AWS Mini Project

Introduction

This project involves creating a simple webpage to check a timetable. The webpage will utilize resources provided by Amazon Web Services (AWS) to ensure scalability and reliability.

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Steps:

Step 1: Launch an EC2 Instance

1. Instance Name:

   • Use your name as the instance name for easy identification.

2. Choose AMI:

   • Select Ubuntu as the Amazon Machine Image (AMI).

3. Create a Key Pair:

   • Create a new key pair during the instance setup to securely connect to the instance.
   • Download the .pem file and keep it safe as it will be required for SSH access.

Step 2: Set Up an EC2 Instance

• While launching the instance, create or modify a security group to allow the necessary traffic:
  • Port 80: For HTTP traffic (webpage access).
  • Port 22: For SSH access.
  • Port 443: For HTTPS traffic (secure connections).
  • Port 5432: For PostgreSQL.
  • Port 8000: For custom application access.
  • All Traffic: (Use only for testing; restrict in production environments).

Step 3: Set Up RDS PostgreSQL

1. Choose Database Engine:

   • In the RDS Console, select PostgreSQL as the database engine.

2. Select DB Instance Type:

   • Choose a Single DB Instance for simplicity and cost-effectiveness.

3. DB Instance Identifier:

   • Use your name as the DB Instance Identifier for easy identification.

4. Credentials Management:

   • Select Self Managed for credentials management.
   • Create a strong password for the database administrator (master user).

5. Connectivity:

   • Configure the database to connect with an EC2 compute resource:
     • Choose the EC2 instance you set up earlier for connectivity.

Step 4: Connect to EC2 Instance Using MobaXterm

1. Open MobaXterm:

   • Launch MobaXterm on your system.

2. Create a New SSH Session:

   • Click on Sessions and select New Session.
   • Choose SSH as the session type.

3. Remote Host:

   • Enter your Public IPv4 address in the Remote host field.
     • You can copy the Public IPv4 address from your EC2 instance in the AWS Console.

4. Advanced SSH Settings:

   • Tick the box for Use private key.
   • Browse and select your .pem key file created earlier.

5. Start the Session:

   • Click OK to initiate the connection.
   • Once connected, you will be prompted to login as:
     • Enter ubuntu as the username (since you are using an Ubuntu instance).

Step 5: Update EC2 and Install Dependencies

1. Update EC2 Instance:

   • Run the following command to update the package list:

     sudo apt update

2. Install Necessary Packages:

   • Run the following command to install Python 3, pip, and PostgreSQL client:

     sudo apt install python3 python3-pip postgresql-client -y

Step 6: Connect to RDS PostgreSQL

1. Connect to the RDS Instance:

   • Use the following command to connect to your RDS PostgreSQL instance:

     psql -h <RDS_End_Point> -U <RDS_User> -d <RDS_Database_Name>

   • Replace <RDS_End_Point>, <RDS_User>, and <RDS_Database_Name> with your actual RDS endpoint, username, and database name.
   • In this case, the RDC_User and RDS_Database_Name will both be postgres.
   • You can find the RDS endpoint in the RDS Console under the Connectivity & Security section. Copy the Endpoint (not the port), which is used in the connection command.

2. Enter the Database Password:

   • When prompted, enter the database password that you created during the RDS setup.

3. Create Your Database:

   • If the connection is successful, you will see the prompt: postgres=>.
   • Now, create a new database with your name using the following query:

     CREATE DATABASE your_name;

   • After creating the database, switch to it with the following command:

     \c your_name;

4. Success Message:

   • If the operation is successful, you will see the prompt: your_name=>.

5. Create a Table:

   • Now, create a table using Timetable as the table name with the following query:

     CREATE TABLE Timetable ( 
         course_name VARCHAR(100),
         room INTEGER,
         day VARCHAR(20),
         time VARCHAR(20)
     );

6. Insert Data into the Table:

   • Insert the following sample data into your table:

     INSERT INTO Timetable (course_name, room, day, time) VALUES 
         ('Mathematics for Computer Science', 103, 'Monday', '9:30 AM'),
         ('Operating Systems', 112, 'Monday', '11:30 AM'),
         ('Python Programming', 205, 'Tuesday', '9:30 AM'),
         ('Java Programming', 213, 'Tuesday', '11:30 AM'),
         ('IT Project Management', 308, 'Wednesday', '2:00 PM'),
         ('Network Principles', 312, 'Wednesday', '4:30 PM'),
         ('Systems Analysis and Design', 415, 'Thursday', '9:30 AM'),
         ('Computer Languages', 325, 'Thursday', '11:30 AM'),
         ('Social Engineering', 256, 'Friday', '2:00 PM'),
         ('Computer and Information', 309, 'Friday', '4:30 PM');

7. Check the Data:

   • Use the following command to check if the data was successfully inserted into the table:

     SELECT * FROM Timetable;

8. Exit SQL:

   • To exit the SQL session, use the following command:

     \q

Step 7: Create Project Directory (https://github.com/Xamidulla0406/AWS-Mini-Project)

1. Create Project Directory:

   • Run the following command to create a project directory and navigate into it:

     mkdir my_project
     cd my_project

2. Create Python File:

   • Create a Python file called app.py in the my_project directory using the following command:

     nano app.py

3. Create Templates Directory:

   • Now, create a directory named templates to hold your HTML files:

     mkdir templates
     cd templates

4. Create HTML Files:

   • Create the index.html file inside the templates directory:

     nano index.html

   • Similarly, create the timetable.html file:

     nano timetable.html

5. Return to the Project Directory:

   • Once you've created the necessary files, return to the main project directory:

     cd ..

Step 8: Set Up Python Virtual Environment

1. Install python3.12-venv:

   • First, install the python3.12-venv package to ensure that you can create a virtual environment. Run the following command:

     sudo apt install python3.12-venv

2. Create and Activate Virtual Environment:

   • After installing the package, create a Python virtual environment by running:

     python3 -m venv venv

   • Activate the virtual environment with the following command:

     source venv/bin/activate

3. Install Python Dependencies:

   • Upgrade pip to the latest version:

     pip3 install --upgrade pip

   • Install the necessary Python dependencies:

     pip3 install flask psycopg2-binary

4. Install pg8000:

   • To use an alternative PostgreSQL database adapter, install pg8000:

     pip install pg8000

5. Disable Firewall (Optional):

   • If you need to disable the firewall for testing purposes, you can run the following command:

     sudo ufw disable

6. Run Flask Application:

   • Finally, to run the Flask application, use this command:

     python app.py

   • The Flask development server will start, and you can access your application by opening your web browser and navigating to http://<Public IPv4 address of your instance>:8000/.