Production-minded guidance for Amazon DynamoDB: core concepts, repeatable patterns, two end-to-end examples (E-commerce & Social/Activity Feed), runnable HTTP queries, sample data (CSV/JSONL), Mermaid diagrams, and production checklists.
Live site: https://wowlabz.github.io/dynamodb-playbook/
- Concepts — PK/SK modeling, item collections, LSI vs GSI, conditional/idempotent writes, transactions vs conditionals, migrations, security, error taxonomy.
- Examples
- E-commerce: Orders, Lines, Payments, Shipments, Inventory (GSI1 OrdersByUser; GSI2 OrdersByStatus; conditional inventory).
- Feed: Posts, Likes, Comments, Tags, Followers, Notifications (GSI1 PostsByAuthor; GSI2 PostsByTag; GSI3 FeedByUser + fan-out).
- Samples — Clean CSVs + JSONL seeds to make the patterns concrete.
- Queries — SigV4-ready
.httppayloads for Get/Query/Put/Update with conditions and pagination. - Diagrams — Access-pattern matrices, key-design cheat sheets, and shared cross-cutting visuals.
- Checklists — Design Review, Security/IAM, Observability/Ops, Cost Alarms, DR/Backup, Migration & Evolution.
- Open the site → https://wowlabz.github.io/dynamodb-playbook/
- Skim Concepts → understand keys, indexes, conditional writes, streams, and migrations.
- Pick an example → browse its Samples, Access Patterns, Diagrams, and Queries.
- Run the queries → copy from
docs/assets/samples/*/queries.httpinto your REST client (SigV4) or adapt to AWS CLI/SDK. - Before shipping → walk through Production Checklists.
docs/
index.md # Home
concepts.md # Core concepts (with shared diagrams)
downloads.md # Raw Assets & Downloads
ecom/
index.md # Overview
samples.md # Inline tables for CSVs (links to raw)
access-patterns.md # Patterns table + notes
diagrams.md # Renders A1–A7
queries.md # How to run queries.http
feed/
index.md
samples.md
access-patterns.md
diagrams.md
queries.md
assets/
samples/
ecom/ (...csv, seed.jsonl, queries.http, helpers.{py,ts})
feed/ (...csv, seed.jsonl, queries.http, helpers.{py,ts})
diagrams/
ecom/ A1_access-pattern-matrix.mmd, A2_key-design-cheatsheet.mmd, ...
feed/ B1_..., B2_..., ...
shared/ C1_partition-bookshelf.png, C2_lsi-vs-gsi.mmd, ... C7_security-scope.mmd
checklists/
design-review.md, security-iam.md, observability-ops.md, ...
styles/, overrides/, js/ # MkDocs Material branding & mermaid init
mkdocs.yml # Site configuration
# 1) Install
pip install mkdocs mkdocs-material pymdown-extensions
# 2) Serve locally
mkdocs serve
# http://127.0.0.1:8000
# 3) Build static site (optional)
mkdocs buildDiagrams use Mermaid via MkDocs Material; no extra build step needed.
If you prefer PNGs for diagrams, export from the.mmdsources underdocs/assets/diagrams/*.
- CSV/JSONL: load into your scripts/tests or use as mental models for item shapes and key design.
queries.http: run with a client that supports AWS SigV4 (or translate to AWS CLI/SDK).- Helpers:
helpers.py/helpers.tsinclude small key/shard helpers you can reuse.
- Fork and create a feature branch.
- Keep access patterns and diagrams in sync with sample CSVs.
- Prefer Mermaid for diagrams; place sources under
docs/assets/diagrams/.... - Run
mkdocs serveand preview before opening a PR.
Copyright © Wow Labz.
Docs and examples are provided for educational and internal enablement purposes.