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Comment by throwaway0129u | Hacker News Reader

Not at all, k8s is not designed for very large scale. Unsurprisingly, FAANGS don't use it to manage their own platforms.

Edit: Google's Borg is a very different beast.

Edit: no need to patronize me. I worked on massive scale deployments otherwise I would not be commenting.

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Many large organisations use Kubernetes (Google, Spotify, IBM, etc). Regardless, large scale and very large scale are different. Kubernetes is well suited for controlling fleets of compute resource in the order of 10,000s CPU cores, and terabytes of memory.

The compute overhead to orchestrate these clusters is well worth the simplicity/standardisation/auto-scaling that comes with Kubernetes. Many people have never had to operate VMs in the hundreds or thousands and do not understand the challenges that come with maintaining varied workloads, alongside capacity planning at that scale.

a million nodes running a single application is scale, but a thousand nodes running a thousand applications is also scale, and they are very different beasts.

The FAANGs operate the first kind, k8s is mostly aimed at the second kind scale, so its designed "for scale", for some definitions of scale.

K8s spun off of Google’s Borg operator software specifically designed for high availability at FAANG scale. So essentially K8s is the “community edition.” Go read the Google SRE Book for context.

We use it to serve ruby with 50 million requests per minute just fine. And the best part is the Horizontal Pod Autoscaler which saves our ass during seasonal spikes.

While serverless/lambda are great I do think K8s is the most flexible way to serve rapidly changing containerized workload at scale.

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