DEV Community: JEEVA PRAKASINI G

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JEEVA PRAKASINI G — Tue, 15 Sep 2026 18:25:00 +0000

Jeeva Meets Launch Wizard: My First AWS Deep Dive into Guided Deployments 🚀🧩


> A practical exploration of AWS Launch Wizard — from what it is, to how it works, to how it could be used in a college AI/ML department.

Introduction
**
What is AWS Launch Wizard?**

AWS Launch Wizard is a guided deployment service from AWS that helps you size, configure, and deploy AWS resources for popular third-party and enterprise applications — without manually identifying every individual resource yourself.

Instead of separately choosing EC2 instance types, EBS volumes, networking, and other settings, you answer a set of questions about your application's requirements (performance, number of nodes, connectivity), and Launch Wizard recommends and provisions the right combination of resources for you.

Launch Wizard currently supports guided deployments for applications such as:

Microsoft SQL Server (single-instance or Multi-AZ)
SAP HANA, SAP NetWeaver, SAP S/4HANA, SAP BW/4HANA
AWS Managed Microsoft Active Directory
Why Was It Created?

Deploying enterprise applications like SAP or SQL Server on AWS traditionally required deep, application-specific expertise:

Knowing which instance families and sizes fit the workload
Sizing EBS volumes correctly for performance and capacity
Configuring networking, Availability Zones, and high availability
Setting up Active Directory or database-specific requirements
Estimating cost before committing to resources Doing all of this manually is time-consuming and easy to get wrong, especially for teams without dedicated AWS infrastructure specialists.

AWS Launch Wizard was created to reduce this complexity — turning "which resources do I need, and how do I wire them together?" into a guided, best-practice-driven workflow that can cut deployment time for complex applications from weeks to hours.

How It Works

The basic working of Launch Wizard is simple, even though the applications it deploys are complex.

Step 1: Choose Application
        │
        ▼
Step 2: Enter Requirements
   (performance, nodes,
    connectivity, sizing)
        │
        ▼
Step 3: Review Recommended
    Resources + Cost Estimate
        │
        ▼
Step 4: Adjust Configuration
    (optional, re-estimates cost)
        │
        ▼
Step 5: Approve Deployment
        │
        ▼
Launch Wizard Provisions
  (via CloudFormation)
        │
        ▼
Production-Ready Application

Under the hood, Launch Wizard generates and runs infrastructure-as-code — typically AWS CloudFormation stacks — and coordinates services like Amazon EC2, Amazon VPC, and IAM to build the environment. Because the deployment is backed by CloudFormation, it is trackable and repeatable rather than a one-off manual build.

Simple architecture/flow diagram:


                    AWS Launch Wizard
                           │
              ┌────────────┼────────────┐
              ▼            ▼            ▼
         CloudFormation   IAM          VPC
         (provisioning) (permissions) (networking)
              │            │            │
              └────────────┼────────────┘
                           ▼
                 EC2 + EBS + (AD / FSx /
                  ELB, depending on app)
                           │
                           ▼
              Production-Ready Application
                (SQL Server / SAP / AD)

Key Features

1. Guided, Requirement-Based Sizing

Instead of picking instance types yourself, you describe performance, throughput, and node requirements, and Launch Wizard recommends appropriate EC2 instance types and EBS volumes to match them.

2. Upfront Cost Estimation

Before anything is deployed, Launch Wizard shows an estimated cost for the recommended configuration. If you adjust the settings — say, changing the number of nodes — the cost estimate updates instantly, so you can compare trade-offs before committing.

3. Infrastructure-as-Code Under the Hood

Every deployment is backed by reusable AWS CloudFormation templates. This means the same configuration can be reused for future deployments instead of being rebuilt manually each time — useful for creating repeatable dev/test or proof-of-concept environments.

4. Support for Enterprise-Grade Patterns

Launch Wizard supports high-availability patterns for supported workloads — for example, Multi-AZ SQL Server deployments or SAP HANA with host auto-failover — patterns that would otherwise require careful manual configuration to get right.

