Stas Drozdov
About Stas Drozdov
Stas Drozdov is a Senior DevOps Engineer with experience in implementing secure systems and automating deployment processes. He has worked for several companies, including Nexign, Grid Dynamics, and Azul Systems, and holds a Bachelor's degree in Computer and Information Systems Security from Peter the Great St. Petersburg Polytechnic University.
Work at Azul
Currently, Stas Drozdov serves as a Senior DevOps Engineer at Azul Systems. He has held this position since 2020 in Saint Petersburg, St Petersburg City, Russia. In this role, he focuses on enhancing the company's infrastructure and deployment processes, leveraging his extensive experience in DevOps practices.
Previous Experience in DevOps
Before joining Azul Systems, Stas Drozdov worked at Grid Dynamics as a DevOps Engineer from 2019 to 2020. His responsibilities included developing CI/CD pipelines and Chef cookbooks, which contributed to automating deployment processes. He also worked at Nexign as a DevOps Engineer from 2018 to 2019, where he implemented HashiCorp Vault for secure secrets management, improving security practices.
Education and Expertise
Stas Drozdov earned a Bachelor's degree in Computer and Information Systems Security from Peter the Great St.Petersburg Polytechnic University. His studies spanned from 2011 to 2015, providing him with a solid foundation in security principles and practices relevant to his career in DevOps.
Contributions to Infrastructure Automation
During his tenure at Grid Dynamics, Stas Drozdov contributed to projects for The Home Depot, where he automated the creation of Google Cloud Platform VM images using Packer and Chef. He also implemented custom metrics for Google Cloud Platform's Stackdriver, which enhanced the monitoring capabilities of the infrastructure.
Project Involvement
Stas Drozdov has been involved in delivering new versions of the Search application based on Apache Solr Cloud to development and staging environments. This work reflects his commitment to improving application performance and deployment efficiency.