I am a DevOps Engineer with 8 years of experience in end-to-end platform engineering, architecture design, and full automation of CI/CD pipelines. I am proficient in orchestrating complex deployments and managing high-load applications with more than 150 million users, such as digital signature and government services for all citizens in the country. I ensure airtight security across both cloud and on-premises environments. I have been recognized for executing seamless migrations, optimizing infrastructure, and driving operational excellence in banking card issuance for Visa and Mastercard companies, which collectively planned to issue 750 million cards during my tenure. I am always prepared to navigate and resolve the most challenging technical obstacles.
Automation of Data processing and Management.
Done AI/ML application migration as a MLOps from DO to Hetzner. While fixing Github Actions pipeline for dev and production, Applied MLFlow, ArgoWf, JupyterHub. Done Kotlin application migration and deployment to yandex cloud with Kubernetes, Database, Gitlab CI.
Spearheaded the migration of on-premise legacy monolithic applications to a microservices architecture by decoupling services and enabling independent scaling, which significantly improved scalability and reduced deployment times. Optimized CI/CD pipelines for global Visa and MasterCard projects, reducing deployment time from 6 hours to just 20 minutes. Developed and assembled optimized Docker images, enhancing containerization and deployment processes across multiple environments by reducing image size 3 times.
Successfully deployed and managed high-load infrastructure services, ensuring 99.9% uptime for key services like Hadoop, Spark, ClickHouse, Zookeeper, Kafka, AeroSpike, PostgreSQL, Redis, and RabbitMQ within a Kubernetes cluster. Automated the service-to-service certificate issuing process using CI/CD pipelines, reducing error rates and issuance time by a factor of six. Deployed the ClickHouse cluster and provided support for ClickHouse-based applications, diagnosing and resolving performance issues in production. Debugged and optimized SQL queries, resulting in a 90% reduction in CPU load for on-premises services. Tuned Nginx filters to reduce incoming requests by 80% for private cloud services, significantly improving performance and reducing server load.
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