AWS Serverless Architecture for Generative AI

Generative AI is transforming how we build software, but managing AI workflows can quickly become complex and costly. Implementing serverless architecture on AWS allows you to build highly scalable, cost-efficient AI applications that scale automatically. In this text-based course, you will learn how to design and connect key AWS serverless components to power generative AI workloads, transitioning from basic cloud concepts to structuring robust, event-driven AI pipelines. What you'll learn: • Understand core serverless concepts and foundational cloud service definitions • Configure AWS Lambda functions to handle generative AI inference and API calls • Orchestrate complex multi-step AI workflows using AWS Step Functions • Manage asynchronous tasks and queueing with SQS for reliable processing • Decouple AI system components using event-driven routing with EventBridge • Integrate vector databases and prompt engineering patterns into serverless pipelines • Monitor and optimize LLM latency and API costs using cloud observability tools. You will start with fundamental terminology and serverless principles before exploring each key component individually. Through written explanations and clear architectural code snippets, you will learn how to stitch these services together into a cohesive backend. This course is designed for software developers, cloud enthusiasts, and beginners eager to explore cloud-based AI systems, with no prior AWS or serverless experience required. Start reading today to build your first serverless generative AI architecture.