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Xiaokun's Architecture Exploration Notes
Xiaokun's Architecture Exploration Notes
Jul 27, 2025 · Fundamentals

Can Multi-Leader and Leaderless Replication Achieve Linear Consistency?

This article examines why multi‑leader and leaderless replication models struggle to provide linear consistency, explores write‑conflict handling, quorum‑based NWR mechanisms, sloppy quorum and hinted‑handoff techniques, and summarizes the trade‑offs involved in achieving strong consistency across distributed data centers.

Distributed SystemsMulti-LeaderReplication
0 likes · 15 min read
Can Multi-Leader and Leaderless Replication Achieve Linear Consistency?
FunTester
FunTester
Apr 28, 2024 · Backend Development

Tackling Data Consistency: Master‑Slave, Master‑Master & Leaderless Architectures

The article examines why distributed systems inevitably face data‑consistency challenges and breaks down three common service‑architecture patterns—master‑slave, master‑master, and leaderless—detailing their replication mechanisms, advantages, drawbacks, and practical solutions such as synchronous, semi‑synchronous, asynchronous replication, quorum handling, node‑failure recovery, and conflict resolution strategies.

Data ConsistencyDistributed SystemsMaster‑Slave
0 likes · 14 min read
Tackling Data Consistency: Master‑Slave, Master‑Master & Leaderless Architectures
Architect's Guide
Architect's Guide
Sep 23, 2022 · Fundamentals

Key Distributed System Design Patterns and Concepts

This article introduces essential distributed system design patterns such as Bloom filters, consistent hashing, quorum, leader‑follower architecture, heartbeat, fencing, write‑ahead logs, segmented logs, high‑water marks, leases, gossip protocol, Phi failure detection, split‑brain handling, checksums, CAP and PACELC theorems, hinted handoff, read repair, and Merkle trees, explaining their purpose and operation.

CAP theoremMerkle Treebloom-filter
0 likes · 13 min read
Key Distributed System Design Patterns and Concepts
IT Architects Alliance
IT Architects Alliance
Sep 2, 2022 · Fundamentals

Key Distributed System Concepts: Bloom Filter, Consistent Hashing, Quorum, Leader/Follower, and More

This article introduces essential distributed‑system concepts—including Bloom filters, consistent hashing, quorum, leader/follower roles, heartbeats, fencing, WAL, segment logs, high‑water marks, leases, gossip protocol, Phi failure detection, CAP and PACELC theorems, hinted handoff, read repair, and Merkle trees—explaining their purpose and how they are applied in systems such as BigTable, Cassandra, Dynamo, and Kafka.

CAP theoremDistributed SystemsMerkle Tree
0 likes · 12 min read
Key Distributed System Concepts: Bloom Filter, Consistent Hashing, Quorum, Leader/Follower, and More
Meituan Technology Team
Meituan Technology Team
Aug 25, 2022 · Databases

Data Replication in Distributed Systems – Part 1: Models, Challenges, and Design Considerations

The article surveys three data‑replication models—master‑slave, multi‑master, and leaderless—explains how they enable scalability and fault‑tolerance, and examines core distributed‑system challenges such as partial node failures, unreliable networks, and unsynchronized clocks, while stressing safety‑liveness trade‑offs and design techniques like quorum and timeouts.

ConsistencyDistributed SystemsKafka
0 likes · 37 min read
Data Replication in Distributed Systems – Part 1: Models, Challenges, and Design Considerations
Architecture Digest
Architecture Digest
Jul 14, 2022 · Fundamentals

Key Distributed System Concepts: Bloom Filter, Consistent Hashing, Quorum, Leader/Follower, and More

This article explains essential distributed‑system concepts such as Bloom filters, consistent hashing, quorum, leader/follower roles, heartbeats, fencing, write‑ahead logs, segmented logs, high‑water marks, leases, gossip protocols, Phi accrual failure detection, split‑brain handling, checksums, the CAP and PACELC theorems, hinted handoff, read repair, and Merkle trees, illustrating each with practical examples and diagrams.

CAP theoremMerkle Treebloom-filter
0 likes · 12 min read
Key Distributed System Concepts: Bloom Filter, Consistent Hashing, Quorum, Leader/Follower, and More
ITPUB
ITPUB
Jun 10, 2022 · Operations

How Zookeeper Prevents Split‑Brain Failures in Distributed Clusters

This article explains the split‑brain phenomenon in distributed systems, illustrates how it can occur in Zookeeper clusters, and details Zookeeper's quorum‑based solutions—including majority voting, odd‑node deployment, and additional safeguards—to avoid split‑brain and ensure reliable leader election.