College/Student Use Case 🎓

Most student AI/ML projects don't need enterprise applications like SAP. But a college Computer Science or Cloud Computing department could use Launch Wizard in a few practical ways:

 Cloud Computing / Systems Course
                │
                ▼
         AWS Launch Wizard
                │
        ┌───────┴───────┐
        ▼               ▼
   Pick an App      Enter Sizing
 (e.g. SQL Server)   Requirements
        │               │
        └───────┬───────┘
                ▼
      Review Cost Estimate
                │
                ▼
   Compare vs. Manual Setup

Example use cases on campus:

A database systems course could use Launch Wizard to stand up a Microsoft SQL Server instance for a lab exercise, then have students compare the automatically-recommended instance type against what they would have chosen manually.
An enterprise systems / ERP elective could use Launch Wizard's SAP deployment patterns to give students exposure to how real organizations deploy SAP on AWS, without requiring every student to know SAP sizing rules from scratch.
A cloud computing lab could use the cost-estimation step as a teaching tool for cloud cost awareness — showing students how sizing choices (more nodes, higher availability) directly affect projected cost before anything is even deployed.

This makes Launch Wizard more of a teaching tool for infrastructure decision-making than a service every student would use in a personal project.

Simple Example

Since Launch Wizard is console-driven rather than CLI/code-driven for most workflows, here's what a basic walkthrough looks like conceptually:

1. Open AWS Launch Wizard console
2. Select application: "SQL Server"
3. Enter requirements:
     - Deployment pattern: Single instance
     - Performance tier: Standard
     - Storage: 100 GB
4. Launch Wizard recommends:
     - Instance type: (e.g. r5.xlarge)
     - EBS volume: (e.g. gp3, sized for workload)
     - Estimated monthly cost: $XX
5. Review and adjust configuration if needed
6. Approve → Launch Wizard provisions via CloudFormation

For a student walkthrough or workshop, you can go through steps 1–4 (viewing the recommended resources and cost estimate) without approving the final deployment — this avoids incurring charges while still showing how the sizing and estimation process works.

Advantages

Faster Time to Value — reduces the lead time for standing up complex enterprise applications from weeks to hours.
Reduced Delivery Risk — embeds AWS-recommended best practices into the deployment workflow, so you're less likely to under- or over-provision.
Upfront Cost Visibility — you see and can adjust estimated costs before resources are provisioned, not after the bill arrives.
Repeatable Deployments — the underlying CloudFormation templates can be reused for future deployments instead of starting from scratch.
Less Manual Expertise Required — you don't need to already know the ideal instance/EBS combination for SAP or SQL Server; Launch Wizard applies that knowledge for you.

Limitations / Things to Consider

Cost
Launch Wizard itself doesn't add extra charges beyond the underlying AWS resources it provisions, but the applications it targets — SAP, Multi-AZ SQL Server — are enterprise workloads and can be significantly more expensive than a single small EC2 instance. The built-in cost estimator is worth reviewing carefully before approving any deployment, and students should be cautious about actually deploying (versus just reviewing recommendations) in a workshop setting.

Complexity
Launch Wizard simplifies infrastructure decisions, but it doesn't remove the need to understand your application's requirements — database edition, licensing model, high-availability needs, and Active Directory setup still need to be understood to answer its questions correctly. It also currently supports a specific, growing list of applications rather than being a general-purpose deployment tool.

Scalability
Launch Wizard is well-suited to standing up an initial production-ready deployment with sensible sizing. However, as usage grows, the deployed resources still need to be monitored and scaled using normal AWS practices (right-sizing instances, adjusting storage, adding nodes) — Launch Wizard doesn't manage ongoing scaling for you after deployment.

Security
Because Launch Wizard provisions real infrastructure — including networking and, for some applications, Active Directory — it's important to review the IAM permissions and VPC/security group settings it configures. As with any AWS deployment, the principle of least privilege should be applied to whoever has permission to launch or modify these deployments.

Conclusion

AWS Launch Wizard is not a service every student will use in a day-to-day project, but it solves a real and specific problem: deploying complex, enterprise-grade applications without needing to be an infrastructure specialist for each one.

Working through it helped me understand the overall process:

Choose Application
       ↓
Enter Requirements
       ↓
Review Resources + Cost
       ↓
Approve Deployment
       ↓
Production-Ready Application

For a college AI/ML or Cloud Computing department, Launch Wizard is a useful example of how AWS packages best-practice infrastructure decisions into a guided workflow — sitting between raw infrastructure-as-code tools like CloudFormation and fully managed application services.

The main takeaway for me was simple: not every deployment needs to be built resource-by-resource. Sometimes describing the requirement and letting the platform recommend the architecture is the more practical approach — and Launch Wizard is AWS's answer to that idea for a specific set of enterprise applications.

