The True Cost of Kubernetes: People, Time and Productivity

Regardless, the alternative mentioned (Serverless) comes with its own set of problems.

When Google was just Larry and Sergey, they didn't need an additional SRE person to help them set up and maintain their linux servers - they had enough competence to do so themselves. For someone else, renting a managed Windows server with a support agreement would be exactly the right choice.

Likewise, the 1xSRE for managed and 4xSRE for unmanaged K8s isn't substantiated. In my experience, that can be anything from 0 dedicated people and up depending on needs and circumstances. I imagine things like GKE Autopilot (auto-updates) and Fargate for EKS (serverless K8s pods) make it even easier.

It would be more interesting to me to see how their offering compares to other serverless vendors in price and features.

I once had the displeasure of watching an upstart data science team at a boutique portfolio management firm break under the weight of k8s management. The team was great at critical thinking, risk-modeling, and statistical analysis. They knew very little about infrastructure, such as networking fundamentals or CPU/Memory management. This team went from helping our firm rapidly develop a sentiment analysis model that sifts through social media for trading signals to wrestling with kubectl all day. Productivity bombed. Team was disbanded about a year after they started using k8s.

It's a shame the author emphasized and inflated the discrete costs of operating a cluster because that emphasis and exaggeration distracts from the TRUE cost ... opportunity cost. We want our engineering teams doing what they do best, writing code and adding new features. Not bogged down in managing the plumbing/infrastructure. Happy to have that abstracted away.