Mark A
About Mark A
Mark A is a DevOps Engineer currently working at Oak Ridge National Laboratory, where he has been employed since 2020. He previously worked at Greenway Health as a Customer Support Engineer and later as a DevOps Engineer, and he holds a B.S. from the University of West Florida.
Work at Oak Ridge National Laboratory
Mark A has been employed at Oak Ridge National Laboratory as a DevOps Engineer since 2020. In this role, he has contributed to the development of monitoring solutions using Prometheus and Grafana to oversee Kubernetes clusters. His responsibilities also include the architectural redesign of legacy Django scientific applications, transitioning them to a containerized microservices CI/CD approach. This redesign allows for multiple deployments per day, enhancing the efficiency of software delivery within the organization.
Previous Experience at Greenway Health
Mark A worked at Greenway Health from 2014 to 2020, initially as a Customer Support Engineer from 2014 to 2017 in the Tampa/St. Petersburg, Florida Area. He then transitioned to the role of DevOps Engineer, where he served from 2017 to 2020. During his tenure, he developed monitoring solutions and assisted in designing a GitLab runner schema managed by Terraform, implementing a blue/green runner deployment strategy to ensure zero downtime.
Education and Expertise
Mark A earned a Bachelor of Science degree from the University of West Florida. His educational background has equipped him with the skills necessary for his roles in DevOps and customer support. He has developed expertise in Kubernetes, Prometheus, Grafana, Terraform, and CI/CD practices, which he applies in his current position and previous roles.
Technical Contributions and Projects
Throughout his career, Mark A has made significant contributions to various technical projects. He has developed and built multiple Kubernetes clusters on-premise using OpenStack cloud for diverse lab-wide and project-wide applications. Additionally, he created a Kubernetes cluster to facilitate the use of Jupyterhub for multiple scientific teams, enhancing collaboration and resource sharing among researchers.