
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 complexity, what "Spaghetti Graphs" are and how teams fall into the trap, how TypeDB's type system enforces data integrity without sacrificing flexibility, and when a strongly-typed graph database is the right tool for the job. Whether you're deep in a graph migration, evaluating database architectures, or just tired of schema chaos — this one's for you.

Running your Spring Boot app on AWS for production is common, but testing there can be slow and costly. In this video, we’ll show you how to speed up development using LocalStack. By provisioning your infrastructure with Terraform, you can easily switch to local testing in just three steps: configure your dev environment variables, start LocalStack in Docker, and run your IaC files. Get faster feedback and reduce costs by testing locally with LocalStack!

In this live session, WireMock CTO Tom Akehurst will introduce hybrid API simulation (local + cloud) with WireMock Runner. Tom will explain why we built Runner, how developers are using it today, and how it fits into modern dev and test workflows - such as simulating APIs during testing, prototyping, and AI-native development.

LocalStack Chaos API enables you to simulate outages in any AWS region or service. Chaos API provides an easy way to implement chaos engineering experiments to test a wide variety of simulated outages and failures within your application safely, without impacting your production users. Common examples can include region-wide outages, DNS failovers, service failures, and network faults. All the testing scenarios described above can be executed within LocalStack, providing thorough coverage for critical situations in a matter of minutes rather than hours or days. In this presentation by Viren Nadkarni, we explore how Chaos API is leveraged to perform service failures in a local environment while using robust error handling to address and mitigate such issues.