DEV Community: Pradeepa Murugesan

TimeWise – Your Personalized Daily Schedule Generator using AWS PartyRock

Pradeepa Murugesan — Tue, 06 May 2025 06:53:35 +0000

Daily Task Scheduler with AWS PartyRock: A No-Code GenAI Experience

In today's fast-paced world, time management is key to productivity and personal well-being. Imagine having an AI assistant that builds your daily schedule with just a few inputs—no coding, no manual planning. This is exactly what I explored by building a Daily Task Scheduler using AWS PartyRock, a generative AI application builder that lets you prototype powerful apps in minutes without writing a single line of code.

What is AWS PartyRock?

AWS PartyRock is a no-code platform that lets you build generative AI-powered applications with ease. It leverages foundational models from Amazon Bedrock to perform tasks like text generation, summarization, classification, and more. Developers and non-developers alike can build apps by simply dragging and dropping components, connecting inputs, and defining prompts.

Project Overview: Daily Task Scheduler

The goal of this project was to build an application that takes basic daily details—such as work, personal, and health tasks—and generates a full-day personalized schedule.

Tools Used

Platform: AWS PartyRock
Underlying Model: Amazon Bedrock Foundation Models
No coding required

How I Built It

Started with a PartyRock template that uses GenAI for text planning.
Customized the input fields to accept:

General wake-up and sleep times
Categories of tasks (Work, Personal, Health)

Modified the prompt to generate a realistic daily routine based on the user's inputs.
Linked the output to a display component that shows the final schedule in a readable format.

Output: Personalized Daily Schedule

Here is the generated output from the app:
Daily Schedule

Here's your detailed time-blocked schedule:

MORNING 7:00 AM - 7:15 AM: Wake up & hydration
7:15 AM - 7:45 AM: Morning walk
7:45 AM - 8:15 AM: Stretching/yoga
8:15 AM - 8:30 AM: Meditation
8:30 AM - 9:00 AM: Shower & get ready
9:00 AM - 9:30 AM: Breakfast & light planning

WORK MORNING (Peak Productivity)
9:30 AM - 10:00 AM: Check and reply to emails
10:00 AM - 11:00 AM: Team meeting
11:00 AM - 11:15 AM: Buffer/quick break
11:15 AM - 12:30 PM: Project report writing
12:30 PM - 1:30 PM: Lunch break & short walk

WORK AFTERNOON
1:30 PM - 2:45 PM: Code review
2:45 PM - 3:00 PM: Buffer/stretch break
3:00 PM - 4:00 PM: Client call
4:00 PM - 5:00 PM: Final documentation
5:00 PM - 5:30 PM: Final email check & day wrap-up

PERSONAL TIME
5:30 PM - 6:15 PM: Buy groceries
6:15 PM - 6:45 PM: Organize study desk
6:45 PM - 7:00 PM: Evening meditation
7:00 PM - 7:45 PM: Dinner preparation & eating
7:45 PM - 8:00 PM: Clean up

EVENING WIND-DOWN
8:00 PM - 9:30 PM: Free time and reading
9:30 PM - 10:15 PM: Evening routine (prepare for next day)
10:15 PM - 10:30 PM: Light stretching & relaxation
10:30 PM: Lights out

Notes:
• Buffer times are included between major tasks
• Most demanding work is scheduled during morning hours
• Health activities are distributed throughout the day
• Evening schedule allows for proper wind-down
• Free time is protected in the evening for relaxation
• Schedule can be adjusted based on daily priorities

This is the output image generated by the app:

Why This Project Matters

Hands-on with Generative AI: It gave me an easy yet insightful entry into GenAI.
No-Code Learning: Great for beginners to get started with AWS AI tools without needing programming skills.
Real-World Application: Time management is a practical problem, and this app provides a direct solution.

What I Learned

How to use AWS PartyRock effectively.
How GenAI can adapt responses based on structured prompts.
The potential of building full-function apps without traditional programming.

Final Thoughts

The Daily Task Scheduler with AWS PartyRock is just the beginning. AWS's ecosystem opens doors to a wide range of AI-powered applications—from voice synthesis to image recognition. I'll be continuing this journey by experimenting with more mini-projects across the AWS stack.

Stay tuned for upcoming projects, and feel free to try building your own GenAI tools with AWS PartyRock!

💬 Have any questions or built something cool with PartyRock? Let’s connect in the comments!

Getting Started with Cloud: My Experience with the AWS 101 Workshop!!

Pradeepa Murugesan — Sat, 05 Apr 2025 06:57:41 +0000

Cloud computing can seem overwhelming at first, especially when you're just getting started. To ease into it, I recently completed the AWS 101 Workshop — a hands-on beginner-friendly guide that walks you through deploying a web server securely inside your own Amazon VPC.

Workshop link: AWS 101 Workshop

What is the AWS 101 Workshop?

The AWS 101 Workshop is designed to introduce cloud beginners to essential services and networking concepts within AWS. It walks you through deploying a secure, private web tier in AWS with controlled internet access.

You configure an EC2 instance that cannot be reached directly from the internet, but can still access public services like Amazon S3 or download packages via outbound internet.

Key AWS Services Covered

Here are the main AWS services used throughout the workshop:

Amazon EC2 (Elastic Compute Cloud)

Launch and manage virtual machines, configure instance types, attach storage, and apply security groups for access control.

Amazon VPC (Virtual Private Cloud)

Set up a secure virtual network with public and private subnets, routing tables, internet gateways, and NAT gateways to control traffic.

Amazon S3 (Simple Storage Service)

Upload and retrieve files from object storage. You also learn how to allow EC2 access to S3 using IAM roles instead of access keys.

