ml-system-design

# ML System Design

This skill provides frameworks for designing production machine learning systems, from data pipelines to model serving.

## When to Use This Skill

**Keywords:** ML pipeline, machine learning system, feature store, model training, model serving, ML infrastructure, MLOps, A/B testing ML, feature engineering, model deployment

**Use this skill when:**

- Designing end-to-end ML systems for production
- Planning feature store architecture
- Designing model training pipelines
- Planning model serving infrastructure
- Preparing for ML system design interviews
- Evaluating ML platform tools and frameworks

## ML System Architecture Overview

### The ML System Lifecycle

```text
┌─────────────────────────────────────────────────────────────────────────┐
│                        ML SYSTEM LIFECYCLE                               │
├─────────────────────────────────────────────────────────────────────────┤
│                                                                          │
│  ┌──────────┐   ┌──────────┐   ┌──────────┐   ┌──────────┐   ┌────────┐ │
│  │  Data    │──▶│ Feature  │──▶│  Model   │──▶│  Model   │──▶│ Monitor│ │
│  │ Ingestion│   │ Pipeline │   │ Training │   │ Serving  │   │ & Eval │ │
│  └──────────┘   └──────────┘   └──────────┘   └──────────┘   └────────┘ │
│       │              │              │              │              │      │
│       ▼              ▼              ▼              ▼              ▼      │
│  ┌──────────┐   ┌──────────┐   ┌──────────┐   ┌──────────┐   ┌────────┐ │
│  │  Data    │   │ Feature  │   │  Model   │   │ Inference│   │ Metrics│ │
│  │  Lake    │   │  Store   │   │ Registry │   │  Cache   │   │  Store │ │
│  └──────────┘   └──────────┘   └──────────┘   └──────────┘   └────────┘ │
│                                                                          │
└─────────────────────────────────────────────────────────────────────────┘
```

### Key Components

| Component | Purpose | Examples |
| --------- | ----