Artem Kovalenko

At NSPK, I supported a nationwide public-transport payment platform processing millions of transactions daily, helping maintain a 99.9%+ availability target.

I investigated L2 production incidents across logs, metrics, SQL queries, Kubernetes pod state, database data, and service connectivity. I resolved configuration, connection, and missing reference-data issues while coordinating deeper remediation with DBA and L3 teams.

I automated frequent operational requests with Python and SQL, reducing processing time from 10–20 minutes to 1–3 minutes and saving about three hours of manual work per shift. I also built Grafana dashboards used by the duty team to verify transaction flow, monitor service health, and investigate root causes.

I work directly with regional transport operators to isolate partner integration failures and coordinate corrective actions. My academic work includes building a predictive failure-detection system for Kubernetes microservices using streaming telemetry, PyFlink, ML inference, Chaos Mesh, and Locust.