This article explains how Redis Sentinel provides high‑availability for Redis clusters by monitoring masters and slaves, automatically failing over to a new master, and offering three methods for receiving failover notifications, while recommending an indirect‑service approach for scalable integration.
This article narrates how Redis, personified as a character, synchronizes data between master and slave nodes through command propagation, adopts improved sync strategies, and uses Sentinel's INFO and PING checks to detect failures and automatically trigger failover, illustrating a practical high‑availability cache service.
This guide explains MongoDB replica set fundamentals, walks through local deployment of a primary‑secondary‑secondary cluster, demonstrates automatic failover, and details write concern and read preference options—including member attributes, connection string parameters, and shell commands—for reliable high‑availability data handling.
This article walks through the evolution of big‑data systems to modern stream processing, explains core Flink concepts such as state, checkpoints, event‑time and windowing, and details Kuaishou’s real‑time UV calculation and fast‑failover techniques for high‑availability streaming jobs.
This article explains how MySQL Group Replication (MGR) can provide zero‑RPO high‑availability within a city‑scale data center, why it needs asynchronous replication for WAN‑scale disaster recovery, and walks through a step‑by‑step setup—including code examples—for automatic failover of asynchronous replication channels.
This article explains how to use Redis Sentinel to achieve high availability, covering its core functions, configuration steps, three methods of receiving failover notifications, and a recommended overall design with diagrams and code examples.
This guide explains how to configure Redis Sentinel to monitor master‑slave instances, automatically promote a slave on master failure, and verify the high‑availability setup with detailed configuration files, startup commands, status checks, and failover testing steps.
This article explains how Redis Sentinel provides automatic failover and high availability by using master‑slave replication, multiple Sentinel nodes, consensus‑based leader election, and client notification mechanisms to ensure continuous service despite node failures.
This article explains Redis Cluster’s architecture, node and slot management, failover and resharding mechanisms, and how they together affect write safety, detailing commands, metadata storage, conflict resolution, and client redirection strategies in distributed environments.
This guide explains how to replace the traditional MHA/Keepalived high‑availability setup with MariaDB MaxScale integrated with Consul, providing a simpler, fully automated HA solution, complete with configuration files, installation commands, and detailed failover, switchover, and rejoin procedures.
This article introduces MySQL 8.0.20 Group Replication, covering single‑master and multi‑master modes, monitoring, failover procedures, abnormal recovery, flow control, performance testing, encountered issues, and limitations, and provides a downloadable PDF with detailed documentation hosted on Baidu Cloud.
This article explains the design, pitfalls, and improvement ideas of a Redis‑based distributed lock used since 2013, covering lock acquisition and release processes, expiration handling, high‑availability strategies, and practical lessons for building robust concurrency control in distributed systems.
This article explains what Oracle Active Data Guard (ADG) is, outlines its basic deployment architecture, and provides detailed step‑by‑step emergency response procedures for four common network and server configurations to ensure rapid failover and business continuity.
Keepalived, originally designed for LVS load balancing, provides VRRP-based high‑availability by managing LVS nodes, performing health checks, and offering failover for services like Nginx, HAProxy, and MySQL, while also addressing split‑brain scenarios and non‑preemptive configurations.
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 how to build a highly available Redis service by analyzing failure scenarios, comparing single‑instance, master‑slave with one or multiple Sentinel processes, and finally presenting a three‑Sentinel architecture that ensures continuous service despite node or network outages.
This article explains the evolution of Alipay's high‑availability and disaster‑recovery architecture—from a simple single‑datacenter design to a multi‑datacenter, unit‑based system with failover and blue‑green deployment—highlighting the challenges, solutions, and operational benefits that enable continuous service during massive traffic spikes.
This article walks through the evolution of a Redis‑based cache layer for multi‑data‑center deployments, addressing consistency, safety, performance, disk‑space, data loops, timestamp versioning, master‑slave failover, and global numeric aggregation, and culminates in a ready‑to‑use middleware solution.
This guide explains how to install Keepalived, configure VRRP‑based high‑availability for Nginx load balancers, modify master and backup configuration files, test failover scenarios, and add a Bash watchdog script to ensure seamless service continuity.
This article describes JDHBase’s large‑scale KV storage architecture, its HBase‑based asynchronous replication mechanism, multi‑active cluster design, client‑side routing via Fox Manager, automatic failover strategies, dynamic replication tuning, and serial replication techniques to ensure data consistency across geographically distributed data centers.
This article explains Kafka's topic architecture, detailing how topics are split into partitions for scalability and parallelism, the role of logs, key-based and round-robin partitioning, replication with leaders, followers, ISR, and how these mechanisms enable fault‑tolerance and high‑performance consumer failover.
This article reviews Alibaba's decade‑long evolution of HBase high‑availability, covering large‑cluster design, MTTF/MTTR metrics, disaster‑recovery strategies, traffic switching, and performance optimizations that together enable millions of requests per second with near‑zero downtime.
