CineDB: Building a Movie Catalog with DocumentDB 📽️

📘 Introduction

This project demonstrates how to set up Amazon DocumentDB (with MongoDB compatibility) inside a custom Amazon VPC and securely connect to it from an EC2 instance and covers end-to-end steps starting from network creation, security configuration, cluster provisioning, client setup, and finally performing CRUD (Create, Read, Update, Delete) operations using the MongoDB shell (mongosh).

The goal is to understand how a managed NoSQL database like Amazon DocumentDB is deployed and accessed in a real-world AWS environment.

🏗️ Architecture Overview

The architecture is based on a private Amazon DocumentDB cluster deployed inside a custom VPC. An EC2 instance placed in a public subnet acts as the client machine to connect securely to the DocumentDB cluster using security groups and TLS encryption.

Key ideas:

• DocumentDB runs inside private subnets
• EC2 client accesses it through security group–based rules
• Communication happens over port 27017 using TLSLS

🧩 Architecture Components

• Amazon VPC: Custom VPC for isolation and network control
• Public Subnet: Hosts the EC2 client instance
• Amazon DocumentDB Cluster: MongoDB-compatible NoSQL database
• Subnet Group: Defines subnets where DocumentDB can be deployed
• Security Groups:
  • DocumentDB cluster security group
  • DocumentDB client (EC2) security group
• Amazon EC2 (Amazon Linux 2): Client machine for database access
• MongoDB Shell (mongosh): Used to interact with DocumentDB
• TLS Certificate: Ensures encrypted communication

🎯 Why This Project?

• To understand how Amazon DocumentDB works in a secure VPC setup
• To learn networking and security concepts such as VPCs, subnets, and security groups
• To practice MongoDB-style CRUD operations on a managed AWS service
• To gain hands-on experience useful for cloud, DevOps, and database roles

✨ Key Features

• Secure DocumentDB cluster deployment
• Controlled access using security groups
• MongoDB-compatible operations using mongosh
• Full CRUD workflow on a sample movie catalog
• Proper cleanup of AWS resources to avoid unnecessary costs

🛠️ Execution Workflow

I. VPC and Subnet Configuration

• Open the AWS Management Console

• Search for VPC and open the VPC Dashboard

• Click Create VPC

• Set VPC name as documentdb-demo-vpc

• Keep all other settings as default

• Click Create VPC

• Once created, click View VPC

• Go to Subnets

• Select Public Subnet 1 and click edit subnet settings

• Enable Auto-assign public IPv4 address

• Save the subnet settings

II. DocumentDB Subnet Group Creation

• Search for Amazon DocumentDB and open its dashboard

• From the left menu, click Subnet groups

• Click Create subnet group and enter the following details:
  • Name: documentdb-subnet-group
  • Description: Subnet group for DocumentDB
  • VPC: Select the previously created VPC

• Add all subnets associated with this VPC

• Click Create subnet group

III. Security Group Configuration

A. DocumentDB Cluster Security Group

• Open EC2 → Security Groups

• Click Create security group, in Basic Details configure:
  • Security group name: documentdb-sg
  • Description: Security group for DocumentDB cluster
  • VPC: documentdb-demo-vpc

• Keep rest of the settings as defailt and click create security group

B. DocumentDB Client Security Group

• Click Create security group again and in Basic Details configure:
  • Security group name: documentdb-client-sg
  • Description: Security group for DocumentDB clients
  • VPC: documentdb-demo-vpc

• Add an inbound rule with the following configuration:
  • Type: SSH
  • Port Range: 22
  • Source: Anywhere-IPv4

• Click Create security group

C. Inbound Rule Configuration

• Open documentdb-sg and click edit inbound rules

• Click Add rule and configure:

  • Type: Custom TCP
  • Port range: 27017
  • Source: documentdb-client-sg

• Save the rules

IV. Amazon DocumentDB Cluster Creation

• Open Amazon DocumentDB

• Click Create cluster & select instance-based cluster

• In Cluster Configuration, configure:
  • Cluster identifier: movie-catalog-cluster
  • Engine version: 5.0

