MongoDB Learning Labs Documentation
A structured, incremental learning path to master MongoDB — from document model fundamentals to sharding and security.
📌 Quick Links
- GitHub Repository — Source code, Docker setup, and lab files
- Labs Overview — All 11 hands-on lab exercises
- Interview Prep — Q&A and revision guide
🚀 Getting Started
1. Start the MongoDB Cluster
cd docker && ./start.sh
OR
cd docker && docker compose up -d
mongo1, mongo2, mongo3) + Mongo Express UI at http://localhost:8081.
2. Run a Lab
docker exec -it mongo1 mongosh --file /labs/01_database_basics.js
OR, open the notebook in notebooks/ and run it with Jupyter or Pycharm.
### 3. Interactive Shell
```bash
docker exec -it mongo1 mongosh
# or from host (requires mongosh installed):
mongosh "mongodb://127.0.0.1:27017/mongo_labs?directConnection=true"
4. View These Docs Locally
pip install -r requirements.txt
mkdocs serve
# open http://localhost:8000
📚 Learning Path
| Step | Resource | Description |
|---|---|---|
| 1 | NoSQL & MongoDB | Document model, CAP theorem, when to use MongoDB |
| 2 | Core Concepts | BSON, replica sets, ObjectId, collections |
| 3 | Data Modeling | Embedding vs referencing, schema patterns |
| 4 | Indexes & Aggregation | Index types, pipeline stages |
| 5 | Transactions & Consistency | ACID, read/write concerns |
| 6 | TTL & Change Streams | Data expiry, real-time events |
| 7 | Advanced Aggregation | $lookup, $facet, $graphLookup |
| 8 | Advanced Topics | Sharding, security, monitoring |