DynamoDB powers everything from indie apps to Amazon-scale workloads, yet many teams barely scratch the surface of what it can do. In this session we’ll strip away the mystique, explore the service’s key building blocks, and see how they work together in practice. Then we’ll tackle the (in)famous single-table design - why it’s worth considering, where it shines, and where it might not. You’ll leave with a clear mental model, practical design guidance, and the confidence to build a DynamoDB schema that stays fast, cost-aware, and ready for whatever your roadmap throws at it.

ip.labs is the world’s leading white label e-commerce software imaging company and processes millions of images every day. The workflows of our users consist of designing, saving, loading, ordering and delivering to the printing facilities the photo products like prints, photobooks, calendars, gift products among others. In this talk we’ll explore our motivation and architecture behind the reimplementation of our image storage solution based on AWS Serverless services like API Gateway, Lambda, DynamoDB, SQS, SNS, EventBridge, Kinesis and others. We’ll especially dive deeper into the parts using event-driven communication and explore patterns like storage-first, fan out, change log and cross-account logging among others and explain our architectural decisions.

In this session I talk about all things that can be represented as code: starting from the very basic software and ending modern approaches such as infrastructure as code and observability as code

AWS doesn’t have a Flux Capacitor per se, but it relies on a key concept that, without it, we wouldn’t be able to use its services at all: the network. Sometimes, I think we just grant it this and forget that it is the base, and when we give a peak to the available network services, the number of them can be overwhelming. Some of them run in the background of other trendy services like Bedrock or are the base of core ones like EC2. That’s why I want to share some lessons I wish I had known when I started working in AWS 12 years ago. Join me in this session, where we will see a use case that required a hybrid connection between AWS and our On-Premises System, the challenges we had during the setup and debugging of our environment, and check some tips while using services like Site-to-Site and Client VPN, AWS Global Accelerator, Route 53 Resolver, PrivateLink and Redshift, Glue, Lambda VPC integration, to get our environment beyond 88 MPH.

As software developers, we’re all guilty of having at least a few unfinished side projects collecting dust on our GitHub repositories. For me, blogging was one of those ideas that stayed on my to-do list for ages until AWS Amplify changed the game. In this session, I’ll share how I used AWS Amplify to stop procrastinating and finally build a platform to share content focused on helping women and tech beginners navigate their tech journeys. We’ll explore how Amplify makes it easy to deploy frontend apps, add storage, connect to real-time data sources, and scale seamlessly. The best part? All of that without needing deep cloud expertise. Join me as I walk through my journey from idea to execution with AWS Amplify and learn how you can do the same to bring your projects to life, breaking free from procrastination.

This session explores the Model Context Protocol (MCP) from basic concepts to practical applications. We’ll start with generative AI fundamentals and quickly move to how MCP enhances AI systems through structured context handling.

We’ll examine MCP’s technical architecture and how it improves conversations with AI by enabling RAG systems and agent workflows. The presentation breaks down MCP’s key components and integration points for developers looking to implement this technology.

The talk concludes with live demonstrations of MCP in action: knowledge retrieval using Amazon Bedrock, Kubernetes troubleshooting automation, and Terraform code generation. Attendees will learn how to leverage MCP to build more capable AI applications across various technical domains.

AWS Strands Agents is fresh out of the lab, a brand-new framework for building and orchestrating intelligent agents. In this session, we’ll explore how to tame that new power with a familiar toolset: object-oriented design. You’ll learn how to break agents into clean, testable components, keep their state organized, and build systems that are easy to extend as the technology evolves. We’ll look at practical examples, pitfalls to avoid, and why combining OOP patterns with this bleeding-edge AWS SDK can give you a serious head start in building the next generation of agent-driven applications.

Examples of functionless (a.k.a. Lambda-less) integration pattern, where a direct integration between two AWS services is configured instead of using custom code in an intermediary Lambda function, based on Step Functions, AppSync, EventBridge.

In complex data platforms powered by AWS Glue, AppFlow, Airflow, and Step Functions, operational issues are inevitable. This talk shares how we built a self-healing system that automatically detects issues, tags them with context, uses Bedrock-based LLMs to suggest resolutions, and keeps stakeholders informed via GitLab and Slack. The result: a 40% drop in incident volume and significantly faster resolution times.

Key takeaways: • Using automation + AI for smarter incident workflows • Practical use of Bedrock in a data engineering context • Bridging operations and business with structured communication

This session is about pushing boundaries with AWS hybrid architectures. We’ll explore how to combine Raspberry Pi nodes, EKS, DMS, and generative AI for smarter data transfer and flexible hybrid setups. It’s a practical and innovative way to handle complex workloads on a budget.

This presentation highlights the business and customer impact of downtime in critical services. It also demonstrates how Hapag-Lloyd’s Web&Mobile department introduced a multi-region architecture to build resilience and ensure business continuity.

Cloud cost optimization isn’t about clever billing tricks, there are no shortcuts here. It’s about engineering maturity. If you’re serious about lowering your cloud spend without breaking your velocity, join this presentation. We’ll look at why savings plans and tools aren’t enough, how finance and engineering often misalign, and what high-maturity teams do differently. You’ll leave knowing what to focus on and where the real impact lies.

Search engines guide users from their initial goals to the information that fulfills those goals. The retrieved items are deemed relevant when they align with the user’s intent. Ensuring relevant results involves having the data in the catalog, analyzing it accurately, representing it through text and vectors, ranking it appropriately, and performing other actions. In this session, discover how auction houses utilize vector search, powered by Amazon OpenSearch Service, to find similar items within their extensive database, enhancing the customer experience and preventing issues with counterfeit artworks, and see how it assists users in obtaining the most relevant results. This session also uncovers some peculiarities in getting embeddings with AWS Bedrock and AWS SageMaker serverless inference for the abovementioned goals.

Building RAG-powered agents doesn’t have to come with sky-high vector database costs. In this session, learn how to create an Amazon Bedrock Agent backed by Amazon S3 Vectors, a new low-cost vector storage option that cuts vector storage and query costs by up to 90%.

We’ll walk through:

1. Setting up a Bedrock Knowledge Base using S3 Vectors for semantic retrieval
2. Creating a Bedrock Agent that can reason over a large-scale knowledge base
3. Designing embeddings, chunking, and metadata filtering strategies for accurate results

Whether building internal copilots, customer support bots, or document search, this talk shows how to do RAG at scale without the price tag of high-performance vector databases. This is ideal for developers and teams looking to build practical, budget-friendly GenAI apps on AWS.

In this hands-on workshop you will learn how to build agentic applications on AWS using the Model Context Protocol (MCP) and the AWS Strands SDK. We will cover the core concepts, how to define tools and capabilities, how to ground agents in enterprise knowledge, and how to orchestrate complex tasks securely. You will leave with practical examples you can adapt to your own use cases.

What happens when AI makes code writing the easiest part of development? The rise of Generative AI has transformed software development, making rapid prototyping more accessible than ever. This keynote examines the evolving role of developers as AI reshapes traditional coding practices. The presentation cuts through both hype and fear to explore what truly matters in modern software development. Learn why moving from intuition-based ‘vibe coding’ to structured engineering approaches becomes more crucial with AI assistance. The session demonstrates how specification-driven development and engineering principles create the foundation for successful AI collaboration.