Identity and Access Management (IAM)

Grant secure, role-based access to AWS resources. Learn to apply least-privilege principles by setting fine-grained permissions.

My Experience and Learnings

This workshop provided a practical challenge: configure a private EC2 instance that can access external services without being exposed to the internet. Initially, setting up the VPC, subnets, and route tables was a bit confusing — but it all came together after some trial and error.

One of the most interesting parts was enabling outbound internet using a NAT Gateway in a public subnet, allowing the EC2 instance in the private subnet to download packages while remaining invisible to the outside world.

Another key takeaway was how IAM roles can be used to grant EC2 access to S3 without hardcoding credentials, ensuring both security and automation.

Key Takeaways

Hands-on experience configuring EC2, VPC, S3, and IAM
Learned to isolate and secure infrastructure using private subnets
Gained exposure to AWS networking fundamentals: subnets, route tables, gateways
Understood how to use IAM roles instead of static credentials
Confidence to start deploying cloud-based applications with better security awareness

Final Result

At the end of the workshop, I successfully deployed a sample web application using a private EC2 instance behind a load balancer. The setup followed modern architectural principles, including network isolation, least privilege access, and centralized logging.

To view the deployed application:

Retrieve the Load Balancer DNS from the AWS Console
Paste it in your browser
Access the live app running in a secure cloud environment

Advice for Beginners

If you're planning to try this workshop, here are a few tips:

Review basic networking concepts like CIDR, NAT, and routing
Follow each step slowly and carefully; don’t rush
Use the AWS documentation when something feels unclear
Take notes on what each component does — it helps with retention

This workshop is a great stepping stone before diving into AWS certifications or more advanced services like Lambda, ECS, or CloudFormation.

Conclusion

Completing the AWS 101 Workshop has been a rewarding endeavor, laying a robust foundation for my cloud computing journey. I encourage others to explore this and other AWS learning opportunities to build their skills in this ever-evolving domain.

AWS offers a variety of workshops catering to different skill levels and interests, which can be found on the AWS Workshops page.

Final Result of the Deployed Service

This workshop was a perfect hands-on intro to AWS — I highly recommend it to beginners eager to build real-world cloud skills.

Implementing Secure and Scalable Three-Tier Applications on AWS

Pradeepa Murugesan — Sat, 05 Apr 2025 06:45:42 +0000

Introduction

In today's digital era, businesses require web applications that are not only highly scalable but also secure and efficient. One of the most widely adopted architectural patterns to achieve this is the Three-Tier Architecture, which enhances application performance, maintainability, and security.

A Three-Tier Architecture consists of:

Presentation Tier – The frontend that interacts with users (e.g., web servers).
Application Tier – The logic layer that processes data and handles requests.
Data Tier – The database layer that securely stores and manages data.

By leveraging AWS services, we can build a scalable, highly available, and secure three-tier application in the cloud. In this blog, I will walk you through the step-by-step implementation of a Three-Tier Architecture on AWS, highlighting key services, best practices, and security measures.

Let's dive in!!

Implemention

Step 1: Create an Amazon S3 Bucket

To store static assets (such as images, scripts, and stylesheets) or application data, we first need to create an Amazon S3 bucket.

Navigate to AWS S3:

Go to the AWS Management Console.
Search for S3 in the services search bar.
Click on Amazon S3.

Create a New Bucket:

Click on Create bucket

Enter a unique Bucket name (e.g., yourname-bucket).
Choose the AWS Region where you want to store your data.

Configure Bucket Settings:

Keep Block Public Access settings enabled (for security).
Enable versioning if needed for data backup.
Leave other settings as default unless specific configurations are required.

Create the Bucket:

Click on Create bucket to finalize the setup.
You will see a success message confirming bucket creation.

Step 2: Create an IAM Role for EC2

To allow an EC2 instance to access AWS services securely, we need to create an IAM Role and attach the required policies.

Navigate to IAM:

Go to the AWS Management Console.
Search for IAM in the services search bar.
Click on Roles under the Access management section.

Create a New IAM Role:

Click on Create role.
Select AWS Service as the trusted entity.
Choose EC2 as the use case (to allow EC2 instances to assume this role).
Click Next.

Attach Required Policies:

Attach the following policies:
- AmazonS3ReadOnlyAccess – Provides read-only access to S3.
- AmazonEC2InstanceProfile – Grants permissions for EC2 to access necessary resources.

Click Next.

Configure Role Settings:

Enter a Role Name (e.g., 3-tier-web-application).
Review the settings and permissions.
Click Create Role.

Verify IAM Role Creation:

Go to IAM > Roles and search for the created role (3-tier-web-application).
Ensure the attached policies are correct.

Step 3: Create a VPC in AWS

A Virtual Private Cloud (VPC) allows you to define a custom network for your AWS resources. Below are the steps to create a VPC.

Navigate to the VPC Dashboard

Go to the AWS Management Console.
Search for VPC in the services search bar.
Click on Your VPCs under the Virtual Private Cloud section.

Create a New VPC

Click on Create VPC.

Provide the following details:
- Name tag: MyVPC (or any name of your choice)
- IPv4 CIDR Block: 10.0.0.0/16 (or any custom CIDR block)
- IPv6 CIDR Block: None (optional)
- Tenancy: Default
- Click Create VPC.

Verify the VPC Creation

Navigate back to Your VPCs.
Ensure your newly created VPC appears in the list.

Step 4: Create Six Subnets for 3-Tier Architecture

Navigate to the Subnets Section

Go to VPC Dashboard → Subnets.
Click Create Subnet.

Select the VPC

Choose the VPC created in Step 3.

Create the First Subnet

Subnet Name: Public-Web-Subnet-AZ-1
Availability Zone: us-west-1a (or any AZ in your region)
IPv4 CIDR Block: 10.0.0.0/24
Click Create Subnet.

