
0 likes · 19 min read
Mastering Cache Algorithms: From LRU to LFU and Beyond
Architects' Tech Alliance
Architects' Tech Alliance
Feb 7, 2017 · Backend Development

Technical Overview of WeChat Red Packet Distribution System

The article analyzes the massive scale of Chinese New Year red‑packet activity on WeChat, presents usage statistics, and explains the backend architecture—including distributed KV storage, cache‑layer atomic operations, and database transaction handling—that enables high‑throughput red‑packet distribution.

Backend ArchitectureDatabaseWeChat
0 likes · 5 min read
Technical Overview of WeChat Red Packet Distribution System
dbaplus Community
dbaplus Community
Jan 15, 2017 · Databases

How JD’s JIMDB Achieves Zero‑Downtime Scaling and Automatic Failover for Massive Caches

JIMDB is JD’s in‑house distributed cache platform that combines automatic fault detection, seamless online scaling, multi‑language support, and containerized deployment to replace traditional Memcached/Redis solutions, offering features such as one‑click cluster creation, elastic expansion, lossless scaling, and comprehensive monitoring for high‑traffic e‑commerce services.

Elastic ScalingFault Tolerancecache
0 likes · 23 min read
How JD’s JIMDB Achieves Zero‑Downtime Scaling and Automatic Failover for Massive Caches
Architecture Digest
Architecture Digest
Nov 26, 2016 · Databases

Redis Cache Update Strategies and Best Practices

This article summarizes common Redis cache update problems, compares four update approaches—including proactive, passive, and pre‑loading methods—and recommends a pre‑load strategy with key versioning to avoid data loss, improve performance, and reduce memory waste.

DatabaseRedisUpdate Strategy
0 likes · 8 min read
Redis Cache Update Strategies and Best Practices
ITFLY8 Architecture Home
ITFLY8 Architecture Home
Nov 24, 2016 · Fundamentals

Why Redlock May Not Be the Ultimate Distributed Lock (And What to Use Instead)

This article reviews the evolution of distributed locking—from simple MySQL table locks to Redis cache locks and the Redlock algorithm—examines expert criticisms of Redlock’s correctness, presents the Redis author’s rebuttal, and ultimately recommends Zookeeper as a more reliable solution for high‑availability distributed locks.

ConsensusRedisRedlock
0 likes · 22 min read
Why Redlock May Not Be the Ultimate Distributed Lock (And What to Use Instead)
Nightwalker Tech
Nightwalker Tech
Oct 15, 2016 · Backend Development

Technical Discussion on Cache Hit Rate, AOP, and Performance Optimization

A multi‑person technical discussion explores the reasons behind low cache hit rates, examines memcached LRU mechanisms, proposes AOP‑based caching strategies, and shares practical solutions such as proactive cache invalidation, lock‑based stampede protection, and workload‑aware configuration for backend systems.

AOPMemcachedbackend
0 likes · 9 min read
Technical Discussion on Cache Hit Rate, AOP, and Performance Optimization
ITPUB
ITPUB
Aug 31, 2016 · Databases

Lock‑Free Transactions and Cache Switching: MVCC Techniques for Key‑Value Stores

This article explains how traditional ACID transactions fall short for modern large‑scale systems and presents lock‑free transaction methods, atomic and partial cache‑switch techniques, and a PostgreSQL‑style MVCC model for key‑value databases, including practical rules and trade‑offs.

DatabaseKey-ValueMVCC
0 likes · 10 min read
Lock‑Free Transactions and Cache Switching: MVCC Techniques for Key‑Value Stores
High Availability Architecture
High Availability Architecture
Aug 26, 2016 · Backend Development

Evolution of Weibo Cache Service: From Bare Memcache to Multi‑Layered Service Architecture

The article details how Weibo’s cache infrastructure progressed from simple Memcache deployments to a sophisticated, service‑oriented architecture featuring multi‑layer caching, proxy layers, dynamic configuration, monitoring, and automated scaling to meet massive read‑write demands and high availability requirements.

