Discover | BestHub

Quick starts golang kubernetes observability distributed systems platform engineering mysql

Results

Matches for “raft”

134 results

Fundamentals Dec 29, 2020 Code Ape Tech Column

Understanding Distributed Consistency: CAP, BASE, 2PC, 3PC, Paxos, Raft, ZAB, and NWR Model

This article explains the challenges of distributed systems such as node failures and network anomalies, then introduces the CAP theorem, BASE theory, two‑phase and three‑phase commit protocols, and details consensus algorithms including Paxos, Raft, ZAB, and Amazon Dynamo's NWR model, highlighting their trade‑offs and practical usage.

distributed systemsCAP theorem2PCconsistencyRaftPaxos3PCZAB

Fundamentals Nov 26, 2020 Architecture Digest

Two-Phase Commit, Paxos, and Raft: Core Concepts and Workflows

This article explains the principles and workflows of Two‑Phase Commit, Paxos, and Raft, detailing their roles, phases, failure handling, and how they achieve distributed consensus in fault‑tolerant systems, including the coordinator‑participant model, proposal numbering, leader election, heartbeat mechanisms, and log replication processes.

AlgorithmsRaftPaxosDistributed ConsensusTwo-Phase Commit

Fundamentals Oct 23, 2020 Architecture Digest

Understanding Consistency Algorithms: Paxos, Raft, ZAB, and Gossip

This article explains why data consistency is essential in distributed systems, defines consistency, compares strong and eventual consistency, and details the design and operation of major algorithms such as Paxos, Multi‑Paxos, Raft, ZAB, and Gossip with illustrative examples and diagrams.

distributed-systemsalgorithmconsistencyraftpaxos

Fundamentals Sep 7, 2020 Xiaokun's Architecture Exploration Notes

How Raft Guarantees Strong Consistency: Leader Election & Log Replication Explained

This article provides a comprehensive overview of the Raft consensus algorithm, detailing its strong‑leader model, node states, leader election process, log replication mechanics, consistency checks, and single‑node configuration changes, while illustrating each concept with diagrams and code examples.

Distributed SystemsRaftConsensus AlgorithmLeader ElectionLog Replication

Cloud Native Jun 6, 2020 Java Architecture Diary

Explore Nacos 1.3.0: Embedded DB, New Raft Protocol, and High‑Availability

Nacos 1.3.0 introduces an embedded relational database, unified cluster management, an upgraded Raft consistency layer, security patches, Snowflake ID configuration, data migration guidance, new cluster addressing modes, and a set of Open‑API operations for Raft administration, all aimed at simplicity, performance, and high availability.

ConfigurationNacosSecurityEmbedded DatabaseCluster ManagementRaft

Fundamentals Apr 7, 2020 360 Tech Engineering

Implementing Raft in Go: Persistence, Optimizations, and Crash Scaling

This article, the fourth in a series on building a Raft consensus module in Go, explains how to add persistent state, improve command delivery semantics, optimize AppendEntries handling, and handle crash tolerance, while providing concrete Go code examples and practical testing tips.

OptimizationGoPersistenceRaftDistributed Consensus

Backend Development Mar 31, 2020 360 Tech Engineering

Implementing Raft Command Handling and Log Replication in Go

This article explains how to extend a Go implementation of the Raft consensus algorithm to handle client commands, replicate logs across the cluster, manage commit pipelines, and ensure election safety, while providing detailed code examples and discussion of underlying concepts.

backendDistributed SystemsGoRaftConsensusLog Replication

Backend Development Mar 20, 2020 360 Tech Engineering

Implementing Raft Election Mechanism in Go – Part 2

This article, the second in a series on Raft, explains the election mechanism, server states, timers, RPC handling, and partition scenarios while providing complete Go code examples for the consensus module and its interactions.

Distributed SystemsGolangGoRaftConsensusElection

Fundamentals Mar 10, 2020 360 Tech Engineering

Introduction to Raft: A Comprehensive Overview of the Distributed Consensus Algorithm

This article provides a thorough introduction to the Raft consensus algorithm, explaining its purpose, core components such as state machine replication, log and consensus module, leader‑follower model, client interaction, fault‑tolerance considerations, the CAP trade‑off, and why Go is a suitable implementation language.

GoFault ToleranceRaftDistributed ConsensusState Machine Replication

Fundamentals Mar 10, 2020 360 Zhihui Cloud Developer

Understanding Raft: A Beginner’s Guide to Distributed Consensus in Go

This article introduces the Raft distributed consensus algorithm, explains its core concepts such as replicated state machines, leader‑follower roles, client interaction, fault tolerance, the CAP trade‑off, and why Go is a suitable language for implementing Raft.

fault toleranceGo programmingRaftdistributed consensusstate machine replication

Previous Page 4 Next