Create the Remaining Subnets

Subnet Name	Availability Zone	IPv4 CIDR Block
Public-Web-Subnet-AZ-1	us-west-1a	10.0.0.0/24
Private-App-Subnet-AZ-1	us-west-1a	10.0.1.0/24
Private-DB-Subnet-AZ-1	us-west-1a	10.0.2.0/24
Public-Web-Subnet-AZ-2	us-west-1b	10.0.3.0/24
Private-App-Subnet-AZ-2	us-west-1b	10.0.4.0/24
Private-DB-Subnet-AZ-2	us-west-1b	10.0.5.0/24

Verify Subnets

Ensure all subnets are available in the VPC Dashboard.

Step 5: Create an Internet Gateway and Attach It to the VPC

An Internet Gateway (IGW) allows communication between resources inside the VPC and the internet. This step is crucial for making public subnets accessible.

Steps to Create an Internet Gateway

Navigate to VPC Dashboard → Internet Gateways.
Click Create Internet Gateway.

Provide a Name (e.g., three-tier-igw).
Click Create Internet Gateway.

Attach IGW to the VPC

Select the Internet Gateway created (three-tier-igw).
Click Actions → Attach to VPC.

Select the VPC created in Step 1 (aws3tierworkshop).
Click Attach Internet Gateway.

IGW is now attached to the VPC!

This allows resources in the public subnet to access the internet when configured correctly in the route table.

Step 6: Create and Attach a NAT Gateway

To allow private subnets to access the internet securely while keeping them protected, we need to create a NAT Gateway in each public subnet.

Navigate to AWS NAT Gateway

Open the AWS Management Console.
Go to VPC Dashboard → NAT Gateways.
Click Create NAT Gateway.

step 1: Create NAT Gateway for AZ1

Name: NAT-GW-AZ1
Subnet: Public-Web-Subnet-AZ-1
Connectivity Type: Public
Elastic IP: Click Allocate Elastic IP → Select an available Elastic IP.
Click Create NAT Gateway.

step 2: Repeat step 1 and 2 for the other subnet.

Verify NAT Gateway Status

Go to VPC Dashboard → NAT Gateways.
Ensure that the State of the NAT Gateways is Available.

Step 7: Configure Route Tables and Associate Subnets

Now that we've created the NAT Gateways, we need to configure the Route Tables to ensure proper routing between public and private subnets.

View Existing Route Tables

Navigate to AWS Console → VPC Dashboard → Route Tables.
You should see multiple route tables, including:
- PublicRouteTable (for public subnets)
- Private-RT-AZ1 (for private subnets in AZ1)
- Private-RT-AZ2 (for private subnets in AZ2)

Step 1: Configure Public Route Table

Objective: Allow public subnets to have direct internet access via the Internet Gateway.

Select PublicRouteTable from the list.
Navigate to the Routes tab → Click Edit Routes.
Add the following rule:
- Destination: 0.0.0.0/0
- Target: Select your Internet Gateway (IGW-ID).
Click Save Routes.

Step 2: Configure Private Route Tables

Objective: Allow private subnets to access the internet via the NAT Gateways.

Private Route Table for AZ1

Select Private-RT-AZ1.
Navigate to the Routes tab → Click Edit Routes.
Add the following rule:
- Destination: 0.0.0.0/0
- Target: Select NAT-GW-AZ1.
Click Save Routes.

Private Route Table for AZ2

Select Private-RT-AZ2.
Navigate to the Routes tab → Click Edit Routes.
Add the following rule:
- Destination: 0.0.0.0/0
- Target: Select NAT-GW-AZ2.
Click Save Routes.

Step 3: Associate Subnets with Route Tables

Associate Public Subnets with Public Route Table

Select PublicRouteTable.
Navigate to the Subnet Associations tab → Click Edit Subnet Associations.
Select the Public-Web-Subnet-AZ-1 and Public-Web-Subnet-AZ-2.
Click Save Associations.

Associate Private Subnets with Private Route Tables

Select Private-RT-AZ1.
Navigate to the Subnet Associations tab → Click Edit Subnet Associations.
Select Private-App-Subnet-AZ-1.
Click Save Associations.
Select Private-RT-AZ2.
Navigate to the Subnet Associations tab → Click Edit Subnet Associations.
Select Private-App-Subnet-AZ-2.
Click Save Associations.

Step 4: Verify the Routing Setup

Go back to Route Tables in the VPC Dashboard.
Ensure each route table has the correct routes and subnet associations.
Your Public Subnets should be linked to the Public Route Table, and your Private Subnets should be linked to their respective Private Route Tables.

Now your VPC networking is fully configured with proper internet and internal routing!

Step 8: Security Groups

Security groups control the traffic allowed to our Elastic Load Balancers and EC2 instances. We will set up multiple security groups to enforce access rules.

Security Group for Public Load Balancer

Navigate to Security Groups in the VPC Dashboard (under Security).

Create a new security group for the public, internet-facing load balancer.
Add an inbound rule:
- Type: HTTP
- Source: Your IP (for admin access)

Security Group for Public Web Instances

Create a new security group for public instances in the web tier.
Add two inbound rules:
- Allow HTTP traffic from the internet-facing load balancer security group.
- Allow HTTP traffic from your IP (for direct instance access).

Security Group for Internal Load Balancer

Create a new security group for the internal load balancer.
Add an inbound rule:
- Type: HTTP
- Source: Public instance security group (allows traffic from web tier instances).

Security Group for Private Instances (App Tier)

Create a new security group for private instances.
Add two inbound rules:
- Allow TCP traffic on port 4000 from the internal load balancer security group (to receive traffic).
- Allow TCP traffic on port 4000 from your IP (for testing).

