Instrument one small app with a counter and a histogram, run Prometheus 3.x in Docker Compose, and answer how much, how broken, and how slow with three PromQL queries. Part 2 of a series.
What observability is, how it differs from monitoring, what metrics, logs, and traces each answer, and the vocabulary (SLOs, RED, USE, golden signals) to learn before you pick a tool. Part 1 of a series.
A jargon-free introduction to containerization — what containers, images, and registries actually are; how Docker Desktop and Kubernetes fit in; and the failure modes containers do not solve.
A jargon-free introduction to ETL — what Extract, Transform, and Load actually mean; the vocabulary defined without hand-waving; concrete examples; and how to decide when an organization actually needs one.
A jargon-free introduction to data models and data modeling — what a data model actually is, how they’re typically represented (ER diagrams, relational schemas, JSON structures, dimensional models), and why deciding the shape of your data before writing the code that manipulates it is usually the cheapest work you’ll do all quarter.