Elson Rodriguez
Platform Engineer
Portland, Oregon Metropolitan Area United States
Summary
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RockstarElson Rodriguez is a platform engineer with two decades of hands-on experience building and automating cloud-native infrastructure, from early Puppet/Cobbler provisioning to modern Kubernetes and Crossplane platforms. He has repeatedly reduced operational toil and outages—introducing package management at Time Warner, converting TSYS microservices to fully automated deployments, and prototyping hybrid Kubernetes deployments at Rentrak. At Intel and SADA he led ML and MLOps migrations, contributed the first MNIST example to Kubeflow, and helped adapt Kubeflow and Ceph for cleaner cloud integration. Comfortable across the stack, he pairs pragmatic tooling and automation with client-facing delivery—helping secure major deals and grow SADA into a GCP premier partner. Based in Portland, he continues to contribute to influential open source projects (Minio, TensorFlow, Kubernetes) while architecting resilient, repeatable platforms for production ML and data workloads.
12 years of coding experience
10 years of employment as a software developer
Stackoverflow
91reputation
8kreached
1answer
1question
Github Skills (22)
kubernetes10
docker10
dockers10
automation10
mlops10
amazon-s310
jsonnet10
kubernetes-pods10
aws-s310
ceph10
automations10
s3-bucket10
bash9
cloud-infrastructure9
yaml9
Programming languages (12)
Github contributions (5)
ceph/ceph-container
May 2016 - Nov 2016
Docker files and images to run Ceph in containers
Role in this project:
DevOps Engineer
DevOps EngineerContributions:10 commits, 1 PR, 27 comments in 5 months
Contributions summary:Elson primarily focused on enhancing the Ceph containerization efforts by modifying and creating Kubernetes deployment configurations. They updated scripts for secret generation, cluster creation and deletion. Furthermore, the user migrated from using Release Candidates (RCs) to Deployments for managing the Ceph cluster components. These changes streamlined deployment, configuration, and management.
containersdocker-imagedocker-filesdockerceph
kubeflow/kubeflow
Jan 2018 - Mar 2018
Machine Learning Toolkit for Kubernetes
Role in this project:DevOps Engineer & MLOps Engineer
DevOps Engineer & MLOps EngineerContributions:7 commits, 15 PRs, 50 comments in 1 month
Contributions summary:Elson primarily focused on improving the deployment and configuration aspects of the Kubeflow project. Their contributions involved modifying service types for JupyterHub, refactoring TF Serving components, and adding support for S3-based model serving. They also addressed issues with CRD deployments and updated configurations to align with newer versions of related tools. This work directly impacted the usability, flexibility, and cloud integration of Kubeflow deployments.
pythondata-sciencenotebookmachine-learningmlops
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