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Backend Development Feb 11, 2022 IT Architects Alliance

Cache Design and Optimization Strategies in High-Concurrency Distributed Systems

The article discusses the importance of caching in high‑concurrency distributed systems, outlining its benefits and costs, various update policies such as LRU/LFU/FIFO, expiration, active refresh, and advanced optimizations like penetration protection, hole mitigation, avalanche prevention, and hot‑key rebuild techniques.

Distributed Systemsperformance optimizationcachingcache avalanchecache penetrationcache eviction

Backend Development Feb 11, 2022 Top Architect

Cache Design and Optimization Strategies for High‑Concurrency Distributed Systems

The article explains why caching is essential in high‑concurrency distributed systems, analyzes its benefits and costs, and then details various cache update, penetration, no‑hole, avalanche, and hot‑key rebuilding techniques, offering practical guidance for backend engineers.

distributed systemscachingbackend optimizationcache avalanchecache penetrationcache eviction

Backend Development Jan 30, 2022 Architecture Digest

Cache Design and Optimization Strategies in High‑Concurrency Distributed Systems

This article examines the role of caching in high‑concurrency distributed systems, outlining its performance benefits and associated costs, and detailing various cache‑update strategies—including LRU/LFU/FIFO, expiration, active refresh, Bloom‑filter protection, and solutions for penetration, avalanche, hot‑key rebuild, and the “no‑bottom‑hole” problem.

distributed systemsperformancecachinghigh concurrencyBloom filtercache eviction

Fundamentals Jan 23, 2022 Tencent Cloud Developer

Understanding Paxos and Consensus Algorithms in Distributed Systems

Understanding Paxos and other consensus algorithms, this article explains how crash‑fault‑tolerant protocols like Paxos, Raft, and ZAB achieve sequential consistency through two‑phase voting, contrasts them with Byzantine‑fault‑tolerant methods, and details Multi‑Paxos optimizations, leader election, and practical trade‑offs for distributed systems.

Distributed SystemsRaftConsensus AlgorithmByzantine Fault ToleranceCrash Fault ToleranceMulti-PaxosPaxos

Backend Development Jan 22, 2022 Architecture Digest

Implementation Schemes and Design Trade‑offs of Delayed Messages in Distributed Messaging Systems

This article surveys common delayed‑message solutions in distributed messaging, compares implementations based on external storage (MySQL, RocksDB, Redis) and built‑in MQ features (RocketMQ, Pulsar, QMQ), and analyzes their advantages, disadvantages, and design considerations.

backenddistributed systemsmessage queueRocketMQPulsardelayed messagingQMQ

Backend Development Jan 18, 2022 IT Architects Alliance

Implementation Strategies for Delayed (Scheduled) Messages in Distributed Systems

This article examines common delayed (scheduled) message implementations in distributed systems, comparing external storage approaches using databases, RocksDB, and Redis, as well as built-in solutions in open-source MQs like RocketMQ, Pulsar, and QMQ, and discusses their advantages, drawbacks, and design considerations.

distributed systemsRedisMessage QueueRocketMQRocksDBdelayed messages

Backend Development Jan 13, 2022 Tencent Cloud Developer

Strategies for Ensuring Cache Consistency in Distributed Systems

The article reviews major cache‑consistency strategies—Cache‑Aside, Read‑Through, Write‑Through, and Write‑Behind—detailing their performance and consistency trade‑offs, discusses compensation techniques such as delayed double‑delete and MySQL binlog‑based incremental parsing (DTS) for reliable deletion and HA, and advises selecting the appropriate approach based on specific business requirements.

Distributed SystemsSystem Architecturedatabase optimizationcache consistencycaching strategies

Backend Development Jan 4, 2022 DeWu Technology

Best Practices for Redis Cache Consistency in Distributed Systems

In distributed e‑commerce systems, achieving Redis cache consistency requires invalidating stale entries via reliable DB change detection (e.g., binlog listeners) and optionally using versioned writes that only update when newer, combined with safeguards like TTLs, double deletes, and business‑specific designs to mitigate race conditions and ensure eventual consistency.

Distributed SystemsBackend DevelopmentRedisBest PracticesCache Consistency

Fundamentals Dec 20, 2021 Architect

Understanding Distributed Systems: Zookeeper, 2PC/3PC, Consensus Algorithms, CAP and BASE Theories

This article explains the evolution from centralized to distributed architectures, the role of Zookeeper in solving consistency problems, the mechanics and drawbacks of 2‑phase and 3‑phase commits, and key consensus algorithms such as Paxos, Raft, ZAB, as well as CAP and BASE theories that guide practical system design.

Distributed SystemsBASE theoryCAP theoremZookeeper2PC3PCconsensus algorithms

Fundamentals Dec 9, 2021 Architects Research Society

Key Challenges in Designing Distributed Systems

Designing a distributed system involves overcoming major challenges such as heterogeneity, transparency, openness, concurrency, security, scalability, and fault tolerance, each of which must be addressed to build a reliable, extensible, and performant system.

distributed systemsscalabilityconcurrencyfault tolerancesecurityheterogeneitytransparency

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