Managing System Workloads on Google Kubernetes Engine (GKE)

Managing System Workloads on Google Kubernetes Engine (GKE)

In this tutorial, wwe wwill learn how to managing system workloads on Google Kubernetes Engine (GKE). Operating GKE at scale is a bit harder than you may think.

First let us consider what Google Kubernetes Engine (GKE) is:

Secured and fully managed Kubernetes service with revolutionary autopilot mode of operation.

— Google Kubernetes Engine

With this in mind, it sounds like an oxymoron for us to have to manage system workloads on GKE (a fully-managed Kubernetes service).

Shared Responsibility Model

We dive a bit deeper into what Google means by fully managed Kubernetes.

This article is focused on GKE Standard, i.e., not the newer more managed GKE Autopilot. At the same time, it is not clear that Autopilot absolves us from having to manage system workloads; their service level agreement (SLA) does not specifically call them out.

Here we see that Google uses a shared responsibility model when supporting GKE.

kubernetes

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