Security Group for Private Database Instances

Create a new security group for private database instances.
Add an inbound rule:
- Type: MYSQL/Aurora (Port 3306)
- Source: Private instance security group (allows only app-tier instances to access the database).

With these security groups, we ensure that only necessary traffic is allowed at each layer of the architecture while maintaining security and accessibility.

Step 9: Subnet Group

Database Deployment - Subnet Groups

To deploy our database in a high-availability setup, we need to create an RDS Subnet Group that includes subnets from different availability zones.

Creating a DB Subnet Group

Navigate to the RDS Dashboard in the AWS Console.
Click on Subnet groups on the left-hand side.
Click Create DB subnet group.

Provide the following details:
- Name: A meaningful name for the subnet group.
- Description: A brief description.
- VPC: Select the VPC we created earlier.
Add Subnets:
- Select the subnets from each availability zone that were specifically created for the database layer.
- If unsure, navigate back to the VPC Dashboard to verify and select the correct Subnet IDs.

This ensures our database is deployed across multiple availability zones, improving fault tolerance and reliability.

Step 10: Database Deployment

Creating the Database

Navigate to the RDS Dashboard in the AWS Console.
Click Databases on the left-hand side.
Click Create database.

Configuring the Database

Choose database creation method:
- Select Standard create.
- Choose MySQL-Compatible Amazon Aurora as the engine.
- Leave all Engine options as default.
Select a Template:
- Choose Dev/Test since this isn't a production setup.
Set Database Credentials:
- Set a Master username and password.
- Note down these credentials for later authentication.
Configure High Availability:
- Under Availability and durability, select the option to create an Aurora Replica (reader node) in a different availability zone.
Set Network & Security Settings:
- Under Connectivity,
  - Choose the VPC we created earlier.
  - Select the DB subnet group created in the previous step.
  - Set Public access to No.
- Attach the Security Group for the database layer.
Choose Authentication Method:
- Select Password authentication.
Create the Database

Copying Database Credentials

If you chose to auto-generate the password, make sure to copy and save it immediately after database creation, as AWS will not show it again.

Post-Deployment Checks

Once the database is provisioned, you should see:
- A Writer instance
- A Reader instance (in a different availability zone).
Note down the Writer endpoint for database connectivity in later steps.

Step 11: App Instance Deployment

Launching an EC2 Instance

Navigate to EC2 Service
- Go to the AWS Management Console.
- Open the EC2 Dashboard.
- Click on Instances → Launch Instances.

Choose an Amazon Machine Image (AMI)
- Select Amazon Linux 2 AMI.
Select an Instance Type
- Choose t2.micro (Free Tier eligible).
- Click Next: Configure Instance Details.
Configure Instance Details
- Network: Select the VPC created earlier.
- Subnet: Choose one of the Private App Subnets.
- IAM Role: Assign the IAM role created for this instance.
- Key Pair: Proceed without a key pair, as we will use EC2 Instance Connect.
Set Security Group
- Select the Private Instance Security Group created in Step 8.
Launch the Instance
- Click Launch Instance.
- Wait for the instance to be provisioned.

Step 12: Connect to the Instance & Configure the Database

Connecting to the EC2 Instance

Access the EC2 Dashboard
- Navigate to the AWS EC2 Dashboard.
- Click on Instances to view all running instances.
- Select the desired instance by marking the checkbox next to it.
- Click the Connect button located at the top-right corner.
Establish Connection Using Session Manager
- In the Connect to instance page, select the Session Manager tab.
- Click on the Connect button to initiate the session. A new browser tab will open, providing terminal access to your instance.

Note: If the Session Manager tab is unavailable or the connect button is disabled, ensure that:

The instance has the SSM Agent installed and running.

The associated IAM role has the necessary permissions, specifically the AmazonSSMManagedInstanceCore policy.

The instance can route to the necessary AWS endpoints, either through the internet or via VPC endpoints. :contentReference[oaicite:0]{index=0}

Switch to the ec2-user Account
- Once connected, the default user might be ssm-user. Switch to the ec2-user by executing:
```
 sudo -i -u ec2-user
```
Verify Internet Connectivity
- Test the internet connection by pinging an external server:
```
 ping -c 4 8.8.8.8
```

If you receive responses, your instance has internet access. Stop the ping test by pressing Ctrl + C.

Troubleshooting: If the ping test fails:

Verify that the instance's subnet route table directs internet-bound traffic to a NAT Gateway or an Internet Gateway, as appropriate.

Ensure that security groups and network ACLs allow outbound ICMP traffic.

Configuring the Database

1. Install the MySQL Client

Update the package repository and install the MySQL client:
```
 sudo yum update -y
 sudo yum install mysql -y
```

If the above installation encounters issues, consider the following alternative steps:

 sudo wget https://dev.mysql.com/get/mysql57-community-release-el7-11.noarch.rpm
 sudo rpm -ivh mysql57-community-release-el7-11.noarch.rpm
 sudo yum install mysql-community-client -y

2. Connect to the Amazon RDS Database

Initiate a connection to your RDS instance using the MySQL client. Replace YOUR-RDS-ENDPOINT with your database's endpoint and YOUR-USERNAME with your database username:
```
 mysql -h YOUR-RDS-ENDPOINT -u YOUR-USERNAME -p
```
When prompted, enter the corresponding password.

Note: Ensure that the security group associated with your RDS instance allows inbound traffic from your EC2 instance on the MySQL port (default: 3306).

