This talk is dedicated to the practical experience of transitioning from the classic Istio architecture with sidecar containers to a new model - Istio Ambient Mesh. We will tell how scaling a microservice infrastructure on Kubernetes led to increased resource costs, complicated CI/CD, and delays in launching services. The search for solutions led us to implement Ambient Mesh, an architecture without sidecar containers that greatly simplifies mesh integration and reduces infrastructure costs. The presentation will detail the technical aspects of the migration: how we prepared for the transition, what challenges we faced during the implementation process, and how we managed to overcome them in cooperation with the Istio community. We will share the results, analytics, real before/after metrics, and give practical advice to teams planning to implement Ambient Mesh in production.

Let's talk about our history. How we started the project with a small vector database of less than 2 million records. Later, we received a request for +100 million records, then another +100... And so gradually we reached almost 1 billion. Standard tools were quickly running out of steam - we were running into performance, index size, and very limited resources. After a long series of trials and errors, we built our own low-cost cluster, which today stably processes thousands of queries to more than 1B vectors.

In this talk, I'll discuss how Reacts' often overlooked concurrent features like startTransition, useDeterredValue and Suspense can transform an application's performance and responsiveness. Participants will learn practical techniques to prioritise critical updates, gracefully handle loading states, and create fluid user experiences even with complex data interactions.

In this talk, we will explore the micro frontend architecture based on the real example of the big product, uncovering how dozens of teams coexist, work, and deploy features independently every day. Moreover, I will talk about the bottlenecks of React hydration, how it affects users, and how to apply the progressive hydration pattern to improve web performance.

Software performance engineering (SPE) aims to build predictable performance into systems by specifying and analyzing quantitative behavior from the beginning of a system to its deployment and evolution. We should also apply this thinking to the data portions of our applications and systems. Performing data operations with Entity Framework Core 8 can seem simple, but there is a hidden part of this framework that can allow developers to unlock the performance users expect. We will lean into this, explore those EF Core features, and leave the talk as better developers.

In recent years, I have gained most of my knowledge through reverse engineering, how I did it and what I learned during this period, I decided to share. All this concerns graphic programming, performance, best practices in the frontend.

In this talk, we’ll explore a number of popular techniques for populating and delivering content into web views for our users. We’ll compare different rendering models to help us understand the benefits and limitations of each one, and we’ll build examples with different tools to show how our choices influence the developer experience, user experience, and environmental impact of our projects.