• Choose DB instance class: Memory optimized

• Keep cluster storage and connectivity settings as default

• Under Authentication, configure:
  • Username: docdbadmin
  • Enable Self-managed passwords
  • Enter and confirm username and password

• Enable Advanced settings

• Under Network settings:
  • VPC: documentdb-demo-vpc
  • Subnet group: documentdb-subnet-group
  • Security group: documentdb-sg

• Keep remaining settings as default

• Disable Deletion Protection for cluster

• Click Create cluster

• Wait 10–15 minutes for cluster creation

V. EC2 Client Instance Setup

• Open Amazon EC2 dashboard and click launch instance

• Configure:
  • Name: documentdb-client-ec2
  • AMI: Amazon Linux 2
  • Instance type: t2.micro or t3.micro

• Create a Key Pair:
  • Name: dynamodb-client
  • Type: RSA
  • Format: .pem

• In Network settings:
  • VPC: documentdb-demo-vpc
  • Subnet: Choose a public subnet
  • Security group: documentdb-client-sg

• Click Launch instance

VI. Connect to EC2

• Wait until instance status checks pass and click Connect

• Choose EC2 Instance Connect and Click Connect

VII. MongoDB Shell Installation

• Download MongoDB shell:

wget https://downloads.mongodb.com/compass/mongodb-mongosh-1.10.0.x86_64.rpm

• Install mongosh:

sudo yum install -y mongodb-mongosh-1.10.0.x86_64.rpm

• Verify installation:

mongosh --version

• Download DocumentDB TLS certificate:

wget https://truststore.pki.rds.amazonaws.com/global/global-bundle.pem

VIII. Connect to DocumentDB

• Open Amazon DocumentDB → Clusters

• Go to Connectivity & Security and copy the mongosh connection string

• Paste it into the EC2 terminal and enter the database password

IX. Database Operations (CRUD)

• Switch database:

use movieCatalog

• Create collection:

db.createCollection("movies")

• Insert data:

db.movies.insertMany([
{ title: "Inception", genre: "Sci-Fi", releaseYear: 2010, rating: 8.8 },
{ title: "Interstellar", genre: "Sci-Fi", releaseYear: 2014, rating: 8.6 },
{ title: "The Dark Knight", genre: "Action", releaseYear: 2008, rating: 9.0 },
{ title: "Avengers: Endgame", genre: "Superhero", releaseYear: 2019, rating: 8.4 },
{ title: "Parasite", genre: "Thriller", releaseYear: 2019, rating: 8.6 }
])

• Read all movies:

db.movies.find()

• Find by genre:

db.movies.find({ genre: "Sci-Fi" })

• Update one movie:

db.movies.updateOne(
{ title: "Interstellar" },
{ $set: { rating: 8.7 } }
)

• Update multiple movies:

db.movies.updateMany(
{ genre: "Sci-Fi" },
{ $inc: { rating: 0.1 } }
)

• Delete a movie:

db.movies.deleteOne({ title: "Parasite" })

• Verify deletion:

db.movies.find().pretty()

• Compare the total number of documents in the collection after deletion

db.movies.countDocuments()

📂 Full Repository
All source code, configuration steps, and documentation are available here:
https://github.com/Knandwani07/aws-database-architectures/tree/main/documentdb-movie-catalog

X. Cleanup

• Delete DocumentDB cluster instance and DocumentDB cluster

• Delete Subnet Group

• Delete EC2 instance

• Delete Key Pair

• Delete Security Groups

• Delete VPC

✅ Conclusion

This project provides a complete, production-style walkthrough of deploying and using Amazon DocumentDB securely within AWS. It covers networking, security, database operations, and cleanup, reflecting real-world cloud practices.

🤝 Let’s Connect

For feedback, collaboration, or cloud discussions:

LinkedIn: https://www.linkedin.com/in/khushi-nandwani/

GitHub: https://github.com/Knandwani07