Fundamentals of Cloud Computing and OpenAI with Microsoft Azure

This course offers a comprehensive introduction to cloud and serverless computing, focusing on Microsoft Azure's key services and Azure's artificial intelligence (AI) platform. We contrast the challenges and benefits of cloud computing, serverless cloud computing, and traditional self-managed cloud and on-premises solutions. Students learn the fundamental architecture and design patterns necessary to build geographically distributed, highly available, and scalable solutions using key services in the Microsoft Azure platform. Students learn about the OpenAI offerings in Azure and how to responsibly leverage them in their cloud-native solutions, with hands-on experience in prompt engineering, fine tuning, and embedding. We cover the costs and benefits of each and how to pragmatically apply them. Students engage in hands-on learning architecting secure, scalable, geo-redundant, and cost-effective infrastructure and deploying that infrastructure to Microsoft Azure using infrastructure as code via the Bicep language. Students learn approaches for building solutions that gracefully degrade when non-essential functionality is unavailable. Students learn to implement defense in depth using network segmentation (VNETs) and additional best practices. A wide range of Microsoft Azure Services are covered including Azure Front Door, Azure App Services, Azure App Configuration, KeyVault, Azure SQL, Azure API management; serverless services including Azure Functions, and Azure Logic Applications; Microsoft Entra ID (formerly Azure Active Directory) for enterprise identity management; Azure B2C for low-cost identity management on consumer-centric software-as-a-service offerings; and Azure Storage, Azure Service Bus, Azure Event Grid, Azure Event Hub, Azure Cosmos database, and Azure Cognitive Search. In addition to Azure services and guidance, the course covers implementing processes to streamline development, such as continuous integration, continuous deployment (CICD), and automated testing. Students also learn how to test their applications and infrastructure at scale using Azure Load Testing. Coverage includes always-up architecture and deployment strategies, rollback strategies, A/B testing, testing in production, monitoring, distributed tracing, alerting, performance tuning, snapshot debugging in production, and health analysis using Application Insights and Azure Monitor. Additionally, students learn strategies and architecture for ensuring data sovereignty concerns are addressed in their solutions.