MongoDB – 100+ Lab Exercises Roadmap (Basic, Intermediate, Advanced)

🔰 Basic Level (30+ Exercises)

 

Goal: Build foundational skills in NoSQL concepts, MongoDB basics, CRUD operations, and document structure.

 

Introduction to MongoDB & NoSQL

  • Install MongoDB on Windows/Linux/Mac.

  • Understand NoSQL vs. RDBMS.

  • Learn about documents, collections, databases.

  • Use MongoDB shell (mongosh) and Compass UI.

  • List databases and collections using show dbs, show collections.

CRUD Operations

  • Insert single and multiple documents (insertOne, insertMany).

  • Retrieve data with find(), use projections.

  • Update documents (updateOne, updateMany, $set, $inc).

  • Delete documents with deleteOne, deleteMany.

  • Use replaceOne and upserts.

Querying Documents

  • Use comparison operators ($eq, $gt, $lt, $in).

  • Apply logical operators ($and, $or, $not).

  • Filter documents using embedded document fields.

  • Sort, skip, and limit results.

  • Count documents in a collection.

Data Modeling Basics

  • Understand embedding vs. referencing.

  • Design basic schemas using nested documents.

  • Use _id fields and custom primary keys.

  • Create collections with validation rules.

  • Normalize vs. denormalize data structure in MongoDB.

 

🚀 Intermediate Level (40+ Exercises)

 

Goal: Enhance capabilities in indexing, aggregation, data modeling, schema design, and application integration.

 

Indexing & Performance

  • Create and drop indexes.

  • Use explain() to analyze query plans.

  • Create compound indexes and unique indexes.

  • Create text indexes for full-text search.

  • Optimize read performance with indexes.

Aggregation Framework

  • Use $match, $group, $sort, $project.

  • Work with $lookup for joins between collections.

  • Build pipelines with multiple stages.

  • Use $unwind for array flattening.

  • Perform conditional operations with $cond, $ifNull.

Schema Design & Validation

  • Apply schema validation using $jsonSchema.

  • Set up required fields, data types, and enums.

  • Apply data integrity rules at collection level.

  • Implement versioning for documents.

  • Design schema for multi-tenant applications.

Application Integration

  • Connect MongoDB with Node.js using Mongoose.

  • Create RESTful API with Express + MongoDB.

  • Integrate MongoDB with Python using PyMongo.

  • Store user session data in MongoDB.

  • Use MongoDB as a backend for MERN/MEVN stack apps.

 

🧠 Advanced Level (40+ Exercises)

 

Goal: Master MongoDB for production use—covering sharding, replication, security, backup strategies, and advanced analytics.

 

Replication & High Availability

  • Set up a replica set.

  • Configure primary-secondary nodes.

  • Test automatic failover.

  • Add and remove nodes from replica set.

  • Use rs.status() and rs.initiate().

Sharding & Horizontal Scaling

  • Configure a sharded cluster.

  • Understand shard key selection strategy.

  • Split and move chunks manually.

  • Use balancer and monitor data distribution.

  • Analyze sharded performance and consistency.

Security & Access Control

  • Set up authentication (SCRAM, x.509).

  • Create roles and assign privileges.

  • Use IP whitelisting and firewalls.

  • Enable and configure TLS/SSL encryption.

  • Audit user activity and queries.

Backup & Disaster Recovery

  • Use mongodump and mongorestore for snapshots.

  • Backup and restore replica sets.

  • Configure cloud backups using Atlas.

  • Test disaster recovery with restore scenarios.

  • Automate backups with scripts and cron.

Monitoring & DevOps

  • Monitor metrics using mongostat, mongotop.

  • Use MongoDB Atlas monitoring dashboard.

  • Integrate with Prometheus + Grafana.

  • Set up logging and log rotation.

  • Automate provisioning with Docker, Kubernetes.

Capstone Projects

 

  • Design and build a NoSQL database for a real-time chat app.

  • Create an e-commerce backend with advanced filtering and aggregation.

  • Deploy a sharded cluster on the cloud (AWS/GCP/Azure).

  • Secure and monitor a production-grade MongoDB instance.

  • Integrate MongoDB with Kafka or RabbitMQ for event-driven architecture.

 

✅ Tools & Technologies

 

  • MongoDB Shell (mongosh), Compass UI

  • Mongoose (Node.js ODM), PyMongo

  • MongoDB Atlas, Robo 3T, Studio 3T

  • Docker, Kubernetes, Helm

  • Prometheus, Grafana, Elastic Stack (ELK)

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