Scaling ML Deployment with Ray Serve on Kubernetes: A Practical Guide for DevOps Teams
Why Ray Serve? And Why Now? Machine learning (ML) workloads are maturing fast. What used to be experimental notebooks are now powering real-time user experiences, from recommendations to fraud detection. And with that shift comes pressure — pressure to deploy faster, scale reliably, and recover smoothly. That’s where Ray Serve steps in. Built on top […]
From Kubernetes to Crustaceans: Applying DevOps Principles to Sustainable Aquaculture
Bridging the Worlds of Tech and Aquaculture As a senior platform engineer, I’ve spent over a decade working with cloud-native infrastructure. My daily tools included Kubernetes, GitOps, CI/CD pipelines, and enough YAML to fill a novel. But lately, I’ve found myself applying those same tools — or at least the thinking behind them — to […]