Aditya Vajpayee

About Aditya Vajpayee

I am a Senior DevOps Engineer with 4.5+ years of experience in designing and optimizing CI/CD pipelines, infrastructure orchestration, and workflow automation. My expertise lies in on-prem Kubernetes environments, Jenkins, and Apache Airflow, where I focus on scaling DevOps workflows, reducing build times, and enabling seamless automation for engineering teams.At Cohesity, I have been instrumental in migrating CI/CD pipelines from traditional job-based execution to an in-house DAG-based approach, breaking down monolithic builds into scalable, re-entrant task structures. This shift has significantly improved reliability, reduced execution time by ~50%, and provided fine-grained control over task retries, reducing unnecessary full build re-runs. I also work closely with developers to optimize patch builds, eliminating inefficiencies and enhancing developer productivity.Beyond CI/CD, I leverage Kubernetes Pods Executor for test automation, fine-tune performance testing workflows, and integrate observability tools like Prometheus, ELK, and Grafana for proactive monitoring. I am also passionate about AI-driven automation, as seen in my work on DevX Bot, an LLM-powered Slack assistant that has streamlined developer support.With AWS certifications and hands-on experience in cloud and hybrid DevOps setups, I am always eager to explore new automation techniques, optimize engineering workflows, and drive innovation. Let’s connect and discuss how automation can take software delivery to the next level!

Experience

1. Devops Engineer

   Cohesity

   Sep 2022 — Present · IN

   Led the migration of CI/CD workflows from standalone Jenkins pipelines to an in-house DAG-based approach, improving execution efficiency and reducing build times by ~50%: Implemented patch builds to avoid unnecessary full builds, optimizing resource utilization and enhancing developer productivity. & : Utilized Kubernetes Pods Executor for test automation, improving infrastructure efficiency and parallel execution of test jobs: Spearheading the migration of select build workflows to Apache Airflow, enhancing reliability, scalability, and observability in the build process. & : Integrated Prometheus, ELK Stack, and Grafana to improve build and test pipeline observability: Automated key infrastructure provisioning tasks, reducing manual intervention and improving operational efficiency: Successfully transformed CI/CD pipelines with DAG-based execution, reducing build times by ~50%, increasing parallelization, and improving task-level retries for better pipeline reliability.

Education

• Savitribai Phule Pune University

  Bachelor of Engineering - BE

  2016 — 2020