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Systems Fundamentals

How computers actually work underneath the abstractions.

11 posts · Engineering

  1. 1

    Systems Fundamentals: The Skills That Outlast Every Framework

    Why systems fundamentals like latency, storage, and the four pillars stay useful for decades while frameworks churn - and how to use them to build faster.
  2. 2

    How a Computer Actually Runs Your Code: CPU, Memory & Threads

    See how a computer runs your program, from source code to CPU, memory, and threads, and turn performance guesswork into real, confident understanding.
  3. 3

    Concurrency vs Parallelism: How Computers Juggle Tasks

    Concurrency vs parallelism, explained simply. Learn how computers juggle many tasks, why race conditions happen, and which tool fits I/O vs CPU work.
  4. 4

    Relational Databases, SQL & ACID Explained Simply

    Learn how relational databases, SQL, and ACID transactions keep your data correct under load - with clear examples, common mistakes, and practical tips.
  5. 5

    How Databases Find One Row in a Billion (Without Reading Them All)

    How database indexes find one row in a billion almost instantly. A clear guide to pages, B-trees, LSM-trees, and writing queries that stay fast.
  6. 6

    Scaling a Database: Replication, Sharding & NoSQL Explained

    Learn how to scale a database past one server with replication, partitioning, and NoSQL - and why reads are easy to scale but writes are genuinely hard.
  7. 7

    How Data Travels the Internet: IP, TCP, UDP & DNS

    A clear, practical guide to how data travels the internet: IP, TCP, UDP, and DNS explained in plain language so you can debug slow, hung, and flaky apps.
  8. 8

    How the Web Really Works: HTTP, TLS, Load Balancing & Caching

    A clear, practical tour of the web stack: how HTTP requests work, why HTTPS is safe, what load balancers and CDNs do, and how caching makes sites fast.
  9. 9

    Distributed Systems Explained: Why Many Computers Act as One

    A distributed system makes many computers behave as one. Learn partial failure, CAP, consistency, consensus, and idempotency in plain, practical language.
  10. 10

    Data Engineering Explained: How Data Moves at Scale

    Learn how data engineering moves and shapes data at scale - OLTP vs OLAP, ETL vs ELT, Kafka, lakehouses, and idempotent pipelines, explained in plain English.
  11. 11

    System Design Trade-offs: How to Reason About Any System

    Learn the repeatable system design process: back-of-envelope estimates, the five universal trade-offs, idempotency, and how to reason about any system.