Accelerate end-to end DevOps with generative AI

Software development and IT operations face significant challenges due to the complexities of modern systems and increased demand for faster release cycles. This session is packed with demos on how you can mitigate these challenges with generative AI to accelerate end-to-end DevOps processes. We explain how builders and developers can save time and speed up application development with key tools on AWS. We share how to use Code Catalyst and Amazon Q to bring your idea to runnable and mergeable code. Understand how to debug workflows easily and set up development project using blueprints within minutes. We outline the real-world use cases demonstrating how large language models (LLMs) and code generation can reduce manual effort across the DevOps lifecycle. By the end of the session, learn how to use generative AI to streamline tasks such as deployment pipeline development, testing, infrastructure provisioning, and incident remediation. The session also features best practices for implementing responsible AI in DevOps practice.

Speaker: Tuan Hyunh, Senior Cloud Architect, AWS Professional Services