3. Create a Database and Table

Once connected to the MySQL prompt, create a new database named webappdb:
```
 CREATE DATABASE webappdb;
```
Verify the creation by listing all databases:
```
 SHOW DATABASES;
```
Switch to the newly created database:
```
 USE webappdb;
```

Create a table named transactions:

 CREATE TABLE transactions (
     id INT NOT NULL AUTO_INCREMENT,
     amount DECIMAL(10,2),
     description VARCHAR(100),
     PRIMARY KEY (id)
 );

Confirm the table creation:
```
 SHOW TABLES;
```

4. Insert and Retrieve Data

Insert a sample record into the transactions table:

 INSERT INTO transactions (amount, description) VALUES (400.00, 'groceries');

Retrieve and display the inserted data:
```
 SELECT * FROM transactions;
```

5. Exit the MySQL Client

Terminate the MySQL session by typing:
```
 EXIT;
```

Uploading Files to S3

1. Install AWS CLI (If Not Installed)

sudo yum install -y aws-cli

2. Configure AWS CLI

Run the following command and enter your AWS credentials:

aws configure

Access Key ID: [Your AWS Access Key]
Secret Access Key: [Your AWS Secret Key]
Region: [Your AWS Region]
Output Format: json

3. Upload a File to S3

Replace YOUR-BUCKET-NAME with your actual S3 bucket name and yourfile.txt with the file you want to upload.

aws s3 cp yourfile.txt s3://YOUR-BUCKET-NAME/

4. Upload a Directory to S3

If you need to upload the entire app-tier folder:

aws s3 cp app-tier/ s3://YOUR-BUCKET-NAME/app-tier/ --recursive

5. Verify Uploads

To list files in your S3 bucket:

aws s3 ls s3://YOUR-BUCKET-NAME/

Security Reminder: Always ensure that database credentials and AWS credentials are stored securely and not hard-coded into your applications. Consider using AWS Secrets Manager or Parameter Store for managing sensitive information.

Step 13: Internal Load Balancing and Auto Scaling

App Tier AMI

Navigate to the EC2 Dashboard
- Open the AWS EC2 Dashboard.
- Click on Instances in the left-hand navigation panel.
Create an AMI (Amazon Machine Image)
- Select the app-tier instance that was previously created.
- Click on Actions → Image and templates → Create Image.
Configure the Image
- Provide a name and description for the AMI.
- Click Create Image to start the process.
Monitor Image Creation
- The AMI creation process may take a few minutes.
- To monitor the status, navigate to AMIs under the Images section in the left-hand navigation panel.

Step 14: Target Group

Creating a Target Group

While the AMI is being created, we can proceed with setting up a target group for the load balancer.

Navigate to Target Groups
- Open the AWS EC2 Dashboard.
- In the left-hand navigation panel, go to Target Groups under Load Balancing.
- Click Create Target Group.

Configure the Target Group
- Select Instances as the Target Type.
- Provide a name for the target group.
- Set the Protocol to HTTP and the Port to 4000. (This is the port our Node.js app is running on.)
- Choose the VPC used in the previous steps.
- Change the Health Check Path to /health, which corresponds to the health check endpoint of our app.
- Click Next.
Skip Target Registration
- Do not register any targets at this stage.
- Skip this step and create the target group.

Step 15: Internal Load Balancer

Creating an Internal Load Balancer

Navigate to Load Balancers
- Open the AWS EC2 Dashboard.
- On the left-hand navigation panel, go to Load Balancers under Load Balancing.
- Click Create Load Balancer.

Choose Load Balancer Type
- Select Application Load Balancer (ALB) for handling HTTP traffic.
- Click the Create button.
Configure the Load Balancer
- Provide a name for the Load Balancer.
- Choose Internal as the type (since this ALB will not be public-facing).
- This ALB will route traffic from the Web Tier to the App Tier.
Select Network Configuration
- Choose the correct VPC.
- Select the private subnets for deployment.
Assign Security Group
- Use the security group created earlier for the internal ALB.
Configure Listener and Target Group
- The ALB will listen for HTTP traffic on port 80.
- Set the Target Group to the one created in Step 14.
- Select it from the dropdown.
Create the Load Balancer
- Click Create Load Balancer to finalize the setup.

Step 16: Launch Template

Creating a Launch Template

Navigate to Launch Templates
- Open the AWS EC2 Dashboard.
- On the left-hand side, go to Launch Templates under Instances.
- Click Create Launch Template.

Configure Launch Template
- Provide a name for the launch template.
- Under Application and OS Images, select the App Tier AMI created earlier.
Select Instance Type
- Choose t2.micro as the instance type.
Exclude Key Pair and Network Settings
- Do not include a key pair in the template.
- The network settings will be configured in the Auto Scaling Group.
Set Security Group
- Assign the security group used for the App Tier.
Advanced Settings
- Under Advanced details, select the IAM instance profile that has been used for other EC2 instances.
Create Launch Template
- Click Create Launch Template to finalize the setup.

Step 17: Auto Scaling

Creating an Auto Scaling Group

Navigate to Auto Scaling Groups
- Open the AWS EC2 Dashboard.
- On the left-hand side, go to Auto Scaling Groups under Auto Scaling.
- Click Create Auto Scaling Group.

Set Auto Scaling Group Name
- Enter a name for your Auto Scaling Group.
- Select the Launch Template created in the previous step.
- Click Next.
Configure Instance Launch Options
- Select the VPC.
- Choose the private instance subnets for the App Tier.
- Click Next.
Attach to Load Balancer
- Attach the Auto Scaling Group to the Load Balancer created earlier.
- Select the existing target group from the dropdown.
- Click Next.
Configure Group Size and Scaling Policies
- Set:
  - Desired capacity: 2
  - Minimum capacity: 2
  - Maximum capacity: 2
- Click Skip to review.
Finalize and Create Auto Scaling Group
- Click Next until the final step.
- Click Create Auto Scaling Group.

