Aleksandr Serbul
where else to find them
no profile links on file
what they talk about
all 8 in the filters
where they keep going back
- Backend Conf (РИТ++)2 editions2018–2019
- HighLoad++2 editions2015–2017
all 5 in the filters
on a stage with
never shared a talk
who talks about the same things
- Alice Ryhl6 talks
- Luca Palmieri7 talks
- Tarun Pothulapati7 talks
- Francesco Ciulla13 talks
- Neville Dipale2 talks
- Sabree Blackmon3 talks
| title | conference | date |
|---|---|---|
| Thousands of Async Tasks per Second in the Cloud on Rust/Axum/Tokio | Saint HighLoad++ 2025 | 2025-06-23 |
Describes building Rust command-line utilities using Axum and Tokio to perform massive asynchronous, non-blocking operations against AWS-compatible S3 clouds… | ||
| The RUST Language for High‑Load Network Services — Quick Start | Highload fwdays'20 | 2020-10-13 |
A presentation traces the evolution of a high-load push-notification cluster from Unix/bash and PHP scripts to an asynchronous, non-blocking, multithreaded… | ||
| Voice Control in Cloud Web Projects | Backend Conf 2019 (РИТ++) | 2019-05-27 |
Describes integrating voice-assistant devices and platforms (Yandex.Station, Yandex.Alice, Google Home/Google Assistant, Irbis A, DEXP Smartbox) with a… | ||
| Designing, developing and operating a high‑load system | Backend Conf 2018 | 2018-05-28 |
Covers design, development and operation of a high-load backend system using lambda-style architectures and AWS serverless (Amazon Lambda). Discusses practical… | ||
| Machine Learning in E‑commerce | HighLoad++ 2017 | 2017-11-07 |
Covers building and operating large-scale predictive analytics for an e-commerce/CRM product (Bitrix24): designing, training and tuning Spark MLlib models in… | ||
| Machine Learning in E‑commerce | РИТ++ 2017 | 2017-06-05 |
Describes practical machine-learning techniques used in e-commerce for customer acquisition and retention, including product-catalog clustering, customer… | ||
| Big Data — How to Mine Gold from Data | HighLoad++ 2015 | 2015-11-02 |
Overview of common big data technologies and algorithms used to extract business-critical information from large datasets, with concrete discussion of… | ||
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