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:1. Configure your dev environment variables2. Start LocalStack in Docker3. Run your IaC filesGet faster feedback and reduce costs by testing locally with LocalStack!## ResourcesThis project is available in both the open-source and pro versions. LocalStack Pro significantly simplifies development by using Transparent Endpoint Injection.• Project using LocalStack OSS: https://github.com/localstack-samples/sample-shipment-list-demo-lambda-dynamodb-s3• Project using LocalStack Pro: https://github.com/localstack-samples/sample-pro-version-shipment-list-demo-lambda-dynamodb-s3## Documentation• Transparent Endpoint Injection: https://docs.localstack.cloud/user-guide/tools/transparent-endpoint-injection/• Terraform for LocalStack: https://docs.localstack.cloud/user-guide/integrations/terraform/• LocalStack Lambda: https://docs.localstack.cloud/user-guide/aws/lambda/• LocalStack S3: https://docs.localstack.cloud/user-guide/aws/s3/• LocalStack DynamoDB: https://docs.localstack.cloud/user-guide/aws/dynamodbstreams/• LocalStack SQS: https://docs.localstack.cloud/user-guide/aws/sqs/• LocalStack SNS: https://docs.localstack.cloud/user-guide/aws/sns/

Silvio and Carole introduce lstk, LocalStack's next-generation CLI built from scratch in Go. They explain why the team rebuilt the CLI, walk through its key features — zero-config startup, seamless browser-based authentication, and a rich interactive TUI that surfaces real-time progress and actionable errors — and demo how lstk gets you from install to a running emulator in seconds. They also dive into the architecture behind lstk and how it is designed to support multiple emulators, flexible runtimes, and deep integrations with CI pipelines and IDEs.

Cloud-first development kills your inner dev loop. There's a better way.TypeDB on AWS is powerful — Lambda functions querying complex relationship hierarchies, recursive schema functions resolving transitive memberships, all without application logic. But iterating on schemas and queries in the cloud is slow and expensive.Harsh Mishra introduces the TypeDB extension for LocalStack: run a fully functional TypeDB server inside your local AWS environment and connect your app exactly as you would in production. Faster iteration, zero unnecessary spend.

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.