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This advanced course provides a deep technical exploration of Amazon DynamoDB for developers building production workloads. You will learn how DynamoDB works under the hood, including partitioning, throughput management, indexing, consistency models, streams, and scaling behavior. The course also covers performance optimization, operational best practices, and strategies for building resilient, high-throughput applications. By the end of this course, you will have a strong understanding of DynamoDB’s architecture and the expertise required to confidently design and operate high-performance applications at scale.

Serverless on AWS is powerful — but between context-switching, slow feedback loops, and fragmented tooling, the developer experience often gets in the way of the work itself. This course fixes that. You'll build a complete serverless application from scratch while learning the tools, workflows, and practices that keep you in flow: local development with SAM and LocalStack, AI-assisted coding, automated validation, event documentation, and observability patterns that actually help during development — not just in production. By the end, you'll have a repeatable, professional-grade SDLC for serverless on AWS — one that scales from solo projects to team workflows — and the confidence to ship faster without sacrificing quality. Built for developers who already know serverless. Designed to make you dangerous with it.

Modern distributed systems promise scalability and flexibility, but building microservices that actually work in production is far more complex than most diagrams suggest. In this course, you’ll learn how to design, build, and operate .NET microservices on AWS using patterns and practices proven in real systems. We’ll explore the architectural decisions that matter most when moving from monoliths to microservices, including service boundaries, communication patterns, data ownership, resilience, deployment strategies, and operational trade-offs. You’ll also see how AWS services can be applied pragmatically to support .NET-based microservices, focusing on reliability, scalability, and production realities rather than theoretical architectures. This course is designed for experienced developers, architects, and technical leaders who want to move beyond simplified examples and understand how microservices work in real-world environments.

Deliver high-quality enterprise systems quickly by leveraging the best cloud services. Businesses want everything: high quality, fault tolerance, highly available systems that are cost-effective. Developer expectations are higher than ever. AWS Serverless services help you to exceed them. While at AWS, I led the expert Java and Serverless group. I had the opportunity to work closely with internal AWS service teams and some of the best customer teams. In this course, I will share all the knowledge I gained in those 6 years. We'll dive deep into software choices, project structures, and detailed insights into how AWS Lambda works. After this course, you'll understand all the important choices you need to make when building high-quality systems.

Most expert-level AWS Architecture courses stay at 30,000 feet. This course takes you on the journey from patterns to implementation. Led by AWS Hero Lee Gilmore, you won’t just study diagrams of global-scale systems; you will learn and build the patterns that make them a success. Lee brings the exact architecture design patterns he has used for some of the world’s biggest brands and hands you the keys to the implementation. This is a high-intensity, hands-on masterclass designed to transform you towards an expert, Principal-level Architect. You will go far beyond basic cloud tutorials, learning how to think and behave like a technical leader who owns the entire architectural lifecycle, and how to implement professional, scalable and secure systems that deliver huge value to customers.

Turn your workflow into a system you can version, automate, and scale. In this course, you’ll learn how to apply proven software engineering practices like Git, CI/CD, and modular architectures to knowledge work, transforming scattered tasks into structured, AI-powered workflows. By the end, you’ll be able to design a “productivity operating system” that automates reporting, augments decision-making, and reclaims hours of focused time every week. Help your engineers work on what they do best: create value