GenAI can do incredible things, but like any technology, its success depends on how we implement and use it. Without proper implementation, GenAI failures can pose significant risks to your organization's reputation and customer trust, leading to real financial impact. And like any other application, regulatory rules, SLAs, and reliability standards still apply to GenAI.

With more companies integrating GenAI into their systems and products, it’s essential to make sure GenAI workloads and applications are highly available to deliver an exceptional user experience.

But how do you actually do that? How is it different than standard resilience efforts, and how is it the same?

In this webinar with AWS and Gremlin, we’ll go over how customers are using GenAI workloads on AWS, how the reliability pillar best practices of the Well-Architected Framework apply, and what you can do to improve the resilience and uptime of your GenAI-related workloads.

Includes a live demo of how to test the resilience of GenAI workloads with Gremlin.

Key Takeaways:

–Common GenAI architectures
–Reliability best practices specific to GenAI workloads—both managed and unmanaged
–Standard reliability practices that you can apply beyond GenAI