Easy Learn
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;…
A beginner-to-production comparison of RabbitMQ and Apache Kafka — why they exist, how push-vs-pull, delete-after-ack vs retain-and-replay, exchanges vs partitions, quorum queues vs KRaft actually differ under the hood, and how to pick the right one (or both) for your architecture.
A complete, beginner-to-production walkthrough of multi-region deployment: the many-kitchens pizza analogy and the 1990s-to-today evolution timeline (single data center, multi-server single site, mid-2000s CDNs, 2010s cloud regions, 2015+ compliance-driven multi-region), why the speed of light and two-thirds signal velocity through fiber make it a physics problem rather than a code…
A beginner-to-production deep dive into multi-cloud strategy — why teams run workloads across AWS, Azure and GCP, how the pipelines and data-replication flows actually work, the real trade-offs, and how organisations like Netflix, Spotify, Snap and large regulated banks combine clouds in practice.
A ground-up tutorial on the three pillars of observability — metrics, logs, and traces — from the shift out of monoliths into microservices, through OpenTelemetry, W3C Trace Context, structured logging, spans, sampling, exemplars, PromQL, the RED and USE methods, SLOs and error budgets, cardinality control, downsampling, HA and DR patterns…
A complete, beginner-friendly walkthrough of what “the cloud” actually is, how it works under the hood, why it took over modern computing, and how the engineers at Netflix, Amazon, and Uber use it every single day. Opens with the taxi-versus-car and public-utility-versus-backyard-generator analogies to explain that cloud computing means using…
A complete, beginner-friendly walkthrough of one of the most repeated questions in system design: why the world’s largest, busiest, most important computer systems almost always choose to grow sideways — adding more ordinary machines — rather than upward, by piling ever-more power onto one extraordinary machine. Opens with a neighbourhood…
A complete, beginner-friendly walkthrough of one of the most famous jokes in computer science — that there are only two truly hard problems: naming things, and cache invalidation. This guide is entirely about the second one, and treats it seriously rather than as a punchline. Opens with a whiteboard on…
A complete, ground-up tutorial on message queues: introduction and history (from 1970s mainframe middleware and IBM MQ through JMS, ActiveMQ, RabbitMQ, Kafka, and today’s managed cloud services), the problem and motivation, eight core concepts (message, producer, consumer, broker, queue, topic, acknowledgment, dead letter queue), full architecture, internal working for both…
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…