Tag archive

#consistency

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16 articles

Distributed Transactions Part 1: The Death of ACID

Distributed Transactions Part 1: The Death of ACID In a monolith, data consistency is easy. You wrap your code in a database transaction, and the database guarantees that either everything happens or nothing happens. In…

Apr 20, 20262 min read

Deep DiveDistributed Transactions Mastery

#distributed-transactions#acid#microservices

System DesignAdvanced

Distributed Transactions Part 3: The Saga Pattern

Part 3: The Saga Pattern When a workflow spans multiple microservices, a single ACID transaction across all services is usually impractical. The Saga pattern solves this by composing local transactions, each with compens…

Apr 20, 20262 min read

Deep DiveDistributed Transactions Mastery

#saga-pattern#microservices#consistency

System DesignExpert

Distributed Snapshots: Chandy-Lamport Algorithm

Distributed Snapshots: Chandy-Lamport How do you take a "global photo" of a system where every node has a different time and no central master? 1. The Problem You need to save the state of a system for debugging or check…

Apr 20, 20262 min read

Deep DiveReliability Engineering Mastery

#distributed-systems#snapshot#chandy-lamport

MessagingExpert

Exactly-Once Semantics: The Mathematical Impossibility

Exactly-Once: The Mathematical Impossibility Exactly-once processing is impossible in a distributed system because you cannot guarantee the delivery of the (acknowledgement) over an unreliable network. 1. The Two General…

Apr 20, 20261 min read

PlaybookKafka Production Playbook

#exactly-once#kafka#distributed-systems

DatabasesAdvanced

Hybrid Logical Clocks (HLC): Solving Distributed Time & Causality

Hybrid Logical Clocks (HLC): Mastering Time In a distributed system, time is a lie. Due to Clock Drift, no two servers have perfectly synchronized clocks. If Server A records an event at 10:00:01 and Server B records a s…

Apr 20, 20262 min read

Deep DiveDistributed Systems Mastery

#distributed-systems#hlc#causality

System DesignAdvanced

Linearizability vs. Sequential Consistency: A Developer's Guide to Correctness

Linearizability vs. Sequential Consistency If you use a "Consistent" database, what guarantees are you actually getting? In distributed computing, there are two major models of "Strong" consistency. 1. Linearizability (T…

Apr 20, 20263 min read

Deep DiveReliability Engineering Mastery

#distributed-systems#consistency#linearizability

System DesignAdvanced

Beyond CAP: Why PACELC is the Real Rule for Distributed Databases

Beyond CAP: Understanding the PACELC Theorem The CAP theorem (Consistency, Availability, Partition-tolerance) is a useful abstraction, but it only describes what happens when the network is broken. In the real world, the…

Apr 20, 20262 min read

Deep DiveBackend Systems Mastery

#distributed-systems#pacelc#cap-theorem

System DesignBeginner

Beyond CAP: The PACELC Theorem for Distributed Databases

Beyond CAP: Understanding the PACELC Theorem Most engineers know the CAP Theorem: in the presence of a network partition (P), you must choose between Consistency (C) and Availability (A). However, CAP only tells us what…

Apr 20, 20262 min read

Deep Dive

#distributed-systems#pacelc#cap-theorem

System DesignBeginner

The Saga Pattern: Managing Distributed Transactions in NoSQL

The Saga Pattern: Consistency Without Distributed Locks In a microservices architecture, a single business process (like "Order Placement") often spans multiple services and databases. Since NoSQL databases don't support…

Apr 20, 20262 min read

Deep Dive

#distributed-transactions#microservices#saga-pattern

System DesignAdvanced

System Design: Designing a Distributed File Lock (Zookeeper/Curator)

Designing a Distributed File Lock In a distributed environment, two instances of a service might try to modify the same shared file at the same time, leading to data corruption. While we have locks for databases (Redis/P…

Apr 20, 20262 min read

Deep Dive

#system-design#distributed-locking#zookeeper

System DesignExpert

Distributed Locking: The Danger of Fencing Tokens

Distributed Locking: The Danger of Fencing Tokens The most common failure in distributed locking is assuming that the lock is 100% secure. A system pause (e.g., a 2-second Garbage Collection pause in your Java app) can m…

Apr 20, 20263 min read

Deep DiveReliability Engineering Mastery

#distributed-systems#locking#consistency

System DesignAdvanced

System Design: Designing a Distributed Lock Manager

System Design: Designing a Distributed Lock Manager (DLM) In a microservices architecture, multiple instances of a service often need to access a shared resource (like an inventory item or a single-use coupon) simultaneo…

Apr 20, 20263 min read

Deep Dive

#system-design#distributed-locking#redis

System DesignAdvanced

System Design: Designing a Distributed Lock Service

Designing a Distributed Lock Service Distributed locking is one of the most critical and complex infrastructure components. It provides a "global" synchronization mechanism that ensures resources (like file systems, data…

Apr 20, 20262 min read

Deep Dive

#system-design#distributed-locking#consistency

System DesignAdvanced

System Design: Distributed Transactions (2PC and 3PC)

Distributed Transactions: 2PC and 3PC Achieving ACID guarantees across multiple independent databases is the "Holy Grail" of distributed systems. While Sagas are popular for microservices, the classic protocols Two-Phase…

Apr 20, 20262 min read

Deep Dive

#system-design#distributed-transactions#2pc

System DesignAdvanced

System Design: Managing Distributed Transactions with the Saga Pattern

System Design: Managing Distributed Transactions with the Saga Pattern In a monolithic architecture, a single database transaction guarantees ACID properties across all operations. In a microservices architecture, a sing…

Apr 20, 20263 min read

Deep Dive

#system-design#microservices#saga-pattern

MessagingAdvanced

The Transactional Outbox Pattern: Reliability in Microservices

The Transactional Outbox Pattern In a microservice, you often need to save data to a database (e.g., Order) and send an event to Kafka (e.g., OrderCreated). If the DB write succeeds but the Kafka send fails, your system…

Apr 20, 20262 min read

Deep DiveBackend Systems Mastery

#microservices#kafka#distributed-systems