Niket Ranjan
I am a passionate DevOps Engineer currently working at Red Hat as an Associate Software Maintenance Engineer. With two years of experience, I specialize in Linux kernel maintenance, cloud infrastructure, and automation. My expertise includes hybrid cloud management (AWS, Terraform), containerization (Docker, Kubernetes, Podman), CI/CD pipelines (Jenkins, GitHub Actions, GitLab, ArgoCD), and monitoring tools (Prometheus, Grafana, ELK, Loki).
At Red Hat, I focus on maintaining and optimizing Red Hat Enterprise Linux (RHEL) by backporting critical CVE patches, managing kernel builds, troubleshooting complex kernel issues, and optimizing CI/CD workflows. My previous experience includes working on performance engineering and automating infrastructure using Ansible and AWS.
Red Hat
Job title –Associate Software Maintenance Engineer
Session
Deploying AI/ML models in production involves more than just training—it's about building scalable, secure, and automated pipelines. This talk focuses on how AIOps can enable production-grade deployment of ML workflows using cloud-native tools. We’ll walk through an end-to-end architecture built on GitLab CI/CD, Terraform, GKE, and FastAPI, showcasing how to automate infrastructure, containerize applications, and monitor deployed models.
As a use case, we’ll demonstrate deploying a self-hosted LLM for intelligent Q&A over internal documents using RAG. The focus will be on infrastructure, automation, and best practices for taking any AI workload—from concept to production.