Institution
Lake Washington Institute of Technology
Project Background
Project Overview
This project was completed as the final capstone assignment for the CSNT257 Cloud Computing course at Lake Washington Institute of Technology. Although the assignment could be completed in a single cloud environment, I chose to implement the deployment independently in Amazon Web Services, Microsoft Azure, and Google Cloud Platform.
Each environment included multi-factor authentication, static website hosting, public and private cloud networks, network peering, public and private virtual machines, connectivity testing, monitoring, CPU alerts, pricing estimates, network diagrams, and resource cleanup.
Completing the same architecture across all three providers created an opportunity to compare terminology, workflows, management interfaces, network design, security controls, monitoring systems, and pricing models.
Project Summary
Cloud Project at a Glance
A multi-platform infrastructure project documenting complete deployments across three major public cloud providers.
Instructor
Dr. Linda Epps
Completed
11 June 2026
Duration
3 Weeks
Environment
Small-to-Medium Enterprise
3
Cloud Platforms
28
Report Pages
3
Static Websites
6
Virtual Machines
6
Cloud Networks
3
Monitoring Alerts
Repeatable Design
Shared Multi-Cloud Architecture
The same general architecture was recreated in each provider, allowing the platforms to be compared using equivalent goals and validation procedures.
MFA
Secure Account
Static Site
Cloud Storage
Public Network
Internet Access
Private Network
Isolated Resources
Peering
Network Routing
Virtual Machines
Public & Private
Monitoring
CPU Alerting
Pricing
Annual Estimate
Static Website Hosting
Published an MSPUB static website using provider-native object or blob storage services.
Public & Private Segmentation
Separated internet-accessible resources from private workloads using dedicated cloud networks and subnets.
Network Peering
Configured private routing between separate public and private cloud network environments.
Connectivity Validation
Verified expected routing behavior between virtual machines, private networks, and internet-connected systems.
Monitoring & Alerting
Configured CPU monitoring and generated test load to validate alert delivery.
Resource Cleanup
Verified that temporary cloud resources were removed after documentation and testing were completed.
Provider Implementations
Cloud Platform Deployments
Each platform fulfilled the same core business and technical requirements using its own services, terminology, and management workflows.
Amazon Web Services
AWS Deployment
The AWS environment used Amazon S3 for static website hosting, separate VPCs for public and private resources, VPC peering, Amazon EC2 virtual machines, security groups, route tables, CloudWatch monitoring, and SNS notifications.
- Amazon S3 static website
- Two Amazon VPC environments
- VPC peering and route tables
- Public and private EC2 instances
- Security groups and ICMP testing
- CloudWatch CPU alarm
- Amazon SNS email notification
- AWS pricing estimate
Microsoft Azure
Azure Deployment
The Azure environment used a storage account with static website hosting, separate virtual networks, virtual network peering, public and private virtual machines, network security groups, Azure Monitor, and budget and cost-estimation tools.
- Azure Storage static website
- Dedicated resource group
- Public and private virtual networks
- Virtual network peering
- Public and private Azure VMs
- Network security groups
- Azure Monitor alerting
- Azure pricing estimate
Google Cloud Platform
GCP Deployment
The Google Cloud environment used Cloud Storage for static website files, separate VPC networks, VPC Network Peering, Compute Engine instances, firewall rules, Cloud Monitoring, and Google Cloud pricing tools.
- Cloud Storage website assets
- Public and private VPC networks
- VPC Network Peering
- Compute Engine instances
- Firewall rules and connectivity tests
- Cloud Monitoring alert policy
- Email notification channel
- Google Cloud pricing estimate
Cross-Platform Analysis
Cloud Service Comparison
Equivalent requirements were implemented with each provider's native services, making their terminology and platform relationships easy to compare directly.
| Requirement | AWS | Azure | Google Cloud |
|---|---|---|---|
| Static Website | Amazon S3 | Azure Storage | Cloud Storage |
| Virtual Network | Amazon VPC | Azure Virtual Network | Google Cloud VPC |
| Virtual Machines | Amazon EC2 | Azure Virtual Machines | Compute Engine |
| Traffic Filtering | Security Groups | Network Security Groups | VPC Firewall Rules |
| Monitoring | Amazon CloudWatch | Azure Monitor | Cloud Monitoring |
| Network Connection | VPC Peering | Virtual Network Peering | VPC Network Peering |
Applied Knowledge
Skills Demonstrated
The repeated deployment strengthened provider-independent skills in cloud networking, security, virtual machines, monitoring, cost analysis, testing, cleanup, and documentation.
- Multi-Cloud Infrastructure Deployment
- Cloud Network Architecture
- Public and Private Subnet Design
- Virtual Network Peering
- Cloud Virtual Machine Administration
- Static Website Hosting
- Cloud Security Configuration
- Monitoring and Alerting
- Connectivity Testing
- Cloud Pricing Analysis
- Resource Lifecycle Management
- Technical Documentation
Submitted Work
Project Deliverable
The project report documents the AWS, Azure, and Google Cloud deployments, including configuration details, screenshots, connectivity tests, monitoring validation, pricing estimates, network diagrams, reflection, and resource cleanup.
Multi-Cloud Technical Report
MSPUB Multi-Cloud Deployment Report
A 28-page implementation report documenting equivalent cloud deployments across Amazon Web Services, Microsoft Azure, and Google Cloud Platform.
28 Pages
AWS
Azure
Google Cloud
Screenshots
Network Diagrams
Pricing Analysis
Available Upon Request
Professional Review Copy
The report is intentionally withheld from public distribution. Supporting documentation, implementation notes, screenshots, and additional project artifacts are available for professional review.
Any shared copy will have credentials and unnecessary account-identifying information removed or redacted.
Request DocumentationProject Reflection
Lessons Learned
This project demonstrated that AWS, Microsoft Azure, and Google Cloud can provide comparable infrastructure capabilities while using different interfaces, terminology, defaults, workflows, and pricing structures.
Repeating the same architecture across three providers improved my understanding of cloud networking, routing, security rules, virtual machines, monitoring, static storage, alerting, and resource lifecycle management.
It also reinforced the importance of multi-factor authentication, careful documentation, cost awareness, verification testing, secure handling of credentials, and deleting temporary resources when cloud labs are complete.
Continue Exploring
Interested in This Cloud Project?
Explore the rest of my technical portfolio or contact me to discuss cloud computing, infrastructure, networking, automation, or professional opportunities.