<aside>

About

This project showcases the deployment of a secure, scalable, and production-ready web banking application using AWS, Kubernetes, Terraform, Docker, GitHub Actions, and Datadog. It highlights a real-world implementation of DevOps and cloud security principles, executed by a student engineering team.

View deployment video →

</aside>

Project Goal

Successfully deploy a modern 3-tier web banking application composed of backend APIs, a frontend user interface, and a MySQL database. Ensure full deployment on AWS with automated infrastructure provisioning, CI/CD integration, and robust monitoring. Deliver a secure, scalable environment that reflects industry best practices in DevSecOps within a project-based learning framework.

Project Objectives

• Translate classroom theory into real-world project execution with cloud-native architecture.
• Implement a secure, high-availability 3-tier banking application.
• Use Infrastructure as Code (IaC) via Terraform to provision and manage AWS resources.
• Automate builds, tests, and deployments using GitHub Actions.
• Containerize services with Docker and deploy to Kubernetes (EKS).
• Apply DevSecOps practices including monitoring, alerting, and IAM security policies.
• Promote team collaboration through agile methodologies and modern communication tools.
• Achieve continuous improvement through iteration and feedback.
• Document each step with transparency for future scalability and audit-readiness.

Deliverables

• ✅ Live Web Banking Application accessible via private domain.
• ✅ Version-controlled infrastructure and application code in GitHub.
• ✅ CI/CD Pipeline via GitHub Actions with secrets managed securely.
• ✅ AWS Infrastructure: VPC, EC2, EKS, S3, IAM, RDS.
• ✅ Monitoring Stack: Datadog dashboard integrated with Slack alerts.
• ✅ Architecture Diagram showing cloud components and interconnections.
• ✅ Terraform Cloud state management with remote backend.
• ✅ Detailed Documentation: Processes, tools, decisions, and troubleshooting logs.
• ✅ Screenshots and deployment video for verification.
• ✅ Functional and security validations for cloud resources.

Methodologies

1. Hands-on Implementation: Every team member worked on practical tasks, no simulations or mockups.
2. Agile Collaboration: We adopted a lightweight agile approach using Slack, GitHub Projects, and Jira for sprint planning and task tracking.
3. Issue-Driven Progress: We logged blockers in daily check-ins and resolved them collectively.
4. Peer Debugging: Screensharing and peer assistance were critical in resolving GitHub Runner, pipeline, and VPC issues.
5. Feedback Loop: Iterative testing and pipeline checks ensured rapid corrections and learning.

• Team Collabs

Tools and Technologies

We used tools and platforms that empowered automation, transparency, and efficiency.

• Slack: Communication and notification center (linked to GitHub Actions).
• Jira: Core agile tool used for task tracking, sprint planning, and team coordination.
• GitHub & GitHub Actions: Source control, branching strategy, and automation for CI/CD.
• Terraform & Terraform Cloud: Infrastructure provisioning and backend state management.
• Docker: Containerization of backend, frontend, and supporting services.
• Amazon Web Services (AWS): Hosting infrastructure (EKS, EC2, S3, RDS, IAM).
• Datadog: For application and infrastructure monitoring.
• VS Code: Main development IDE.
• MySQL Workbench: Database schema modeling and access.
• PowerShell & Bash: Scripting automation.
• Notepad/Sticky Notes: For quick logging of secrets, tokens, and configs.

<aside>

Development Standards Followed

These are the internal protocols and practices we followed to maintain a consistent, secure, and collaborative development workflow:

• Followed least privilege principle when assigning AWS IAM roles.
• Kept all secrets and tokens in GitHub encrypted secrets, no plaintext in code.
• Used base64-encoded values for sensitive database credentials in Kubernetes secrets.
• Maintained branching standards and commit hygiene for traceable history.
• Conducted pipeline validation after every infrastructure or code push. </aside>

Architectural Design

• Overview
• Infrastructure Components
• Frontend & Backend Flow
• Architectural Image

Monitoring and Notification Setup

Effective monitoring and alerting were essential to maintain visibility, performance insights, and proactive response to any incidents within our deployed banking application. To achieve this, we implemented a comprehensive observability solution using Datadog and integrated it with Slack to provide real-time feedback and ensure team-wide awareness.

• Datadog Configuration
• Slack Integration

Challenges and Solutions

Throughout the project, we faced multiple technical and team-based challenges. Below are some key hurdles and how we tackled them:

• Frontend Deployment Errors
• Kubernetes Manifest Repository Misconfiguration
• Datadog Access Troubleshooting
• Backend Repo Configuration Issue
• Team Coordination
• High AWS Cost Accumulation

<aside>

</aside>

• Step-by-Step Deployment Procedure
• Project Gallery