
Are Property Graphs living up to the hype? Maybe the model itself is the problem.We made the move from relational databases to graph databases to escape "Join Pain" and model the real world more naturally — but for many engineering teams, that promise has curdled into something worse: the Spaghetti Graph.Complex queries. Ugly workarounds for multi-party relationships. Fragile schemas that shatter with every iteration and become a nightmare to maintain.The good news? The problem isn't your data.In this talk, Joshua Send breaks down why standard Labeled Property Graphs (LPGs) fall short when applied to complex domains — and introduces TypeDB, a strongly-typed database that brings together the connectivity of a graph with the integrity of a relational model.You'll come away understanding:Why LPGs struggle at scale and complexityWhat "Spaghetti Graphs" are and how teams fall into the trapHow TypeDB's type system enforces data integrity without sacrificing flexibilityWhen a strongly-typed graph database is the right tool for the jobWhether you're deep in a graph migration, evaluating database architectures, or just tired of schema chaos — this one's for you.

An agent will write you a CDK stack, a Terraform module, or a stack of IAM policies in seconds.
Whether any of it works is a separate question, and the usual way to find out is to deploy to a real AWS account and watch what breaks.
In an agentic workflow, that means giving AI access to a public cloud account, racking up costs on the AWS bill, and waiting for provisioning to complete every time you push new code to the environment.

The rise of agentic AI in the software delivery lifecycle creates a dilemma with high-stakes implications.
As agents create new applications at an unprecedented rate, how do you integrate security without slowing down delivery?

You've been there: Lambda triggers, SQS messages fly, Step Functions execute, and somewhere in the middle, something breaks. You have no idea what triggered what, what payload was passed, or where it all went wrong.
That's the black box problem of AWS development.
Once your architecture grows beyond a single service, visibility disappears fast. You're left stitching together scattered logs and redeploying just to see what's going on.
App Inspector is LocalStack's built-in observability layer that opens up that black box. It gives you a real-time, unified view of every service interaction happening inside your local cloud: what triggered what, with what payload, in what order.
In this talk, we'll walk through what App Inspector is, how it fits into your LocalStack workflow, and how to use it to catch bugs locally before they ever reach staging or production.