High Availabilitybackendcache
0 likes · 19 min read
Evolution of Weibo Cache Service: From Bare Memcache to Multi‑Layered Service Architecture
360 Zhihui Cloud Developer
360 Zhihui Cloud Developer
Aug 12, 2016 · Databases

Why Redis Replicas Return Expired Keys and How to Prevent It

The article explains how Redis replicas can return keys that should have expired due to the master‑only expiration process, describes the three expiration strategies (lazy, periodic, active), and offers practical solutions such as using SCAN or upgrading to Redis 3.2 to avoid stale reads.

Rediscacheexpiration
0 likes · 9 min read
Why Redis Replicas Return Expired Keys and How to Prevent It
Qunar Tech Salon
Qunar Tech Salon
Aug 3, 2016 · Backend Development

Optimizing Write‑Heavy High‑Concurrency Cache: Lock Granularity, Horizontal Sharding, and Lock‑Free Strategies

The article analyzes write‑mostly, read‑light cache scenarios such as driver location updates and counter increments, discusses lock bottlenecks, proposes horizontal sharding and per‑record locking, explores lock‑free approaches with data‑integrity signatures, and summarizes practical optimization techniques for high‑concurrency back‑end systems.

Lock-FreeShardingcache
0 likes · 8 min read
Optimizing Write‑Heavy High‑Concurrency Cache: Lock Granularity, Horizontal Sharding, and Lock‑Free Strategies
Efficient Ops
Efficient Ops
Jul 5, 2016 · Operations

Mastering Web Cache: A Complete Layered Knowledge System

This article presents a systematic overview of web caching, detailing a seven‑layer cache hierarchy, clarifying the differences between buffer and cache, and explaining key cache metrics and design considerations for modern web architectures.

Buffercacheweb cache
0 likes · 11 min read
Mastering Web Cache: A Complete Layered Knowledge System
ITFLY8 Architecture Home
ITFLY8 Architecture Home
Jun 19, 2016 · Backend Development

How to Tackle Common Cache Problems in Distributed Systems

This article explores typical cache challenges in distributed systems—including data consistency, high availability, cache avalanche, and cache penetration—explaining their causes, real‑world scenarios, and practical mitigation strategies to ensure reliable and efficient caching.

Cache AvalancheCache PenetrationData Consistency
0 likes · 9 min read
How to Tackle Common Cache Problems in Distributed Systems
Meituan Technology Team
Meituan Technology Team
Jun 17, 2016 · Operations

How to Prevent and Recover from Cache‑Induced Service Overload

Service overload caused by cache failures can cripple dependent systems, but by adopting smart cache get patterns, proactive client‑side checks, traffic throttling, service degradation, and dynamic scaling, developers can both prevent overload and recover gracefully when it occurs.

OperationsSystem Designbackend
0 likes · 22 min read
How to Prevent and Recover from Cache‑Induced Service Overload
MaGe Linux Operations
MaGe Linux Operations
Jun 4, 2016 · Fundamentals

Why Linux’s Buffer/Cache Isn’t Always Free Memory – A Deep Dive

This article explains how the Linux free command reports memory usage, clarifies the roles of buffer and page cache, shows how to manually drop caches, and reveals scenarios—such as tmpfs, shared memory, and mmap—where cached memory cannot be reclaimed, helping readers achieve a deeper understanding of system memory behavior.

Buffer Cachecachepage cache
0 likes · 14 min read
Why Linux’s Buffer/Cache Isn’t Always Free Memory – A Deep Dive
DevOps
DevOps
Apr 17, 2016 · Fundamentals

CPU “Ah Gan” Explains the Boot Process, Memory Hierarchy, Cache, and Pipelining

Through a whimsical first‑person narrative, the article walks readers through a CPU’s start‑up sequence, BIOS interrupt handling, loading the boot sector, memory access patterns, the principle of locality, cache usage, and the introduction of pipelining to illustrate fundamental computer architecture concepts.

CPUboot processcache
0 likes · 11 min read
CPU “Ah Gan” Explains the Boot Process, Memory Hierarchy, Cache, and Pipelining
21CTO
21CTO
Apr 16, 2016 · Backend Development

How WeChat Scaled Red Packets for 80 Billion Transactions: Architecture Secrets

This article explains how WeChat redesigned its red‑packet system for the 2016 Chinese New Year, detailing north‑south data separation, multi‑layer caching, asynchronous settlement, high‑concurrency controls, sharding strategies and graceful degradation to handle billions of red‑packet requests.

