Drina

As user bases expand globally and data residency requirements increase, engineering teams often encounter the complex challenge of scaling applications beyond a single AWS region, this is a shared experience for many successful start-ups. In this talk, we’ll cover the real-world journey of how the cloud engineering team at Slido worked on evolving and scaling our setup from a single-region deployment to a resilient, multi-region AWS architecture spanning multiple locations in Europe, North America, and Asia.

How to set up a satellite kitchen in the customer’s location?

Introducing SaaS Anywhere: More SaaS providers are being asked to deploy their applications directly into customers’ cloud environments. But how do you do this without losing control or reverting to the messy 90s era of multiple, inconsistent versions?

Join this session to explore SaaS Anywhere—an architecture pattern that lets you distribute parts of your multi-tenant SaaS solution into customers’ clouds while maintaining centralized control.

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.

Real-world event ingestion challenges include backpressure, noisy neighbors, poisoned messages, connection storms, and scaling bottlenecks. In this session, you will learn proven patterns from handling over 300M events per month in near real-time with MSK, Lambda, and RDS Proxy. We will explore connection pooling, partition-aware processing, async backpressure handling, and recovery strategies.

The evolution of generative AI has brought forth sophisticated multi-agent systems (MAS) that can tackle complex tasks through distributed intelligence and collaborative problem-solving. These systems represent a paradigm shift from traditional single-agent AI implementations to coordinated networks of specialized agents working in concert. As companies continue their digital transformation journeys, understanding the fundamental patterns of multi-agent architectures becomes crucial for designing robust, efficient, and scalable AI solutions. This workshop examines the core patterns in multi-agent systems—Parallel, Sequential, Loop, Router, Aggregator, Network, and Hierarchical—with specific applications in the financial services domain. We’ll explore how these architectures can revolutionize workloads across financial services through enhanced reasoning, planning, and collaborative intelligence. Expected outcomes:

Discover how we transformed a fragmented data landscape into a cohesive analytics powerhouse for airline client. This presentation reveals our journey implementing a data mesh architecture on AWS that harmonized 100 disparate databases, enabling decision-making across operations, customer experience, revenue optimization and other business domains. Learn how AWS services are democratizing data and transforming siloed information into actionable intelligence that propelled our client to new heights in the competitive aviation industry.

In event-driven systems, understanding how data flows through decoupled services is essential—but not always straightforward. Distributed tracing provides the visibility needed to debug issues, monitor performance, and maintain operational resilience at scale.

In this session, we’ll explore how to implement distributed tracing across event-driven architectures on AWS, including scenarios where events originate from external sources like Apache Kafka. You’ll see how AWS CloudWatch and AWS X-Ray can be used together to trace asynchronous workflows involving Lambda, SNS, SQS, and EventBridge—even when they interact with off-AWS systems.

In this session, we will go over advanced techniques to optimize your AWS compute workloads for maximum performance and cost efficiency. Discover how to leverage rightsizing, spot instances, auto-scaling, and AWS’s Graviton processors to reduce costs while boosting performance.