References

AWS Launch Wizard — Overview
AWS Launch Wizard — How It Works
AWS Launch Wizard for SAP
AWS Launch Wizard User Guide

Cloud-Native Systems & Applied AI Integration

JEEVA PRAKASINI G — Tue, 15 Sep 2026 18:15:04 +0000

Cloud-Native Systems & Applied AI Integration — Day 2: EC2, Linux, Nginx, and Tying It All Together Continuing my hands-on workshop notes — this time diving into compute, servers, and end-to-end data flow on AWS.

Picking Up From Day 1

Day 1 covered the fundamentals — IAM basics, AWS Regions, and hosting a static portfolio through S3 and CloudFront. Day 2 moved from storage into compute, and then brought everything together into one connected workflow spanning EC2, S3, and CloudFront.

The tools and services covered:

Amazon EC2
IAM (users & permissions)
Amazon S3
Amazon CloudFront
Amazon CloudWatch
AWS Launch Wizard
AWS CLI
Linux
Nginx

Setting Up IAM Properly

Before touching any compute resources, I created a dedicated IAM user with scoped permissions instead of working from the root account — following the same principle from Day 1:

Give identities only the permissions they actually require.

This IAM user was the one used for the rest of the day's exercises, including CLI access later on.

Launching an EC2 Instance

The core of Day 2 was Amazon EC2 — AWS's virtual server service.

I launched an Ubuntu EC2 instance, which involved:

Choosing an AMI (Ubuntu)
Selecting an instance type
Configuring a key pair for SSH access
Setting up a security group (opening ports for SSH and HTTP)

AWS Console
    ↓
EC2
    ↓
Launch Instance
    ↓
Choose Ubuntu AMI
    ↓
Configure Instance / Key Pair / Security Group
    ↓
Launch
    ↓
Connect via SSH

Exploring AWS Launch Wizard

Alongside the manual EC2 setup, I also explored AWS Launch Wizard — a service designed to simplify deploying common application infrastructure by handling sizing, configuration, and provisioning based on a chosen application type, rather than configuring every resource by hand.

It was a useful contrast to see: EC2 launched manually (full control, more steps) versus Launch Wizard (guided, opinionated, faster for standard deployments).

**
Connecting to EC2 and Working With Linux**

Once the instance was running, I connected to it over SSH and worked directly in the Ubuntu shell — updating packages, navigating the filesystem, and installing software from the command line.

Local Machine
    │
    │ ssh -i key.pem ubuntu@<public-ip>
    ▼
EC2 (Ubuntu)

Basic Linux commands (apt update, apt install, cd, ls, sudo) were the backbone of everything that followed on the server side.

📸 Screenshot: ssh-connection.png — connected to the EC2 instance via SSH
**
Installing and Configuring Nginx**

With the server accessible, I installed Nginx on the Ubuntu instance to serve as the web server.


sudo apt update
sudo apt install nginx
sudo systemctl start nginx
sudo systemctl enable nginx

After installation, hitting the instance's public IP in a browser confirmed the default Nginx welcome page was being served — a good checkpoint before customizing anything further.
**
Working With Data: EC2, AWS CLI, and S3**

This part tied compute and storage together using the AWS CLI.

I downloaded a Stranger Things dialogue dataset onto the EC2 instance, then used the AWS CLI to upload it directly from EC2 into an S3 bucket:

# On the EC2 instance
aws configure          # set up IAM user credentials
wget <dataset-url>     # download the dataset onto EC2

aws s3 cp stranger-things-dialogues.csv s3://<bucket-name>/

This demonstrated a common real-world pattern: processing or staging data on a compute instance, then pushing it to durable storage — rather than working with everything locally.

Dataset Source
      │
      ▼
   EC2 (Ubuntu)
      │
      │ aws s3 cp
      ▼
   S3 Bucket

Hosting a Static Website on S3 (Again — This Time End-to-End)

Using the same bucket, I set up static website hosting on S3, similar to Day 1, but now as part of a fuller pipeline that started on EC2.

EC2 → AWS CLI → S3 Bucket → Static Website Hosting

Delivering Through CloudFront

As the final step, I connected the S3-hosted site to a CloudFront distribution for content delivery — the same pattern from Day 1, now applied to a bucket populated via the EC2 → CLI → S3 workflow.

User
 │
 ▼
CloudFront
 │
 ▼
S3 Bucket (populated via EC2 + AWS CLI)
 │
 ▼
Static Website

Monitoring With CloudWatch

To round things out, I looked at Amazon CloudWatch for monitoring the EC2 instance — metrics like CPU utilization and basic status checks, giving visibility into how the instance was performing.