This article explains OpenStack Trove’s role as a Database-as-a-Service platform, outlines its core components, and details QiYun’s custom enhancements—including automated backup, monitoring, and a streamlined single-API master-slave instance creation with isolated networks and VIP-based failover for improved security and availability.
This article explains the need for high‑availability MySQL services, critiques the original in‑house HA approach, and details how the mature MHA framework was extended into WMHA with added VIP monitoring, enhanced failover procedures, richer notifications, and a reorganized deployment structure to improve reliability and reduce DBA intervention.
The article explains Kafka's consumer‑group rebalance and Pulsar's unified queue/stream subscription models, compares their partition assignment strategies, and demonstrates both with Docker‑based Pulsar setups, Java consumer code, and practical failover and exclusive scenarios.
This article explains the principles and components of high‑availability (HA) clusters, covering active/standby nodes, resource stickiness and constraints, heartbeat and quorum mechanisms, split‑brain avoidance, failure detection methods, and the minimal setup required for a reliable web‑service HA deployment.
The article explains what constitutes a fault, introduces key metrics such as RPO and RTO, and describes various fault isolation principles, patterns, and practical examples—including dependency degradation, failover, dynamic adjustment, fast‑fail, caching, rate limiting, and resource isolation—to improve system reliability.
This article describes Qunar's automated network outage detection and intelligent traffic switching system, detailing the problem background, solution architecture, component functions, workflow, optimization steps, and future plans for more precise, multi‑level failover handling.
This article explains how to design and implement a highly available Redis deployment using master‑slave replication, multiple Redis Sentinel instances, and a virtual IP to provide seamless failover while maintaining simple client connectivity, covering failure scenarios, architecture choices, and practical configuration tips.
This article examines Alipay's evolution from a simple single‑datacenter setup to a multi‑active‑active, unit‑based architecture, detailing the technical challenges of high availability, disaster recovery, failover design, blue‑green deployment, and how these solutions enable continuous service during massive traffic spikes like Double 11.
This article examines the importance of high‑availability and disaster‑recovery architectures, tracing Alipay’s evolution from a simple load‑balanced setup through multi‑datacenter, failover, and unit‑based designs that address scalability, data consistency, and continuous service delivery challenges.
This article explains how to define high availability for Redis, enumerates typical failure scenarios, compares four deployment patterns—from a single instance to a three‑sentinel setup—and provides practical steps, diagrams, and tips for achieving reliable Redis service using Sentinel and virtual IP failover.
This article explains how to build a highly available Redis deployment by defining HA requirements, analyzing failure scenarios, and progressively implementing solutions from a single instance to a three‑sentinel architecture with virtual IP failover for seamless client access.
This article explains how to build a highly available Redis deployment using Redis Sentinel, compares several architectural options, and details the final three‑sentinel design that tolerates node, process, and network failures while keeping client access simple.
This article explores how distributed systems determine node liveness, manage failover and recovery, and implement at‑most‑once, at‑least‑once, and exactly‑once processing guarantees—including opaque transactions and two‑phase commit—using examples from Kafka, Zookeeper, and big‑data pipelines.
This article explains how high‑availability (HA) clusters provide redundancy for directors, RS‑servers, databases and storage, covering active‑passive node roles, resource stickiness, constraints, quorum voting, split‑brain avoidance, failure detection methods, and essential configuration tips.
This article details the evolution of JD's Elastic Database, describing the challenges of scaling MySQL, the staged solutions including sharding, JProxy, and the final elastic architecture with services like Topology, JED‑Gate, and JED‑Tablet, and explains its query processing, dynamic resharding, and automatic failover mechanisms.
This article explains Redis fundamentals, details the Sentinel mechanism, compares several high‑availability deployment patterns—including Sentinel with DNS or VIP, client‑direct connections, Keepalived/Haproxy, Redis Cluster, Twemproxy, and Codis—provides their advantages and drawbacks, and offers practical best‑practice recommendations for reliable production use.
This guide walks through setting up a Redis high‑availability solution using master‑slave replication, Redis Sentinel for automatic failover, and a floating VIP to provide a stable endpoint, covering environment preparation, configuration files, firewall rules, testing, and client integration.
This guide demonstrates how to configure a highly available Redis deployment using master‑slave replication, Redis Sentinel for automatic failover, and virtual IP (VIP) migration, covering environment setup, configuration files, firewall adjustments, testing procedures, and client connection strategies.
An in‑depth review of the heated debate between Redis creator antirez and distributed‑systems expert Martin Kleppmann over the safety of Redis’s Redlock algorithm, covering single‑node lock pitfalls, failover issues, timing assumptions, fencing tokens, and practical recommendations for when to use Redlock versus simpler locks.
This article introduces MHA (Master High Availability) for MySQL, explains its architecture, outlines required hardware and software configurations, provides detailed commands to set up master and slave nodes, create configuration files, and demonstrates how to start and verify the high‑availability cluster.
This article examines the operational challenges of oversized Redis instances—including slow failover, prolonged slave resynchronization, network‑induced avalanches, and persistence blocking—and offers practical mitigation strategies such as key expiration, data compression, and using high‑performance alternatives like Pika.
