Bean & Bark: learn DynamoDB by doing

Meet Bean & Bark — a coffee roaster whose entire store lives in one DynamoDB table. You're the new hire. Chapter by chapter a real problem lands on your desk, and you solve it with a query — learning DynamoDB by doing, on a dataset with actual stories hidden in it. The story runs in two acts: first you learn the table; then, a year later, the company grows past asking every question through it.

This isn't a syllabus of features. Each chapter is a situation: the founder needs an answer before a meeting, a region's revenue has slipped, a cleanup has to run against live data, a standing report needs its own key. You write the query, and the studio shows you exactly what it costs and what it would change — the same disclosure you'd rely on for real work.

Act one runs against your own DynamoDB — a local one on your laptop is ideal: free, offline, nothing to provision. No AWS account required to follow along. New to this? Start with Set up the table — it creates BeanAndBark and loads the sample in a couple of minutes. Then start at the top and use the Next button, or jump to the job you have right now:

Start here — learn the table

One year later — the store outgrew one access path

Act two picks the story up after a year of growth: the table is 40× bigger, and the questions stop fitting through the base key. The table didn't fail — the company outgrew asking every question through one door. These chapters run Professional capabilities against your own AWS (background fleets, managed backups, OpenSearch, S3 Tables replicas, vector indexes), so they're written to be read: every run's receipt is shown exactly as the studio discloses it, and the free sample stays act one's playground.