A discussion with representatives of high-risk systems about why security architecture should be incorporated at the design and development stage, rather than added after release into production. We will talk about the risks of delayed implementation of controls, common security illusions, and practical approaches to integrating security practices into the work of product teams.

Have you ever wondered what’s really going on under the hood of distributed systems? Not those “sort of a cluster” setups with 3 nodes, I mean the real deal. The exabyte-scale beasts. In this talk, we’ll peek behind the curtains of modern infrastructure. How do systems that crunch mountains of data actually work? What patterns, principles, and engineering decisions are hiding behind truly scalable architectures? Here’s what we’ll dive into: - What the inner life of a distributed system really looks like - How a distributed app is different from a distributed system - How data storage patterns evolve into modern DBs, queues, and logs - Why “PostgreSQL in the cloud” isn’t really PostgreSQL anymore - Why Northguard might just outshine Kafka - And how new players like NewSQL are changing the game If you’re an architect, tech lead, developer or just curious about why infrastructure scales the way it does - come join! I’ll share insights you might use in your own projects (or at least see them from a new angle). P.S. Yep, there’ll be a bit of magic ✨ and a whole lot of hard truths about the distributed systems powering our world. ?

This presentation will focus on the maintainability quality attribute — how to keep business logic isolated, consolidated, encapsulated, and consistent, as well as how to integrate it with the infrastructure layer, including persistence, messaging etc. We will explore the practical application of the following approaches: - OOD / Rich Domain Model / DDD - Hexagonal layered architecture - CQRS / Persistence / ORM All these aspects will be illustrated through a real-world task example and its implementation approach (code examples will be in .NET).

Imagine you decide to save an old, worn-out ship by replacing its engines with the most advanced ones. But instead of “sailing into a bright future,” it starts sinking even faster. This is a story about how Clean Architecture can become either a life buoy or a stone tied to a project’s neck. The first part is a chronicle of pain: the attempt to bring architectural elegance into the chaos of legacy code, where even successes felt accidental — and why “We’re just doing Clean Architecture” doesn’t always work. The second part is a story of “triumph”: when a mature team and the right approach turned Clean Architecture into the foundation of a scalable, flexible, and truly alive system. Two stories from real practice that show why the same approach can both sink a project and save it.

Launching a Diia AI Against All Odds What does it take to build a conversational AI assistant for millions of citizens? The journey of creating Diia.AI, Ukraine's national digital assistant, started with a simple, promising Proof of Concept. But moving from a controlled demo to a live, production system that handles sensitive data and real-life services was a journey filled with unexpected turbulence. This talk is an honest, behind-the-scenes look at our architectural evolution. We'll dive deep into the real-world challenges we faced: from tackling unpredictable LLM hallucinations and integrating with complex legacy government registries, to designing for national-level security and scale under extreme pressure. This isn't a story of seamless success; it's a story of problems solved, from the absurdly simple to the monumentally complex. Join us to learn the practical lessons that aren't in the textbooks. We will cover how we architected for resilience using a RAG-based approach to fight misinformation, implemented robust Guardrails to ensure safety, and built a scalable, fault-tolerant ecosystem. This session is for any architect, developer, or product leader who wants to understand the battle scars and hard-won insights that come from launching a massive AI platform against all odds.

We wanted to make our service lightning-fast for users anywhere in the world. Edge computing looked like the perfect solution. In practice, we achieved lower latency — but also ran into a whole bunch of unexpected problems. In this talk, Igor will cover: - how they designed edge architecture for global users; - edge providers and infrastructure: what we chose and why; - which optimizations actually made a difference; - architectural trade-offs that shaped our system design; - when edge turned into an “edge-case” and forced us to find unconventional workarounds; - our failures — and the best practices we derived from them.

How to design architecture for a product that already has a successful production environment, but where you still want to launch startup-like initiatives inside it? How do you avoid breaking a stable system, keep user trust, and at the same time give the business room for experiments? - Painful cases of “heavy features” that didn’t stick - How we turned the business desire for “more and faster” into architecture - A successful case of fast features: Secret Boxes in Expirenza - Problems that came after the success of a “temporary” feature - Shifting the development team’s mindset

Nowadays, there is a wide variety of tools for documenting software architecture. However, over time the question arises: is there a tool that not only allows you to represent architectural blocks as interconnected services or components, but also includes comprehensive information about business processes, information systems, and IT infrastructure in a unified view? Such a tool is ArchiMate. ArchiMate is a modeling language for describing, visualizing, and analyzing enterprise architecture, which, together with TOGAF, becomes a powerful instrument in the hands of an architect. During his talk, Alexander will share examples of the Archimate modeling language, show how Archimate can speed up architecture documentation and analysis, and talk about how they use the modeling language at their company.

For many years, our corporate banking platform ran on a large, reliable monolith. Over time, however, technical debt, long release cycles, and module dependencies slowed us down. It was time to rethink. This is the story of an evolution for 150,000 clients: from running monolith and microservices in parallel to Domain-Driven Development with over 20 platform and product teams, from JSP to microfrontends and design systems, from IBM to Open Source. Key Takeaways: Why a stable monolith is no longer enough for modern banking Transition patterns that don’t disrupt business or harm clients Lessons from running monoliths and microservices in parallel Domain-Driven Development at scale: 20+ platform and product teams Microfrontends and design systems for faster delivery When Open Source is the right choice vs. when to buy