Experience

Performance Analyst – EPAM Systems – from August 2018 to December 2020

  • Worked on 9 projects in total with different architecture solutions and performance testing and monitoring tool-set based on project needs;
  • 5 projects were started from scratch. All performance testing processes were setup and built step-by-step. Defining performance strategies and plans in short and long terms in accordance with business needs;
  • Experienced with monolith e-commerce systems, construction of complex performance scenarios based on real production statistics. Solution of production performance issues, identification of bottleneck on testing stage;
  • Experienced with serverless architecture testing based on AWS clouds. Support of migrations from old monolith architecture to the cloud;
  • Performance monitoring tool-set setup and certification in customers intranet. Development of production client-side performance monitoring solution;
  • Testing of server-side rendering engine from the very beginning with performance improvements suggestions, profiling, solution architecture edits. Performance budgeting of applications components;
  • Work in multicultural team and communication with 5+ large streams on project.

Technologies: AWS stack, MySQL, SAP Hybris, JBoss AS, Apache Kafka, Oracle DB, Java, Groovy, Node.js, Linux, Git.

Tools: JMeter, HP LoadRunner, Gatling, Wolfram Mathematica, Ansible, Jenkins, InfluxDB, Selenium, Sitespeed, Lighthouse, Webpagetest, Prometheus, ELK stack, Fiddler, Grafana, Dynatrace, NewRelic, Google Analytics, CloudWatch, JProfiler, JIRA.

Senior Performance Analyst – EPAM Systems – from December 2020 till now

  • Internal activities – mentoring, tech interviews of newcomers, support of new commerce on their first projects;
  • Playing a role of Engineering team lead for performance team. Activities planning, prioritization, estimations;
  • Preparation for new performance testing streams: requirements gathering from product owners and stakeholders, prediction of production load, test strategies and approach definition, scripting, testing, performance backlog creation, reporting, “go”/”no go“ decision making;
  • Production load monitoring and identification of problems. Reproducing the issues on low environments;
  • Creation of self-written tool for automated performance testing lifecycle (prod logs analysis, script update based on gathered data, distributed testing, metrics gathering, dashboard creation, automated reporter to Confluence);
  • Testing of events on serverless AWS architecture, self-written logs analyzer based on Kafka and AWS SDK.

Technologies: AWS, YC, Couchbase, PostgreSQL, Oracle DB, Oracle WebLogic, OHS, F5, Hybris, Java, Node.js, Linux, Git.

Tools: JMeter, Gatling, Docker, Grafana, InfluxDB, Jenkins, GitLab, Ansible, Dynatrace, Jaeger, Prometheus, ELK, JProfiler, JIRA.

Code example


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Projects

Q-balls without potential
Q-balls in Friedberg-Lee-Sirlin with vanishing potential. Technologies: Wolfram, C++, Origin, Latex.
Q-balls in gFLS
Q-balls in gauged Friedberg-Lee-Sirlin. Technologies: Wolfram, C++, Origin, Latex.
Q-chains in gFLS
Q-chains in gauged Friedberg-Lee-Sirlin. Technologies: Wolfram, C++, Origin, Latex.