EC2 Instance
      │
      ▼
  CloudWatch
      │
      ▼
Metrics / Alarms / Dashboards

Putting It All Together

IAM User Created
      ↓
EC2 (Ubuntu) Launched
      ↓
Connected via SSH
      ↓
Nginx Installed & Configured
      ↓
Dataset Downloaded on EC2
      ↓
AWS CLI Configured
      ↓
Dataset Uploaded to S3
      ↓
Static Website Hosted on S3
      ↓
CloudFront Distribution Connected
      ↓
CloudWatch Monitoring EC2

Key Takeaways

EC2 gives you a real server, not an abstraction — Linux fundamentals matter the moment you SSH in.
Nginx is a quick way to get a web server running on a fresh instance.
The AWS CLI bridges compute and storage — moving data from EC2 to S3 is a pattern used constantly in real pipelines.
Launch Wizard vs manual EC2 setup highlights the trade-off between speed/guidance and full control. 5.CloudWatch closes the loop — once something is deployed, monitoring it is just as important as building it.

Wrapping Up

Day 2 connected the dots between compute and storage — going from a bare Ubuntu EC2 instance all the way to a monitored, CDN-delivered static site, with a real dataset moved through the pipeline via the AWS CLI along the way.

More notes to come as I keep exploring Docker, Kubernetes, and the AI integration components of the workshop.

Rhyming Game Contest Cloud Workshop: AWS Launch Wizard – Service Identification and Verification

JEEVA PRAKASINI G — Tue, 15 Sep 2026 17:01:08 +0000

Cloud Workshop – AWS Launch Wizard

Introduction

As part of the Cloud Workshop, I was assigned the task of identifying and exploring an AWS service based on a specified starting letter. For this activity, I selected AWS Launch Wizard, which starts with the letter L.

AWS Launch Wizard is an AWS service under the Management & Governance category. It provides a guided way to configure and deploy supported applications and workloads on AWS. Instead of manually configuring every AWS resource, users can follow a structured workflow to specify their requirements and validate the configuration before deployment.

The purpose of this activity was to become familiar with the AWS Management Console, understand the selected AWS service, identify its key features, and study a practical real-world use case.

Objective

The main objectives of this activity are:

To identify an AWS service starting with the required letter.
To access the selected service through the AWS Management Console.
To understand the purpose and functionality of AWS Launch Wizard.
To identify the key features of the service.
To understand a real-world use case.
To explore a practical example of using the service.
To document the process with screenshots.

AWS Service Selected

Service Name: AWS Launch Wizard
Starting Letter: L
Category: Management & Governance

AWS Launch Wizard helps users simplify the deployment of supported workloads on AWS. It provides a guided workflow where users can select a supported workload, enter configuration details, validate the configuration, and proceed with deployment.

The service is particularly useful when a workload requires multiple AWS resources and configurations. It reduces the need to manually configure every component individually.

AWS Launch Wizard Workflow

The basic workflow of AWS Launch Wizard can be represented as follows:

AWS Management Console
↓
AWS Launch Wizard
↓
Select Supported Workload
↓
Configure Requirements
↓
Validate Configuration
↓
Deploy Workload
↓
AWS Resources Created

Figure 1: Basic AWS Launch Wizard Workflow

[Insert your diagram/image here]

Key Features 5.1 Guided Deployment

AWS Launch Wizard provides a guided deployment process. It helps users configure supported workloads through a structured workflow rather than requiring them to manually configure every AWS component.

This makes the deployment process easier to understand and reduces manual configuration effort.

5.2 Workload-Specific Configuration

Launch Wizard provides configuration options based on the supported workload selected by the user. The user can specify requirements related to compute, networking, storage, and other components.

This provides a more organized approach to configuring an application environment.

5.3 Configuration Validation

Before deployment, the configuration can be validated to identify potential configuration problems. This helps reduce the possibility of deployment failures caused by incorrect settings.

5.4 Automated Resource Provisioning

After the configuration is completed and validated, AWS Launch Wizard can help provision the required AWS resources for supported workloads. This reduces the amount of manual infrastructure setup required.

Step-by-Step Procedure Step 1: Login to AWS Management Console

I opened the AWS Management Console using a web browser and logged in using my AWS account.

Screenshot 1: AWS Management Console

Step 2: Search for AWS Launch Wizard

I used the search bar available at the top of the AWS Management Console and searched for:

Launch Wizard

The AWS Launch Wizard service appeared in the search results.