Distributed ArchitectureWeChatbackend scaling
0 likes · 13 min read
How WeChat Scaled Red Packets for 80 Billion Transactions: Architecture Secrets
dbaplus Community
dbaplus Community
Mar 28, 2016 · Backend Development

How to Keep Cache and Database Consistent: Invalidate First, Serialize Access

This article explains why cache and database can become inconsistent in distributed systems, why the "invalidate‑cache‑then‑write‑DB" rule is preferred, and presents practical serialization techniques—modifying DB and service connection pools—to guarantee per‑key sequential execution while maintaining availability and load balance.

Backend ArchitectureConnection PoolSerialization
0 likes · 11 min read
How to Keep Cache and Database Consistent: Invalidate First, Serialize Access
21CTO
21CTO
Mar 1, 2016 · Backend Development

Mastering Cache Algorithms: From LRU to LFU with Java Implementations

This article explains the fundamentals of caching, why caches are needed, describes common replacement policies such as LRU, LFU, FIFO, ARC, and provides Java code examples for each algorithm, helping developers choose and implement the right cache strategy for their applications.

LFULRUbackend
0 likes · 19 min read
Mastering Cache Algorithms: From LRU to LFU with Java Implementations
21CTO
21CTO
Jan 9, 2016 · Backend Development

Building a High‑Concurrency, Scalable Proxy for Weibo Recommendation Engine

This article details the design and implementation of a high‑concurrency, easily extensible proxy built in Go for Weibo's recommendation system, covering background, challenges with twemproxy, technical research, architecture, configuration, logging, monitoring, module breakdown, business logic, performance testing, and future improvements.

Twemproxycachegolang
0 likes · 20 min read
Building a High‑Concurrency, Scalable Proxy for Weibo Recommendation Engine
Architect
Architect
Nov 22, 2015 · Backend Development

Implementing Rails Fragment Cache with Redis and Session Storage

This article explains how to enable Rails fragment caching, use HTML fragment cache helpers, understand cache digests, observe read/write fragment logs, and migrate the cache store from file system to Redis by adding redis-namespace and redis-rails gems, configuring cache_store, and handling cache invalidation on data changes.

FragmentCacheRailsRedis
0 likes · 9 min read
Implementing Rails Fragment Cache with Redis and Session Storage
21CTO
21CTO
Nov 14, 2015 · Backend Development

How WeChat’s Red Packet System Handles Millions of Claims in Real Time

This article explains the backend architecture behind WeChat’s red‑packet feature, detailing how the system stores packet data, uses cache‑level atomic operations for grabbing, separates claim and settlement steps, and ensures high‑throughput, fault‑tolerant processing during peak usage.

WeChatbackendcache
0 likes · 6 min read
How WeChat’s Red Packet System Handles Millions of Claims in Real Time
Java High-Performance Architecture
Java High-Performance Architecture
Oct 15, 2015 · Databases

Master MySQL Cache Settings: Key Buffers, Table Cache, and More

This guide explains the essential MySQL cache parameters—including key_buffer_size, table_cache, sort_buffer_size, read_buffer_size, join_buffer_size, thread_cache_size, query_cache_size, and tmp_table_size—detailing their impact on performance and providing recommended values based on server memory to help DBAs optimize MyISAM and InnoDB workloads.

ConfigurationMySQLcache
0 likes · 4 min read
Master MySQL Cache Settings: Key Buffers, Table Cache, and More
Architect
Architect
Jul 30, 2015 · Backend Development

Redis‑Backed Timeline Implementation with MongoDB for a Subscription Feed

This article explains how to implement a scalable timeline for a subscription feed by combining MongoDB storage with a Redis list cache, detailing the data model, query challenges, Redis operations for pushing and trimming statuses, rebuilding strategies, and handling data integrity trade‑offs.

MongoDBQueueRedis
0 likes · 7 min read
Redis‑Backed Timeline Implementation with MongoDB for a Subscription Feed