Anirudh Ramanathan is a seasoned Co-Founder and CTO with 13 years of experience building cloud-native and distributed systems from San Francisco. He leads Signadot, creating lightweight Kubernetes-native tooling, and brings deep hands-on experience from contributions to flagship open-source projects like Kubernetes and Apache Spark. His work spans backend engineering, DevOps automation, and API design—most notably improving Kubernetes client HTTP watch behavior and contributing to PodDisruptionBudget validation. He’s been a SIG lead in the Kubernetes ecosystem, a committer on Apache Spark, and has product and engineering experience at Google and startups, giving him a rare blend of platform-scale and startup execution skills. Anirudh also mentors founders through the Founder Institute and leverages YC and Stanford continuing studies to combine technical leadership with business acumen. Beyond product work, he has a track record of improving CI/CD and testing frameworks that quietly raise reliability across large cloud-native projects.
13 years of coding experience
6 years of employment as a software developer
Y Combinator
Business/Commerce General, Business/Commerce General at Stanford Continuing Studies
Master's degree Computer Science, Master's degree Computer Science at Texas A&M University
B. Tech Electronics Engineering, B. Tech Electronics Engineering at Indian Institute of Technology (Banaras Hindu University), Varanasi
[EOL] This is a place for various components in the Kubernetes ecosystem that aren't part of the Kubernetes core.
Role in this project:
Backend Developer & DevOps Engineer
Contributions:68 commits, 79 PRs, 8 pushes in 1 year
Contributions summary:Anirudh contributed significantly to the `contrib` repository, focusing on backend and DevOps related tasks. They implemented a new feature to allow the `submit-queue` to run against other projects and access Google Cloud Storage. Additionally, they modified various mungers (such as `submit-queue` and `flake-manager`) to integrate features like test contexts and GitHub functionality. These changes indicate a focus on extending the core functionalities of the project within the Kubernetes ecosystem.
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:
DevOps Engineer
Contributions:14 PRs, 294 comments in 2 years 6 months
Contributions summary:Anirudh primarily contributed to the Kubernetes integration within the Apache Spark project. They implemented changes related to container image configurations, including updates to the `Dockerfile`, and the use of container images in the Kubernetes environment. Their work extended to documentation and the build process, modifying the build scripts to support Kubernetes-specific functionalities and improve the user experience of building and deploying the Spark application on Kubernetes. The user also made significant code changes which include updating the configuration parameters related to containerization and DNS resolution.
analyticspythondata-processingsqlapache
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.