Screenshot 2: Searching for AWS Launch Wizard

Step 3: Open AWS Launch Wizard

I selected AWS Launch Wizard from the search results. The Launch Wizard console opened successfully.

Screenshot 3: AWS Launch Wizard Console

Step 4: Explore the Service

I explored the Launch Wizard interface and reviewed the available options and information provided by the service.

The interface provides a guided approach for configuring supported workloads and preparing them for deployment.

Screenshot 4: AWS Launch Wizard Interface

Step 5: Avoid Unnecessary Resource Creation

For this workshop activity, I did not launch any additional infrastructure. This was done to avoid creating unnecessary AWS resources that could result in charges.

The activity focused on identifying and exploring the AWS service and understanding its functionality.

Real-World Use Case

A real-world use case of AWS Launch Wizard is the deployment of enterprise workloads on AWS.

For example, an organization may want to migrate an existing enterprise application from an on-premises environment to AWS. Such an application may require several components, including compute instances, networking, storage, security configurations, and application-specific settings.

Manually configuring all these resources can be time-consuming and may lead to configuration errors. AWS Launch Wizard can provide a guided deployment process for supported workloads, helping administrators configure the required environment in a more systematic manner.

This can be useful for organizations that want to simplify the deployment of supported enterprise applications while reducing manual configuration work.

Practical Example

Consider an organization that wants to deploy a supported enterprise workload on AWS.

Without a guided deployment service, an administrator may need to manually perform several tasks, such as:

Creating a VPC.
Configuring subnets.
Configuring security groups.
Selecting appropriate compute resources.
Configuring storage.
Setting application-specific parameters.
Validating the configuration.
Deploying and testing the application.

Using AWS Launch Wizard, the administrator can follow a guided workflow, provide the required workload configuration, validate the settings, and proceed with deployment.

This provides a more structured approach compared with manually configuring each AWS resource separately.

Benefits

AWS Launch Wizard provides several benefits:

Simplified deployment: Provides a guided process for supported workloads.
Reduced manual effort: Reduces the need to manually configure multiple AWS resources.
Configuration validation: Helps identify configuration issues before deployment.
Workload-specific setup: Provides configuration options based on the selected workload.
Automated provisioning: Can provision required AWS resources for supported workloads.
Better deployment organization: Provides a structured workflow for application deployment.

Limitations and Considerations

AWS Launch Wizard is designed for supported workloads and deployment scenarios. It is not a universal deployment tool for every type of application.

Users should also carefully review the configuration before starting an actual deployment. AWS resources created during deployment may incur charges depending on the resources and services used.

Therefore, users should understand the resources being created and monitor their AWS billing when performing practical deployments.

For this workshop, I explored the service without launching additional infrastructure.

AWS Documentation

The following official AWS documentation was referred to for understanding AWS Launch Wizard:

AWS Launch Wizard Documentation:
https://docs.aws.amazon.com/launchwizard/

AWS Launch Wizard User Guide:
https://docs.aws.amazon.com/launchwizard/latest/userguide/what-is-launch-wizard.html

AWS Management Console:
https://aws.amazon.com/console/

These resources provide official information about AWS Launch Wizard, its capabilities, supported workloads, configuration, and deployment process.

Result

AWS Launch Wizard was successfully identified and accessed through the AWS Management Console. The service interface, purpose, key features, real-world use case, and practical application were explored successfully.

The selected AWS service starts with the letter L, satisfying the service-selection requirement of the Cloud Workshop.

Conclusion

This activity provided practical exposure to the AWS Management Console and helped me understand how AWS services can be searched, accessed, and explored.

Through the exploration of AWS Launch Wizard, I learned how a guided AWS service can simplify the configuration and deployment of supported workloads. I also understood the importance of configuration validation and resource planning before deploying cloud infrastructure.

The activity helped connect cloud computing concepts with a practical AWS deployment scenario. It also highlighted the importance of understanding the AWS resources involved and considering potential costs before launching infrastructure.

Screenshots

The following screenshots are included as evidence of the activity:

AWS Management Console
AWS Console search showing Launch Wizard
AWS Launch Wizard service page
AWS Launch Wizard interface

References AWS Documentation – AWS Launch Wizard https://docs.aws.amazon.com/launchwizard/ AWS Launch Wizard User Guide https://docs.aws.amazon.com/launchwizard/latest/userguide/what-is-launch-wizard.html Amazon Web Services https://aws.amazon.com/

Tags: #AWS #CloudComputing #CloudWorkshop #AmazonWebServices #AWSTraining #CloudComputingJourney