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. ?

Design patterns like Event Sourcing and Event Streaming have long become standards for building real-time analytics systems. However, when the system load becomes nonlinear with fast and often unpredictable spikes, it's crucial to respond quickly in order not to lose real-time operating itself. In this talk, I’ll share my experience implementing and using a tool like Temporal.io. We'll explore the evolution of our system for maintaining real-time report generation and discuss how we use Temporal both for short-lived pipelines and long-running background tasks.

What can go wrong if you allow each service to access the database directly? In a startup, this seems like a quick and easy solution, but as the system scales, problems appear that no one could have guessed. In my talk, I'll share Solidgate's experience in transforming its architecture: from the chaos of direct connections to a service-based data access model. I will talk about the transition stages, bottlenecks, and how isolation affected infrastructure support. I will honestly show what worked and what didn't. In short, we will analyze the controversy of this talk.

Taking a system from 66 million to over 25 billion records is not for the faint of heart—especially when the system in question is financial, where precision is non-negotiable and data latency isn’t an option. In this talk, I’ll walk through the real-world journey of scaling such a system while staying sane and keeping the numbers right. You’ll get a look at how to juggle the need for ultra-high accuracy and low-latency performance, streamline your app logic, and sidestep the usual traps that come with database scaling. This session isn’t about deep-diving into internals—it’s about sharing pragmatic strategies that help you scale without drowning in complexity. Ideal for engineers and system architects eager to tackle serious scale challenges with clarity and confidence.</p> <h4>Abstract

We will explore how e-commerce projects prepare for the busiest time of the year, which key aspects to focus on, and what to expect. We’ll share our experience in setting up auto-scaling, load balancing, and discuss the loads that Silpo handles, as well as the solutions that help us navigate this season without failures.

Today, Redis is the de facto standard for caching in application services. It’s incredibly fast and easy to use, giving it a significant advantage in the market. However, as system complexity grows, Redis has several limitations that affect the reliability and availability of your system, especially under high load. In 2025, we are gradually moving away from Redis and rethinking the caching approach as a whole. In this talk, I will share my perspective on the problem and possible solutions. We will explore the challenges associated with Redis and look at alternative solutions for building more resilient and scalable systems.