Vadim Tsesko is a platform developer and seasoned distributed-systems engineer with 14 years of professional experience building high-load services, object/blob storages and core infrastructure across Yandex, VK and now 01.tech. He combines deep hands-on expertise in JVM performance and low-level system work—demonstrated by contributions to async-profiler—and practical storage engineering, including an AWS S3‑compatible object store and internal Cassandra core improvements. An educator and mentor who taught NoSQL and highload systems at ITMO and VK’s education program, Vadim pairs production-grade delivery with an academic background in computer science. Based in Tuvalu, he brings uncommon mechanical sympathy to software design, improving memory and off‑heap data structures in projects like one-nio to squeeze predictable performance from Java services.
14 years of coding experience
17 years of employment as a software developer
Postgraduate Course Computer Science, Postgraduate Course Computer Science at Peter the Great St.Petersburg Polytechnic University
Contributions:4 releases, 40 reviews, 25 commits in 3 years 10 months
Contributions summary:Vadim primarily contributed to the `one-nio` Java library, focusing on HTTP client and server functionalities, along with improvements to memory allocation and off-heap data structures. They implemented support for various HTTP methods, including PUT, DELETE, and PATCH. Additionally, they enhanced the HTTP request handling, introduced request body support, and fixed several javadoc and review issues, showcasing a focus on improving the library's features and stability.
Sampling CPU and HEAP profiler for Java featuring AsyncGetCallTrace + perf_events
Role in this project:
Back-end & Performance Engineer
Contributions:6 reviews, 24 commits, 10 PRs in 5 months
Contributions summary:Vadim primarily focused on enhancing the performance and stability of the Java profiler. Their contributions involved implementing critical system calls, refining timer parameters for accurate sampling, and incorporating detailed error handling. They improved code maintainability by using `snprintf()` and optimized the profiling process with the addition of detailed error and event reporting. The user also added features to support agent options for profiling frequency and duration.
cpuperfeventsgarbage-collectionglibc
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