# Ddia Architecture

> Foundational architectural concepts for data-intensive applications, distilled from "Designing Data-Intensive Applications" (Kleppmann, 2nd ed) chapters 1-2. Covers the operational vs analytical split, cloud vs self-hosted trade-offs, distributed systems trade-offs, and the core nonfunctional requirements (performance, reliability, scalability, maintainability). Use this skill when: - Choosing between OLTP (operational) and analytical (OLAP) storage - Deciding cloud vs self-hosted / managed service vs build-your-own - Evaluating distributed (microservices, multi-node) vs single-node architectures - Defining performance SLOs and reasoning about response-time percentiles - Designing for reliability, defining a fault model, and choosing fault tolerance strategies - Planning capacity / scalability and choosing scale-up vs scale-out - Architecting for long-term maintainability (operability, simplicity, evolvability) - Reviewing an architecture proposal against DDIA fundamentals

- Skill: `ebarti/ddia-architecture` (Agent Skill, multi-file: 26 files)
- Install (CLI): `npx skillmds@latest add ebarti/ddia-architecture`
- Raw SKILL.md: https://api.skillmd.com/api/skills/ebarti/ddia-architecture/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: DevOps & Infra
- Author: ebarti (https://skillmd.com/u/ebarti)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/ebarti/ddia-architecture

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# DDIA Architecture

Foundational concepts every data-intensive system architect needs: how operational and analytical systems differ, when to use cloud vs self-hosted, when to distribute, and how to reason about performance, reliability, scalability, and maintainability. Built from chapters 1-2 of "Designing Data-Intensive Applications" (Kleppmann, 2nd ed).

## Quick Start

1. Read `guidelines.md` first — it routes you from your task or symptom to the right files.
2. Load only the files relevant to your task (each category has `knowledge.md`, `rules.md`, `examples.md`).
3. Apply the concepts to the architecture decision at hand.

## Contents

### References

| Category | Files | Purpose |
|----------|-------|---------|
| `references/operational-vs-analytical/` | knowledge, rules, examples | OLTP vs OLAP; warehouses, lakes, lakehouses; system of record vs derived data |
| `references/cloud-vs-self-hosted/` | knowledge, rules, examples | Build vs buy; IaaS/PaaS/SaaS; cloud-native vs on-prem trade-offs |
| `references/distributed-systems-intro/` | knowledge, rules, examples | When to distribute; partial failure; microservices vs monolith vs serverless |
| `references/performance/` | knowledge, rules, examples | Response time vs throughput; percentiles; tail latency; SLOs/SLAs |
| `references/reliability/` | knowledge, rules, examples | Fault vs failure; fault tolerance; hardware/software/human faults |
| `references/scalability/` | knowledge, rules, examples | Load parameters; scale-up vs scale-out; shared-nothing |
| `references/maintainability/` | knowledge, rules, examples | Operability, simplicity, evolvability; abstractions; legacy systems |

### Workflows

| Task | Workflow |
|------|----------|
| Decide cloud vs self-hosted deployment | `workflows/choosing-cloud-vs-self-hosted.md` |
| Define performance SLOs (latency, throughput, error budget) | `workflows/defining-performance-slos.md` |
| Assess reliability requirements & identify SPOFs | `workflows/assessing-reliability-requirements.md` |

## Guidelines

See `guidelines.md` for:
- Task-based file selection (architecture decisions, capacity planning, operational design)
- Symptom/question lookup ("latency is unpredictable", "system breaks on deploy", etc.)
- Topic index with paths to every reference file
- Decision tree for common architecture questions
- Complete file index