Modern enterprise architecture is evolving far beyond traditional microservices.

Today's architects must understand not only how to decompose a monolith, but how to design distributed systems that are resilient, secure, observable, cloud-native, event-driven—and increasingly ready for Generative AI, RAG, and Agentic AI.

Microservices Architecture: Cloud-Native to Agentic AI is an architecture-first journey from traditional enterprise applications to modern, production-ready distributed systems.

Rather than focusing on one programming language or framework, this course teaches you how to think, reason, and make decisions like an architect.

Throughout the course, you will progressively architect ShopApp, an enterprise e-commerce platform that evolves from a monolith into a production-grade, cloud-native and AI-enabled architecture.

What You Will Learn

You will learn how to:

Identify the right service boundaries using business capabilities and domain ownership
Decompose monolithic applications into independently evolvable microservices
Design synchronous APIs, asynchronous messaging, and event-driven architectures
Use Kafka and events to reduce coupling between enterprise services
Design distributed data ownership and handle cross-service transactions using Saga patterns
Build resilient systems using timeouts, retries, circuit breakers, idempotency, and safe recovery
Secure microservices using authentication, authorization, API gateways, zero-trust principles, and service-level controls
Design cloud-native platforms using containers, Kubernetes, service discovery, configuration, and deployment strategies
Build observability into distributed systems using logs, metrics, traces, correlation, and production monitoring
Apply proven microservices design patterns and production best practices
Evaluate architecture trade-offs and document important decisions using Architecture Decision Records
Conduct architecture reviews and identify architectural warning signs before production
Extend microservices architectures with Generative AI and Retrieval-Augmented Generation (RAG)
Understand how Agentic AI and AI agents fit into modern enterprise architectures
Design governed AI-agent interactions with enterprise APIs, tools, data, and business services
Take architecture from business requirements through design, review, production readiness, and continuous evolution

A Complete Architecture Journey

The course follows an evolving architecture rather than presenting disconnected concepts.

You will see ShopApp progress through:

Monolith → Microservices → Event-Driven Architecture → Cloud-Native Platform → Secure & Observable Architecture → AI-Augmented Architecture → Agentic AI

Each architectural capability is introduced because a real problem creates the need for it.

You will see why architectures evolve—not simply what the final diagram looks like.

Architecture First, Not Framework First

This is not another course centered around writing CRUD microservices in a particular framework.

The focus is on the decisions that remain relevant regardless of whether your organization uses Java, .NET, Python, Go, AWS, Azure, Google Cloud, or another technology stack.

You will learn the reasoning behind questions such as:

Where should service boundaries be drawn?
When should services communicate synchronously or asynchronously?
Who owns the data?
How do distributed transactions work without a shared database?
What happens when a downstream service fails?
How do we secure hundreds of service interactions?
How do we diagnose one failed transaction across many services?
When does Kubernetes become useful?
When should you NOT use microservices?
How do GenAI, RAG, and AI agents integrate without bypassing enterprise governance?

Production-Ready Architecture

Designing services is only the beginning.

The course explores the capabilities required to operate distributed systems in production, including resilience, security, observability, deployment, data consistency, governance, architecture reviews, and production-readiness decisions.

You will also learn how to recognize common architecture smells and avoid creating a distributed monolith or uncontrolled microservices sprawl.

From Microservices to AI-Native Systems

The final part of the journey moves beyond conventional microservices.

You will explore how enterprise systems can incorporate:

Generative AI, RAG, enterprise knowledge retrieval, AI agents, tools, governed APIs, Agentic AI, observability, security, and human oversight.

The objective is not to add AI because it is fashionable. It is to understand where AI belongs in enterprise architecture—and where it does not.

Who This Course Is For

This course is designed for:

Solution Architects
Software Architects
Enterprise Architects
Senior Developers and Technical Leads
Cloud and Platform Engineers
DevOps professionals
AI and software professionals
Technology consultants
Developers preparing to move into architecture roles
Anyone responsible for designing or modernizing enterprise applications

By the End of the Course

You will have followed a complete enterprise architecture from an initial monolithic system through production-grade microservices and ultimately into an AI-native, agent-enabled architecture.

More importantly, you will have developed a reusable way of thinking:

Understand → Discover → Decide → Design → Validate → Deliver → Observe → Evolve

Because architecture is not simply about drawing diagrams.

Architecture is about making deliberate decisions, understanding their trade-offs, and evolving systems safely as business and technology change.