VCC Assignment 3: Create a Local VM and Auto-Scale It to Any Public Cloud Platform When Resource Usage Exceeds 75% in Local VM

Student Name: Ashutosh Nigam
Roll Number: M25AI2006
Course: Virtual Cloud Computing (VCC)
Cloud: Amazon Web Services (AWS)
Assignment Report: M25AI2006_Assignment_3.pdf

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Problem Statement

Create a local VM and implement a mechanism to monitor resource usage. Configure it to auto-scale to a public cloud (e.g., GCP, AWS, or Azure) when resource usage exceeds 75%.

Objectives

1. Set up a local virtual machine environment
2. Implement real-time resource monitoring for CPU and Memory
3. Configure auto-scaling policies that trigger cloud deployment when local resources exceed 75% utilization
4. Demonstrate the complete workflow from local deployment to cloud migration
5. Provide comprehensive documentation and demonstration of the system

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Project Overview

This ASP.NET Core Web API application serves as a System Resource Monitor and Load Generator designed to test and demonstrate hybrid cloud auto-scaling capabilities. The application provides endpoints to:

• Monitor system resources (CPU, Memory)
• Trigger controlled CPU spikes
• Trigger controlled Memory spikes
• Provide real-time system status

This API acts as the core application deployed on a local VM that can be monitored by tools like Prometheus/Grafana, which then trigger auto-scaling to cloud platforms when resource thresholds are exceeded.

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Architecture Diagram

Technology Stack

• Framework: ASP.NET Core 8.0
• Language: C# with .NET 8.0
• API Documentation: Swagger/OpenAPI
• Architecture: RESTful Web API

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Prerequisites

Before running this application, ensure you have:

• .NET 8.0 SDK installed
• Windows, Linux, or macOS operating system
• A code editor (Visual Studio, VS Code, or Rider recommended)
• Postman or similar tool for API testing (optional, Swagger UI included)

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How to Run the Application

Method 1: Using .NET CLI (Recommended)

1. Clone or navigate to the project directory:

   cd VCC.Assignment3

2. Restore dependencies:

   dotnet restore

3. Build the project:

   dotnet build

4. Run the application:

   dotnet run

5. Access the application:

   • Swagger UI: http://localhost:5000/swagger or https://localhost:5001/swagger
   • API Base URL: http://localhost:5000/api or https://localhost:5001/api

Method 2: Using Visual Studio

1. Open VCC.Assignment3.sln in Visual Studio
2. Press F5 to run with debugging or Ctrl+F5 to run without debugging
3. Browser will automatically open with Swagger UI

API Endpoints

1. GET /api/system/status

Check if the API is running.

Response:

{
  "status": "API is running"
}

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2. GET /api/system/resources

Get current system resource information.

Response:

{
  "systemName": "Microsoft Windows 10...",
  "osArchitecture": "X64",
  "frameworkDescription": ".NET 8.0.0",
  "processorCount": 8,
  "systemUptime": "01.12:34:56",
  "totalMemoryGB": 16.0,
  "usedMemoryGB": 8.5,
  "memoryUsagePercent": 53.12
}

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3. POST /api/system/memory-spike?spikeSize=<size>

Trigger a controlled memory spike for testing auto-scaling.

Query Parameters:

• spikeSize (optional): Size of memory to allocate
  • Small_500MB (default): 500 MB
  • Medium_1GB: 1 GB
  • Large_2GB: 2 GB
  • XLarge_3GB: 3 GB
  • XXLarge_4GB: 4 GB

Example:

POST http://localhost:5000/api/system/memory-spike?spikeSize=Medium_1GB

Response:

{
  "message": "Memory spike triggered",
  "sizeAllocatedMB": 1024,
  "chunks": 102
}

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4. POST /api/system/cpu-spike?duration=<duration>

Trigger a controlled CPU spike for testing auto-scaling.

Query Parameters:

• duration (optional): Duration of CPU spike
  • Short_5Seconds (default): 5 seconds
  • Medium_10Seconds: 10 seconds
  • Long_15Seconds: 15 seconds
  • XLong_30Seconds: 30 seconds
  • XXLong_60Seconds: 60 seconds
  • XXLong_120Seconds = 120,
  • XXLong_240Seconds = 240

Example:

POST http://localhost:5000/api/system/cpu-spike?duration=Medium_10Seconds

Response:

{
  "message": "CPU spike triggered",
  "durationSeconds": 10,
  "actualDurationMs": 10005,
  "cpuUtilizationTarget": "80%",
  "threadsUsed": 6,
  "totalProcessors": 8
}

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Testing the Application

Using Swagger UI (Easiest Method)

1. Run the application
2. Navigate to http://localhost:5000/swagger
3. Expand any endpoint and click "Try it out"
4. Modify parameters if needed and click "Execute"
5. View the response below

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Project Structure

VCC.Assignment3/
│
├── Controllers/
│   └── SystemController.cs        # API endpoints for system monitoring and load generation
│
├── Properties/
│   └── launchSettings.json         # Application launch configuration
│
├── appsettings.json                # Application configuration
├── appsettings.Development.json    # Development environment settings
├── Program.cs                      # Application entry point and configuration
├── VCC.Assignment3.csproj          # Project file
└── README.md                       # This file

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Contact

Student: Ashutosh Nigam
Roll Number: M25AI2006

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Acknowledgments

• ASP.NET Core Documentation
• Prometheus & Grafana Community
• Virtual Cloud Computing Course Materials
• How to Install and Configure Prometheus and Grafana on Ubuntu
• Node Exporter Full
• Installing Grafana
• Prometheus vs Grafana

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