⭐ AWS Project - Connecting EC2 to RDS: Building a Scalable Data Pipeline (MySQL & Python)

➡ Connecting an EC2 instance (client) to an RDS instance (server) running MySQL. This combination enables applications on EC2 to interact with a secure and scalable database in the cloud.

➡Beginning by Setting Up EC2 and RDS and Launching an EC2 Instance:
I started an EC2 instance, choosing an appropriate Amazon Machine Image (AMI) with pre-installed tools like MySQL connector libraries.
➡Creating an RDS Instance: Next, I configured an RDS instance, selecting the MySQL engine and defining essential parameters like storage capacity and security settings.
➡Securing the Connection: Security is Crucial ! I configured security groups for both EC2 and RDS to allow inbound traffic only from the EC2 instance to the RDS endpoint on the designated port.
➡Connecting to RDS: I used Python's (mysql.connector) library to establish a connection from the EC2 instance to the RDS database. This involved specifying the RDS endpoint, username, password, and database name.
➡Inserting Data: With the connection established, I crafted Python code using INSERT statements to insert data into my RDS tables. The code dynamically constructed the queries, ensuring flexibility and data integrity.
➡Deleting Data: For data management completeness, I implemented code using DELETE statements to remove specific records from the RDS tables based on defined criteria.
➡The Power of Cloud-Based Data Management
By successfully connecting EC2 to RDS:
Scalability: RDS offers an elastic and scalable database solution, easily adapting to changing data volumes.
Security: The managed nature of RDS ensures robust security features, safeguarding your valuable data.
Cost-Effectiveness: You only pay for the resources you utilize with RDS, making it a cost-efficient choice.
Flexibility: The combination of EC2 and RDS empowers you to build dynamic applications that interact with structured data in the cloud.

✅This project provided a valuable hands-on experience with managing data in the AWS cloud !