This article walks through semi‑automated Oracle Data Guard deployment, when and how to use DG Broker, practical failover, switchover and archive‑recovery scenarios, Oracle 12c enhancements like Far Sync and VALIDATE, a real‑world standby query failure case, and using Data Guard for database migration.
This article provides a detailed, hands‑on walkthrough of Oracle Data Guard switchover in normal operation and the subsequent steps to convert the original primary to a standby, including all necessary SQL commands, instance restarts, and verification queries.
This guide walks through setting up a MySQL master‑slave cluster, installing MaxScale, configuring authentication, monitoring, routing and logging plugins, testing read/write split and load balancing, and handling single‑ or multiple‑slave failures with automatic failover.
This tutorial walks through setting up a MySQL master‑slave replication cluster, configuring password‑less SSH, installing MHA‑node and MHA‑manager, creating the MHA configuration, validating the setup, and testing automatic failover when the master goes down.
This article demonstrates how MaxScale manages MySQL read/write splitting when one or both slave servers fail, showing log configurations, state changes, and how to configure a stable master to maintain service continuity even when all slaves are down.
The article explains Diamond, a simple, reliable, and easy‑to‑use distributed configuration management system used inside Taobao, detailing its features, persistence and disaster‑recovery mechanisms, overall architecture, client‑side subscription code, and the internal processes that keep configuration data synchronized.
This article explains how MHA provides automated master monitoring, rapid failover within 10‑30 seconds, online master switching, various failover modes, extensible scripts, key commands, and best‑practice workflows to achieve high‑availability MySQL replication without performance impact.
This guide walks through MySQL high‑availability architectures, comparing failover solutions like MMM and MHA, detailing MHA installation, configuration, and testing, and exploring MaxScale's read/write splitting, routing strategies, and integration with MHA for seamless failover.
This article explains MHA’s architecture, failover workflow, comparison with other MySQL HA solutions, and its six key advantages, showing how it can switch masters within seconds while preserving data consistency without altering MySQL settings or adding many servers.
The article examines how oversized Redis instances cause catastrophic failures during primary node crashes, scaling bursts, and network issues, explains the costly re‑synchronization steps, presents real‑world timing data, and offers practical memory‑reduction strategies to keep Redis operations reliable.
This guide explains how to configure a Huawei router to automatically differentiate China Telecom and China Unicom traffic, route each to its respective ISP, and enable seamless failover to the Telecom line if the Unicom link fails, using NAT, ACLs, and policy routing.
The article reviews common MySQL high‑availability solutions—including shared‑storage SAN, DRBD disk replication, keepalived/heartbeat, MHA, ZooKeeper‑based HA, Galera/PXC clusters, and proxy middleware—detailing their architectures, advantages, limitations, and suitability for different business and operational requirements.
This article presents a practical dual‑master MySQL high‑availability solution using keepalived and custom shell scripts that reliably detect master health, perform graceful VIP failover, and safely switch back after repairs, while ensuring data consistency and minimal downtime.
This comprehensive guide explains how SQL Server log shipping works, details the roles of primary, secondary, and monitor servers, walks through each job type, discusses execution intervals and data‑loss implications, and provides step‑by‑step failover and troubleshooting procedures.
This article explores practical MySQL high‑availability solutions, covering asynchronous and semi‑synchronous replication, monitoring with keepalived or Zookeeper, failover decision criteria, GTID and pseudo‑GTID techniques, and lessons learned from real‑world deployments.
This article explains why the DBMP platform was created to automate MySQL operations, describes its architecture and key features such as host management, instance groups, backup, slow‑query handling, and scheduled tasks, and outlines future optimization directions and common technical Q&A.
This guide explains how to create a high‑availability PostgreSQL cluster on two hosts using streaming replication, automatic failover and failback, dual virtual IPs, heartbeat monitoring, and stress testing, with full configuration scripts and practical test results.
The article explains how to create an application‑level interface group for DDBoost to aggregate multiple Data Domain IP interfaces into a private network group, achieving load balancing, fault‑tolerant data transfer, and notes performance considerations such as avoiding mixed‑capacity links.
This article discusses MySQL high‑availability solutions, covering asynchronous and semi‑synchronous replication, monitoring with keepalived, Zookeeper, and custom agents, failover procedures using binlog positions, GTID and pseudo‑GTID techniques, and the author's practical experiences and future plans.
Redis Sentinel provides a high‑availability solution for Redis by continuously monitoring master and replica servers, automatically promoting a replica to master when the original master fails, and seamlessly handling failover and recovery to keep the system operational without manual intervention.
The article explains why Zookeeper is a crucial component for implementing master‑slave high‑availability architectures in distributed systems, detailing how temporary nodes, sequence numbers, and cluster coordination eliminate single points of failure and enable reliable failover for write services.
At Baidu’s 49th Technical Salon, Cheng Yishi explained how the company revamped its MooseFS and Redis systems by adding a Shadow Master to split reads from writes, introducing Slave nodes for failover, and deploying a Redis proxy middleware, thereby dramatically improving performance, scalability, and high‑availability for critical services.