Distributed SystemsSplit-Brainleader election
0 likes · 11 min read
How Zookeeper Prevents Split‑Brain Failures in Distributed Clusters
Top Architect
Top Architect
Sep 26, 2021 · Fundamentals

Fundamentals of Distributed Systems: Concepts, Replication, Consistency, and Protocols

This article provides a comprehensive overview of distributed system fundamentals, covering system models, node concepts, failure types, replication strategies, consistency levels, data distribution methods, replica control protocols such as primary‑secondary, two‑phase commit, lease‑based caching, quorum, MVCC, Paxos, and the CAP theorem.

ConsistencyDistributed SystemsLease
0 likes · 54 min read
Fundamentals of Distributed Systems: Concepts, Replication, Consistency, and Protocols
Senior Brother's Insights
Senior Brother's Insights
Jul 28, 2021 · Operations

How Zookeeper Prevents Split‑Brain: Inside Quorum‑Based Leader Election

This article explains the split‑brain phenomenon in distributed clusters, uses Zookeeper as a case study to illustrate how network partitions can create multiple leaders, and details Zookeeper's majority‑quorum mechanism, node count considerations, and common strategies for avoiding split‑brain scenarios.

Cluster ManagementDistributed SystemsSplit-Brain
0 likes · 13 min read
How Zookeeper Prevents Split‑Brain: Inside Quorum‑Based Leader Election
Top Architect
Top Architect
Apr 24, 2021 · Fundamentals

Fundamentals of Distributed Systems: Models, Replication, Consistency, and Core Protocols

This article provides a comprehensive overview of distributed system fundamentals, covering node models, replica concepts, various consistency levels, data distribution strategies, lease-based caching, quorum mechanisms, two‑phase commit, MVCC, Paxos consensus, and the CAP theorem, illustrating each with practical examples and diagrams.

CAP theoremConsensusConsistency
0 likes · 54 min read
Fundamentals of Distributed Systems: Models, Replication, Consistency, and Core Protocols
Efficient Ops
Efficient Ops
Jan 5, 2021 · Operations

How to Prevent ZooKeeper Split‑Brain: Best Practices and Fault‑Tolerance Strategies

This article explains why ZooKeeper clusters should use an odd number of nodes, how the majority quorum mechanism avoids split‑brain scenarios, and outlines practical solutions such as quorums, redundant communication, fencing, arbitration, and disk‑lock techniques to ensure reliable distributed coordination.

Distributed SystemsSplit-BrainZooKeeper
0 likes · 14 min read
How to Prevent ZooKeeper Split‑Brain: Best Practices and Fault‑Tolerance Strategies
Architecture Digest
Architecture Digest
Nov 21, 2020 · Operations

Understanding and Handling ZooKeeper Split‑Brain Issues

This article explains the causes of ZooKeeper split‑brain situations, why odd‑numbered node deployments are preferred, how the quorum (majority) rule prevents split‑brain, and outlines practical methods such as quorum configuration, redundant communication, fencing, and pause‑before‑failover to handle and avoid the issue.

Cluster ManagementSplit-Brainhigh availability
0 likes · 13 min read
Understanding and Handling ZooKeeper Split‑Brain Issues
High Availability Architecture
High Availability Architecture
Oct 27, 2020 · Fundamentals

Quorum in Distributed Systems: Concepts, Variants, and Impact on Availability and Latency

Quorum, the core principle behind majority read/write and Paxos, can be defined in various ways—including weighted, hierarchical, and non‑majority quorums—to trade off system availability, latency, and fault tolerance, with examples illustrating how different quorum designs affect performance in distributed storage and coordination services.

AvailabilityConsensusDistributed Systems
0 likes · 18 min read
Quorum in Distributed Systems: Concepts, Variants, and Impact on Availability and Latency
Big Data Technology Architecture
Big Data Technology Architecture
Aug 13, 2019 · Fundamentals

Fundamentals of Distributed Systems: Models, Replicas, Consistency, and Protocols

This article introduces core concepts of distributed systems, covering node models, replica types, consistency levels, data distribution strategies, lease and quorum mechanisms, logging techniques, two‑phase commit, MVCC, Paxos, and the CAP theorem, providing a comprehensive overview for engineers and researchers.

CAP theoremLeaseProtocols
0 likes · 53 min read
Fundamentals of Distributed Systems: Models, Replicas, Consistency, and Protocols