This guide walks through setting up a Redis Cluster with three master and three replica nodes on Rocky 9.7 VMs, covering environment preparation, source compilation, configuration files, service creation, cluster creation, verification, and production‑grade tuning.
This article outlines a multi‑level cache system for handling over a million QPS, detailing the architecture from client to database, key components like Caffeine and Redis Cluster, and providing concrete code examples for read‑through and write‑through flows.
Redis Cluster can lose writes due to asynchronous replication, network partitions, inadequate persistence settings, or unconfirmed client operations, but enabling AOF, configuring replication acknowledgments, using Sentinel or built‑in HA, and adding client retry logic can mitigate these risks, as demonstrated with a Java Jedis example.
The article examines the fundamental limitations of consistent hashing—its inability to preserve data locality, support range queries, and handle topology awareness—explaining why major storage systems such as Redis Cluster, TiDB, Ceph, and HBase have adopted alternative sharding strategies like hash slots, range partitioning, and CRUSH.
The article outlines five Redis deployment patterns—from a single‑instance setup to official Redis Cluster—detailing their architectures, advantages, drawbacks, and suitable scenarios, helping engineers choose the right solution for scalability, high availability, and operational complexity.
This article explains the CAP and BASE theorems, compares consistency, availability and partition tolerance, and analyzes how MySQL replication modes, Redis Cluster, and Elasticsearch clusters fit into CP, AP or BASE models to help you choose the appropriate consistency strategy for distributed systems.
This article explains how Redis limits memory with the maxmemory setting, how to view and modify it, details the available eviction strategies—including the newer LFU policies—and offers guidance on choosing a policy, monitoring usage, and scaling with Redis Cluster.
This article analyzes why Lettuce's mget on Redis Cluster performs poorly due to slot-based architecture, presents client-side refactoring using hashtags and pipeline‑based JedisCluster modifications, and shows benchmark results demonstrating up to double speed improvement over Lettuce.
This article explains Redis master‑slave replication, its configuration and failure handling, the automatic failover provided by Redis Sentinel, the proxy‑based Codis sharding solution, and the native Redis Cluster architecture, including slot hashing, redirection, and replica promotion.
This article introduces Redis, explains its advantages, describes Redis Cluster architecture, and provides a detailed, hands‑on tutorial for deploying a Redis Cluster on Kubernetes using StatefulSets, PersistentVolumes, services, and a sample hit‑counter application, complete with configuration files and verification commands.
This guide introduces AnotherRedisDesktopManager, a free and visually appealing Redis GUI that supports cluster connections, walks through installation from GitHub, explains key features such as dark mode, command console, and versatile data operations for strings, lists, and hashes, and demonstrates practical cluster usage.
This article demonstrates how to set up a Redis cluster, connect it with Spring Boot 2.3 using Lettuce, simulate a node failure, and configure Spring Boot's adaptive topology refresh to achieve automatic failover without application downtime.
This article explains the design of Redis Cluster, the challenges of migrating clients, and how the Camellia-Redis-Proxy middleware—built with Netty—provides transparent proxying, sharding, dual‑write, plugin support, and performance optimizations such as multithreading, async I/O, pipelining, and robust error handling.
This guide walks you through setting up a six-node Redis cluster using Docker Compose, configuring the necessary redis.conf settings, deploying the containers, initializing the cluster, and then integrating the cluster into a SpringBoot application via appropriate application.yml configurations and connection commands.
This article explains why Spring Boot 2.0 replaced the Jedis Redis client with Lettuce, highlighting Lettuce’s netty‑based architecture, thread‑safe shared connections, asynchronous and reactive support, seamless Redis Sentinel and Cluster integration, SSL, streaming API, and provides code examples for both blocking and async usage.
This article examines 360’s explosive KV storage demand and compares three solutions—Redis, Redis Cluster, and Pika—detailing their features, performance, persistence options, eviction policies, architectures, migration tools, and ideal usage scenarios for high‑traffic, large‑scale applications.
This article examines the performance challenges of a 700‑node Redis Cluster used by Youku, analyzes bandwidth and latency impacts of cluster communication, and presents practical tuning methods—including adjusting cluster‑node‑timeout, reducing replicas, disabling AOF, limiting cluster‑nodes commands, and tuning the hz parameter—to improve throughput and stability in massive Redis deployments.
This article shares VIPShop's extensive production experience with Redis Cluster, covering use cases, storage architecture evolution, detailed best‑practice guidelines, common pitfalls, operational automation, monitoring strategies, and useful open‑source tools for large‑scale deployments.
This guide explains why the official Redis Cluster tools lack password support, outlines the security risks of an unauthenticated cluster, and introduces a custom management utility that adds password authentication, automates slot migration, and simplifies adding or removing nodes, complete with step‑by‑step testing procedures.
This article explains the concept, benefits, methods, and practical considerations of partitioning data across multiple Redis instances, covering range and hash partitioning, consistent hashing, implementation options, drawbacks, and recommended tools such as Redis Cluster and Twemproxy.
The article records a Q&A session from the Efficient Operations talk, where guest Peng Zhef of Mango TV discusses Docker, Redis Cluster, container resource controls, and related operational challenges, providing practical insights into Python/Flask development, pod scaling, and Linux cgroup tuning.
