Anthony McClure

Customers make deliberate choices about where their workloads run. For SaaS vendors delivering agentic products, that means the runtime has to meet the workload where it is, not the other way around.

Vibe coding is fun and fast, but can leave hidden gaps when building production SaaS. In this hands-on builder session, step into the role of an AWS developer tasked with readying a vibe coded SaaS application for go-live.

Most SaaS environments include some notion of a control plane. This plane support all the cross-cutting needs of a SaaS environment (onboarding, billing, metering, tenant management, etc.).

GenAI-powered development tools are changing how teams build multi-tenant agentic SaaS software. It's time to see how these tools can be used to accelerate the creation of entire SaaS environments.

Multi-tenant SaaS environments must be able to efficiently react and respond to a diverse and shifting set of workloads. It’s your job to implement scaling, onboarding, tiering, data partitioning, tenant isolation, and other multi-tenant strategies that can gracefully support these workloads.

A SaaS architecture must be able to support shifting workloads, complex scaling policies, isolation and a host of other multi-tenant considerations. You need to understand how your system will react and respond to these challenges.

Building any SaaS solution begins with the creation of a control plane that provides support for all the cross-cutting multi-tenant constructs that are foundational to building a robust SaaS environment.

Building solutions that package and offer ML capabilities in a SaaS model can be tricky. There is a wide range of multi-tenant considerations that can shape how you build, operate, and scale your ML offering in a SaaS delivery model.