Easy Learn
A complete, beginner-to-production guide to eventual consistency in system design: the texting-with-bad-signal analogy and a plain-English definition; a short history from the 1990s research literature through Amazon Dynamo (2007), Google Bigtable, Cassandra, and Voldemort; why replication exists and the two possible answers when copies disagree (strong vs eventual consistency); the…
A complete, beginner-to-interview-ready tutorial on graceful degradation – the design approach that lets a system deliberately reduce features or quality in a controlled, planned way rather than failing completely. Uses the four-engine airplane analogy to introduce the mindset shift from “prevent every failure” to “plan the reduced experience in advance,”…
A first-principles guide to the single most important trade-off in distributed systems: strong consistency versus eventual consistency. Covers the history and physical motivation, all the vocabulary (linearisability, causal, read-your-writes, session, bounded staleness), the CAP theorem and PACELC extension, architecture components (replicas, leader-follower, leaderless, quorums N/W/R, vector clocks), how strongly and…
A complete, beginner-friendly guide to strong consistency in distributed systems. Covers: what strong consistency really is and its short history, the problem it solves, the shared-notebook analogy, core terminology (consistency, replication, quorum, consensus, linearizability, eventual consistency), the full consistency spectrum from strong to eventual, the six-component architecture behind it, the…
A complete, beginner-to-production tutorial on sharding versus replication in distributed databases: why the topic matters and the short history of horizontal scaling, the three failure modes of a single database and how each technique attacks a different one, precise definitions of nodes, replicas, and shards, a CAP-theorem foundation with consistency…
A complete, beginner-to-production tutorial on database replication – what it is, why it exists, how it works internally, and how it is used in every serious modern system. Covers the notebook analogy and the full history from 1970s single-machine relational databases through the birth of primary-backup in the 1980s-90s, the…
A complete, beginner-friendly walkthrough of what a disadvantage of microservices actually means in practice: the toy-box analogy for one giant box versus many small boxes; a short history from 1990s-2000s monoliths through the 2011-2014 James Lewis and Martin Fowler microservices article; the specific pains that microservices tried to fix (slow…
A first-principles guide to data sharding: what it is, why systems need it, and how they decide where data lives. Covers all five common strategies (range-based, hash-based, consistent hashing with virtual nodes, directory-based, and geographic/attribute-based) with worked Java code, sequence and ring diagrams, and honest trade-offs. Includes the routing architecture,…
A complete, beginner-friendly guide to database sharding. Covers: what sharding is and its history, the problem it solves (single-server scaling limits, vertical vs horizontal scaling, sharding vs replication), the core vocabulary (shard, shard key, logical vs physical shard, shard map, rebalancing, cross-shard queries), production architecture and routing options, the five…
A complete, from-zero, book-style tutorial answering “what is the main advantage of microservices over a monolith?” — with analogies, diagrams, Java code, and real production stories from Netflix, Amazon, Uber, Spotify, and the Amazon Prime Video counter-example. Covers history, the ShopEasy motivation example, core concepts (coupling, cohesion, bounded contexts, deployment…