Easy Learn
A complete, beginner-to-production guide to Apache Kafka: what problem it solves, how brokers, topics, partitions, consumer groups, KRaft, and replication actually work under the hood, real Java + Spring Boot code, inline SVG diagrams, and lessons from Netflix, Uber, LinkedIn, Airbnb, and Walmart.
The Least Recently Used (LRU) cache eviction policy is one of the oldest, simplest, and most trusted ideas in computer science: when a fixed-size cache runs out of space, throw away whichever item has gone the longest without being touched. Under that one-line rule sits a surprisingly deep piece of…
A ground-up tour of the database object that stores the actual answer to a query — regular views vs materialized views; base tables, staleness, and query rewrite; full and incremental refresh; refresh timing models from on-demand to streaming; MVCC-based concurrent refresh and copy-and-swap; incremental view maintenance and delta rules; the…
A beginner-to-production deep dive into master-slave (now primary-replica) database replication: the single-librarian analogy for why one machine cannot serve everyone forever, a six-milestone historical arc from 1970s mainframes through late-1980s enterprise log shipping, early-2000s MySQL binlog, mid-2000s PostgreSQL WAL streaming, 2010s managed cloud offerings, and the c.2020 industry-wide terminology shift…
A beginner-friendly, deep-dive guide to load testing tools — what they do, how they work internally, how to script them (k6, Locust, JMeter, Gatling), how to run them in CI/CD, and how the biggest engineering teams (Netflix, Amazon, Uber, banks and ticketing platforms) rely on them to survive their peak-traffic…
A complete, beginner-to-production guide to optimistic locking: what it is, why it exists, and how modern databases, ORMs, REST APIs, and distributed systems use it to let many users safely change the same data at the same time. Traces the history from H.T. Kung and John T. Robinson’s 1981 paper…
A beginner-to-production guide to message brokers — what they are, why they exist, how queues vs topics work, how partitioning and replication scale them, how to run one in production, and how to avoid the classic mistakes. With inline SVG diagrams, Java + Spring Boot code samples, and real-world examples…
A beginner-to-production deep dive comparing message queues and topics (publish-subscribe) in distributed systems: the coffee-shop-token vs radio-broadcast analogy for one-consumer-per-message vs every-subscriber-gets-a-copy, and a nine-milestone historical arc (1993 IBM MQSeries, 1994 TIB/Rendezvous, 1999 JMS, 2004 AMQP/RabbitMQ, 2006 SQS, 2011 Kafka, 2012 SNS, 2015 Google Pub/Sub, 2017 Azure Service Bus Topics…
A complete, beginner-to-production guide to message deduplication: why duplicate messages are an unavoidable fact of life in distributed systems, and how production platforms like Kafka, Amazon SQS, Stripe, Uber, and Netflix stop the same event from being processed twice. The guide opens with the classic “double-tap the send button” analogy,…
A ground-up tour of the numeric “measurements over time” that power every green graph and red alert — counters, gauges, histograms, and summaries; push vs pull collection; the five-layer metrics pipeline; JWT-style time-series storage in a TSDB; cardinality discipline, downsampling, write-ahead logs; the four golden signals, RED, USE, SLIs/SLOs/error budgets;…