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Hectal

Part 0

Foundations of State

Why databases, queues, and caches are harder to run than web servers, and the ideas every one of them is built on.

Every system in this guide solves the same few problems in different ways: keeping data safe when a disk or machine dies (durability), keeping copies on several machines (replication), deciding what a reader sees while copies disagree (consistency), and getting data back when everything else fails (backups). Learn these once here and the rest of the course becomes 'how does Kafka/Redis/Postgres answer these questions?'.

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  1. 0.1

    Why State Is Hard: Durability, Replication, Consistency

    Beginner

    What 'stateful' really means, how data survives crashes, why we copy it, and the trade-offs (CAP, PACELC, quorums) that every distributed data system makes.

    35 min · 2 lab steps · 2 drills

  2. 0.2

    Running Stateful Workloads: Disks, Kubernetes, Operators, Managed Services

    Intermediate

    Where stateful systems actually run: disk types and IOPS, StatefulSets and persistent volumes, operators that automate day-2 work, and when to just pay for a managed service.

    45 min · 3 lab steps · 2 drills

  3. 0.3

    Backups, Restores, and Disaster Recovery

    Intermediate

    RPO and RTO, snapshots vs logical vs continuous backups, point-in-time recovery, the 3-2-1 rule, Velero for Kubernetes, and why an untested backup doesn't count.

    40 min · 3 lab steps · 2 drills