Course Introduction

Modern Application Development Patterns (Web + Mobile + Cloud)

Jason Kuruzovich

2026-01-13

Welcome to ITWS-4500

Advanced Web Systems Development

Today’s Agenda

Learning Objectives

  1. Understand the course structure, expectations, and assessments
  2. Learn a pattern-first way to think about modern applications
  3. Compare common patterns across web and mobile clients
  4. Preview backend, data, and deployment patterns you’ll use all semester
  5. Start thinking about project ideas and teams

About Your Instructor

Jason Kuruzovich

Associate Professor
Lally School of Management

  • Research: AI/ML applications, digital platforms, entrepreneurship
  • Industry: Enterprise software, startups, consulting
  • Teaching: Web systems, data science, analytics

Contact: - Email: kuruzj@rpi.edu - Office: Pitt 2206 - Hours: Tuesday 9-11 AM or by appointment - Book: bit.ly/jason-rpi

Course Overview

Why This Course?

Build production-quality applications as integrated systems.

This is not only about writing code. We’ll focus on:

  • Architecture — how systems are structured and why
  • Patterns — reusable solutions to common problems
  • Trade-offs — choosing “good defaults” and knowing when to change them
  • Integration — making components work together
  • Operations — deploying, monitoring, and evolving systems

Big Idea: Patterns Outlast Tools

Tools and frameworks change quickly.

Patterns stick around:

  • Client ↔︎ server communication
  • Authentication and sessions
  • Data modeling and persistence
  • Scaling and reliability
  • Dev workflows and deployment

A Pattern Map

The Full-Stack View

flowchart LR
    Client["Clients"] --> API["API"] --> Services["Services"] --> Data["Data"]

We’ll revisit this diagram all semester and add details as your systems grow.

Client Patterns: Web vs Mobile

Web Applications

Common pattern:

  • Browser UI (React, Vue, etc.)
  • Communicates over HTTP/HTTPS
  • Mostly stateless requests

Typical concerns:

  • Routing
  • Authentication
  • State management
  • Performance (latency, bundle size)

Mobile Applications

Common pattern:

  • Native or cross-platform app
  • Often the same backend as the web app
  • More constraints (battery, offline use, flaky networks)

Key takeaway: Web and mobile usually share the same backend.

Backend Patterns

API-Centered Design

Most systems revolve around APIs:

  • REST (common default)
  • GraphQL (when it fits)

Typical responsibilities:

  • Authentication & authorization
  • Business logic
  • Validation & error handling

Service Organization

You’ll commonly see:

  • Monolith — everything in one deployable
  • Modular monolith — one deployable, clean internal boundaries
  • Microservices — multiple deployables, more coordination

Rule of thumb: Start simple; add distribution when you have clear reasons.

Data Patterns

Databases (Common Choices)

  • Relational: PostgreSQL, MySQL
  • Document: MongoDB

What Matters More Than the Brand

  • Data modeling (entities, relationships, constraints)
  • Indexing and query patterns
  • Security (least privilege, injection prevention)
  • Migrations and change management

Data Access Pattern

Application → Data access layer → Database

Infrastructure & Deployment Patterns

From Laptop to Cloud

A common progression: 1. Local development 2. Containers (Docker) 3. Cloud deployment

Infrastructure as Code

Instead of manual setup:

  • Configuration files
  • Repeatable environments
  • Version-controlled deployments

If it can’t be reproduced, it’s not done.

AI-Assisted Development

The New Reality

Modern developers use AI to:

  • Generate boilerplate
  • Explore unfamiliar stacks
  • Debug and refactor faster

The Catch

AI is most useful when you understand the underlying patterns.

This course will help you ask better questions and evaluate AI output critically.

How This Course Flows

Patterns → Tools → Systems

We will move from:

  • Concepts and patterns
  • To implementation and integration
  • To deployment and operations

Coming Up

  • Web & API architectures
  • Databases and persistence
  • Docker and deployment
  • Multi-service systems

Expectations

  • You do not need to know every tool in advance
  • You do need to think clearly about design choices
  • Focus on the why behind decisions

Your job this semester: build something real, learn patterns, explain trade-offs.

Logistics

  • Office Hours: Tuesday 9–11 AM, Pitt 2206
  • Email: kuruzj@rpi.edu
  • Appointments: bit.ly/jason-rpi

Next Class

Docker and Infrastructure as Code