Ivan Shapovalov
Site Reliability Engineer at Diabolocom
Paris, Ile-de-France
Summary
👤
Senior🎓
Top SchoolIvan Shapovalov is a Linux-focused Site Reliability Engineer with 14 years of experience building and operating systems-level software and production infrastructure from Paris. He has a deep kernel and tooling pedigree—contributing Linux memory subsystem metrics to htop, system-level fixes to systemd, and power and performance work in Powertop—alongside hands-on DevOps roles at startups and telco-scale teams. Ivan blends C/C++ and Python expertise with test automation, CI reliability and performance tuning (notably improving Synapse stability and Tempesta test frameworks), enabling robust, observable services. His background in computational mathematics from MIPT informs a methodical approach to debugging complex interactions between userspace and kernel subsystems. Colleagues describe him as an operator who still enjoys digging into kernel trees and build systems to make infrastructure measurably better.
14 years of coding experience
5 years of employment as a software developer
Computational and Applied Mathematics, Computational and Applied Mathematics at Moscow Institute of Physics and Technology (State University) (MIPT)
Stackoverflow
2,520reputation
163kreached
15answers
25questions
Github Skills (61)
unit-testing10
opencl10
c-language10
system-programming10
python10
init10
matrix-multiplication10
memory-management10
machine-learning10
test-framework10
linux10
cmake10
blas10
c1110
functional-testing10
Programming languages (25)
Github contributions (5)
tempesta-tech/tempesta
Jul 2017 - Aug 2017
All-in-one solution for high performance web content delivery and advanced protection against DDoS and web attacks
Role in this project:
QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:82 commits, 4 PRs, 34 pushes in 1 month
Contributions summary:Ivan's commits primarily focus on enhancing the functional testing framework for the `tempesta-tech/tempesta` repository, a high-performance web content delivery solution. They implemented features to run tests selectively, improved error messages, and addressed issues related to SSH connections and timeouts. The contributions also include improvements to test reliability, such as fixing issues with Nginx and session handling, and included changes to the test framework itself.
content-deliverylinux-kernelhttp-acceleratortlsweb-application-firewall
BVLC/caffe
Jul 2016 - Aug 2016
Caffe: a fast open framework for deep learning.
Role in this project:Backend Developer
Backend DeveloperContributions:36 commits, 2 PRs, 3 comments in 1 month
Contributions summary:Ivan primarily contributed to the build system and dependency management within the Caffe deep learning framework. They fixed linking issues, improved the handling of include directories for various dependencies such as HDF5 and Boost, and refactored the dependency detection process. These changes streamline the build process and improve the overall portability and usability of the Caffe framework, crucial for developers and researchers in machine learning.
pytorchvisiondeep-learningmachine-learningcaffe
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