Step 18: Update Config File and Web Instance Deployment

Update Config File

Open the application-code/nginx.conf file from the repository you downloaded.
Scroll to line 58 and replace [INTERNAL-LOADBALANCER-DNS] with your internal load balancer’s DNS.
- To find the DNS Name:
  - Navigate to EC2 Dashboard → Load Balancers.
  - Select your internal load balancer.
  - Copy the DNS Name from the details page.
Save the file and upload both:
- The updated nginx.conf file.
- The application-code/web-tier folder.
- To the S3 bucket you created for this lab.

Web Instance Deployment

1. Launch a Web Instance

Navigate to EC2 Dashboard → Click on Instances (left-hand side).
Click Launch Instances.

Select Amazon Linux 2 AMI.
Choose t2.micro (Free Tier Eligible) and click Next: Configure Instance Details.

2. Configure Instance Details

Key-Pair: Proceed without a key-pair (using EC2 Instance Login).
Network Settings:
- Select the correct VPC.
- Choose a Public Subnet (AZ-1).
- Enable Auto-Assign Public IP.
Security Group:
- Use the existing Web Tier Security Group.
IAM Role:
- Select the already created IAM Role.
Click Launch Instance.

Connect to the Instance

Go to EC2 Dashboard → Click Instances.
Wait until the Instance State is Running.

Select the instance and click Connect (top-right corner).
Choose Session Manager Tab → Click Connect.
- A new browser tab will open.

4. Test Internet Connectivity

Run the following commands to verify connectivity:

sudo -su ec2-user
ping 8.8.8.8

Step 19: Configure Web Instance

We will now install the necessary components for running our front-end application.

1. Install NVM and Node.js

Run the following commands to install NVM and Node.js 16:

curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.38.0/install.sh | bash
source ~/.bashrc
nvm install 16
nvm use 16

2. Download Web Tier Code from S3

Replace BUCKET_NAME with your actual S3 bucket name.

cd ~/
aws s3 cp s3://BUCKET_NAME/web-tier/ web-tier --recursive

3. Build the React Application

Navigate to the web-tier folder and build the React app:

cd ~/web-tier
npm install
npm run build

4. Install and Configure NGINX

NGINX is used as a web server to serve the front-end application and route API calls to the internal load balancer.

Install NGINX:

sudo amazon-linux-extras install nginx1 -y

Navigate to NGINX Configuration Directory:

cd /etc/nginx
ls

You should see an nginx.conf file.

Replace `nginx.conf` with the one from S3:

sudo rm nginx.conf
sudo aws s3 cp s3://BUCKET_NAME/nginx.conf .

Restart NGINX:

sudo service nginx restart

5. Set Permissions and Enable Auto-Start

Grant necessary permissions:

chmod -R 755 /home/ec2-user

Ensure NGINX starts on boot:

sudo chkconfig nginx on

Step 20: External Load Balancer and Auto Scaling

Create Web Tier AMI

We will now create an Amazon Machine Image (AMI) for the Web Tier to use later with our Auto Scaling Group.

1. Navigate to Instances

Go to the EC2 Dashboard.
Click on Instances on the left-hand panel.

2. Select the Web Tier Instance

Find the Web Tier instance you launched.
Click on the checkbox to select it.

3. Create Image

Click on Actions → Image and templates → Create image.

4. Fill Out Image Details

Name: Give your image a meaningful name (e.g., web-tier-ami).
Description: Add a short description (e.g., "AMI for Web Tier Auto Scaling").

5. Create and Monitor

Click the Create image button.
To monitor the image creation progress:
- Go to AMIs under Images in the left navigation panel of the EC2 Dashboard.

Step 21: Target Group

While the AMI is being created, we can create the target group for our external load balancer.

1. Navigate to Target Groups

Go to the EC2 Dashboard.
On the left-hand side, under Load Balancing, click Target Groups.
Click Create Target Group.

2. Target Group Settings

Select Instances as the target type.
Give your target group a name.

3. Configure Protocol and Port

Set the protocol to HTTP.
Set the port to 80 (this is the port NGINX is listening on).
Select the same VPC used previously.
Change the health check path to /health.

4. Skip Registering Targets

Do not register any targets for now.
Click Create Target Group to finish.

Step 22: Internet-Facing Load Balancer

We will now create an Application Load Balancer (ALB) that is internet-facing. This ALB will route traffic from users to our Web Tier instances.

1. Navigate to Load Balancers

Go to the EC2 Dashboard.
On the left sidebar, under Load Balancing, click Load Balancers.
Click Create Load Balancer.

2. Choose Load Balancer Type

Select Application Load Balancer.
Click the Create button.

3. Basic Configuration

Name: Give your ALB a name (e.g., web-tier-alb).
Scheme: Choose Internet-facing. > This ALB is public-facing and will handle traffic from users on the internet.
IP address type: Choose IPv4.

4. Network Mapping

Select the correct VPC.
Select public subnets in multiple Availability Zones (AZs).

5. Configure Security Groups

Choose the Security Group created for the Web Tier Load Balancer.

6. Listener and Routing

Listener protocol: HTTP
Port: 80
Forward to: Choose the Target Group created in Step 21 for the web tier.

7. Create Load Balancer

Click Create Load Balancer to complete the setup.

Step 23: Launch Template (Web Tier)

Before we configure Auto Scaling, we need to create a Launch Template using the Web Tier AMI we created earlier.

1. Navigate to Launch Templates

Go to the EC2 Dashboard.
On the left sidebar under Instances, click Launch Templates.
Click Create Launch Template.

2. Basic Configuration

Name: Provide a name for your Launch Template (e.g., web-tier-launch-template).
Under Application and OS Images (Amazon Machine Image), select the Web Tier AMI you previously created.

3. Instance Type

Choose t2.micro.

4. Key Pair and Network Settings

Do not include a Key Pair (we’ll use EC2 Instance Connect).
Leave Network Settings unchecked, as we’ll configure them inside the Auto Scaling Group.

5. Security Group and IAM Role

Select the Security Group created for the Web Tier.
Under Advanced Details, set the IAM instance profile we’ve been using for EC2 instances.

6. Create Template

Click Create Launch Template to finish.

Step 24: Auto Scaling Group (Web Tier)

We will now create the Auto Scaling Group (ASG) for our Web Tier instances.

1. Navigate to Auto Scaling Groups

Go to the EC2 Dashboard.
On the left sidebar under Auto Scaling, click Auto Scaling Groups.
Click Create Auto Scaling Group.

2. Configure Basic Settings

Name: Provide a name for the ASG (e.g., web-tier-asg).
Launch Template: Select the Launch Template created in Step 23.
Click Next.

3. Instance Launch Options

Select the appropriate VPC.
Choose the public subnets created for the Web Tier.

4. Configure Load Balancer

Attach the Auto Scaling Group to the Web Tier Load Balancer.
Select the Target Group associated with the Web Tier ALB.
Click Next.

5. Configure Group Size and Scaling Policies

Desired Capacity: 2
Minimum Capacity: 2
Maximum Capacity: 2
Click Skip to review.

6. Create Auto Scaling Group

Review your settings.
Click Create Auto Scaling Group.

Deployment Complete!

You now have a fully working WebApp running behind an Internet-Facing Load Balancer with Auto Scaling enabled for high availability.

To see your application live, follow these steps:

Go to the EC2 Dashboard.
On the left sidebar, under Load Balancing, click Load Balancers.
Find your Web Tier Load Balancer (Internet-facing).
Copy the DNS name of the load balancer.
Paste it in your web browser.

You should now see your deployed Web Application running successfully!

Congratulations on completing the deployment!

Conclusion

Well done on successfully completing your three-tier architecture project on AWS! 🎉

You've set up:

A solid three-tier architecture using EC2, Load Balancers, Auto Scaling Groups, S3, and IAM.
Both internal and external load balancers.
Proper scaling mechanisms for your application and web tiers.
A production-style deployment pipeline from scratch.

🧹 Clean Up Reminder

Before wrapping up, it’s important to clean up all the AWS resources you created for learning purposes to:

Avoid any unwanted charges.
Keep your AWS environment tidy.

Make sure to:

Delete EC2 instances, AMIs, Snapshots.
Delete Load Balancers, Target Groups, Launch Templates.
Remove Auto Scaling Groups.
Clean up your S3 buckets.
Detach and remove IAM Roles if not needed.

Thank you for following along — and congratulations again on leveling up your cloud skills!

Happy Building!

AWS Polly: Transforming Text into Lifelike Speech

Pradeepa Murugesan — Sat, 05 Apr 2025 06:40:20 +0000

AWS Polly: Transforming Text into Lifelike Speech

In today's digital world, voice-enabled applications have gained massive popularity. Whether it's virtual assistants, audiobooks, or customer service bots, natural-sounding speech is crucial for user engagement. AWS Polly, a cloud-based text-to-speech (TTS) service from Amazon Web Services (AWS), enables developers to convert text into lifelike speech using advanced deep learning technologies. This blog explores the capabilities of AWS Polly, its use cases, pricing, and how you can get started with it.

What is AWS Polly?

AWS Polly is an AI-powered text-to-speech service that converts written text into natural-sounding speech. It leverages deep learning models to generate human-like speech in multiple languages and voices. Polly provides both standard TTS and neural TTS (NTTS), which enhances the naturalness and expressiveness of speech output.

Key Features of AWS Polly

Lifelike Speech Synthesis – Uses neural TTS technology to deliver high-quality speech.
Multiple Languages and Voices – Supports a wide range of languages and voices, including both male and female speakers.
Custom Lexicons & Speech Marks – Allows developers to customize pronunciation and control speech output with SSML (Speech Synthesis Markup Language).
Real-Time & Offline Synthesis – Generates speech on the fly or pre-synthesizes it for later use.
Cost-Effective & Scalable – A pay-as-you-go pricing model ensures affordability and scalability for different applications.

Use Cases of AWS Polly

AWS Polly is widely used across industries for various applications. Some of its common use cases include:

Voice Assistants & Chatbots

Enhances AI-driven assistants like Alexa by providing lifelike speech output.
E-Learning & Audiobooks

Converts textbooks, guides, and learning materials into speech to aid accessibility and learning experiences.
Content Accessibility

Helps visually impaired users consume web content through screen readers.
Telephony & IVR Systems

Used in automated customer service systems for personalized voice responses.
Gaming & Entertainment

Creates realistic voiceovers for video games, animated content, and movies.
Multilingual Applications

Supports applications requiring language translation and multilingual speech output.

Pricing Model

AWS Polly follows a flexible pay-as-you-go pricing model, allowing businesses to optimize costs based on usage. The pricing is divided into:

Standard TTS Pricing: Charged per million characters processed.
Neural TTS (NTTS) Pricing: Slightly higher than standard TTS, offering improved voice quality.
Free Tier: AWS provides a free tier for Polly, offering 5 million standard characters or 1 million neural characters per month for the first 12 months.

For detailed pricing information, refer to AWS Polly Pricing.

Advantages of AWS Polly

Scalable and flexible pricing based on usage.
High-quality voices with support for SSML.
Multi-language support to cater to global audiences.

Real-World Example

Here’s how AWS Polly is being used to read webpages and highlight content. With AWS Polly, developers can integrate text-to-speech capabilities into their websites or applications. This allows users to listen to webpage content, making it easier for people with visual impairments or those who prefer auditory learning experiences. The ability to highlight content as it's being read out loud further enhances accessibility, ensuring that users can easily follow along with the content.

Conclusion

AWS Polly is a powerful and versatile text-to-speech service that enables developers to create highly engaging voice-based applications. Whether you're building chatbots, e-learning solutions, or customer service systems, Polly’s lifelike speech synthesis enhances user experience. With its scalability, affordability, and broad language support, AWS Polly is an ideal choice for businesses looking to incorporate AI-driven speech solutions.

Are you ready to add voice to your application? Start using AWS Polly today!

For more details, visit AWS Polly Documentation.

Amazon MQ: Simplifying Messaging for Modern Applications.

Pradeepa Murugesan — Thu, 23 Jan 2025 02:43:49 +0000

Introduction

In today’s fast-paced world of distributed systems, reliable communication between services is a cornerstone of application design. Whether it’s microservices, IoT devices, or legacy systems, message brokers act as intermediaries to ensure seamless data exchange.

Amazon MQ is AWS’s fully managed message broker service that simplifies this complexity. It supports widely used open-source standards such as Apache ActiveMQ and RabbitMQ, enabling developers to migrate legacy systems effortlessly and build modern, decoupled architectures.

This blog dives into the core features, use cases, and practical advantages of Amazon MQ, along with how it fits into your cloud-based application ecosystem.

Key Features

1. Fully Managed Service

Amazon MQ automates tedious administrative tasks such as:

Provisioning hardware and software
Monitoring broker health and availability
Handling upgrades and patches

This lets developers focus on building applications instead of managing infrastructure.

2. Open Standards Support

It ensures compatibility with popular message protocols, including:

AMQP (Advanced Message Queuing Protocol) for message-oriented middleware.
MQTT (Message Queuing Telemetry Transport), widely used in IoT devices.
OpenWire and STOMP, supported by Apache ActiveMQ.

This means you can use your existing applications with Amazon MQ without rewriting code.

3. High Availability with Multi-AZ Deployment

Amazon MQ ensures reliability through redundant infrastructure across multiple AWS Availability Zones. In the event of a hardware failure, it automatically switches to a standby instance.

4. Scalable and Flexible

It scales to meet your workload demands dynamically and supports a pay-as-you-go pricing model, making it cost-effective for various business sizes.

5. Secure Communication

Security is a priority in Amazon MQ, offering:

TLS encryption for data in transit.
AES-256 encryption for data at rest.
Fine-grained access control using AWS IAM policies.

How Amazon MQ Works

Message brokers play a crucial role in communication by facilitating the reliable exchange of messages between producers (senders) and consumers (receivers).

Messaging Models

Queue-Based Messaging

Messages are stored in a queue and consumed by one receiver at a time. This guarantees:
- Ordered delivery
- Fault-tolerant message processing
Publish-Subscribe Model (Pub/Sub)

Multiple subscribers receive the same message simultaneously. This is ideal for real-time scenarios such as broadcasting updates to users.

Real-World Use Cases

Amazon MQ supports diverse scenarios, including:

1. Enterprise Messaging

Enterprises use Amazon MQ for integrating legacy systems with modern applications, enabling seamless communication.

2. IoT Applications

Amazon MQ’s support for MQTT makes it ideal for connecting IoT devices with cloud applications in real-time. Examples include smart homes, connected vehicles, and industrial monitoring systems.

3. Microservices Communication

In a microservices architecture, Amazon MQ acts as a mediator to decouple services, ensuring:

Fault tolerance
Asynchronous communication
Load distribution

4. Financial Systems

Financial services require low-latency, secure, and reliable messaging. Amazon MQ helps process transactions, reconcile accounts, and ensure regulatory compliance.

5. Gaming Applications

Multiplayer games can leverage Pub/Sub for real-time updates, such as broadcasting player actions to all participants in a match.

Integration with AWS Ecosystem

Amazon MQ integrates seamlessly with other AWS services, enabling powerful workflows. For example:

AWS Lambda: Trigger serverless functions based on incoming messages.
Amazon SQS/SNS: Use Amazon MQ alongside SQS (for asynchronous processing) or SNS (for message broadcasting).
Amazon RDS/DynamoDB: Store messages and metadata in databases for audit trails or advanced analytics.

Pricing

Amazon MQ pricing is based on the following factors:

Broker Instance Hours: Charges are based on the uptime of your broker instances.
Storage Costs: Billed per GB-month of storage for message persistence.
Data Transfer: Costs for moving messages between AWS services or out of AWS regions.

For small businesses or low-throughput applications, Amazon MQ’s cost structure can be overkill. In such cases, lightweight solutions like Amazon SQS may be a better alternative.

Amazon MQ vs. Alternatives

Feature	Amazon MQ	Amazon SQS/SNS	Apache Kafka
Fully Managed	Yes	Yes	Partially
Message Durability	High	High	High
Open Protocols	Yes (AMQP, MQTT)	No	No
Use Case	Legacy Integration, IoT, Enterprise	Lightweight Decoupling	Real-Time Streaming

Benefits

Ease of Migration: Supports legacy systems without refactoring code.
Increased Productivity: Developers focus on innovation while Amazon handles the backend.
Reliability: Ensures high availability and fault tolerance for critical workloads.

Conclusion

Amazon MQ is a robust solution for managing inter-service communication, especially for businesses with complex messaging needs. With its support for open standards, high availability, and seamless integration with AWS services, Amazon MQ is well-suited for enterprise applications, microservices, IoT, and more.

If your application demands real-time, secure, and scalable communication, Amazon MQ is worth exploring.

Have any questions or insights? Share them in the comments below!!