Estimating the Cost of Kubernetes Deployment on GKE Autopilot

In the world of full-stack application development, the path often leads to the cloud, especially when scalability is a concern. Teams start with local setups and, and soon they transition to containerization, typically via Docker Compose due to its simplicity and well-established presence in the general community. However, the next natural step, deploying on managed Kubernetes like GKE Autopilot, can be cost-intensive. Before making the leap, it’s crucial to estimate the cost of your current setup to avoid overpaying for unused resources. In this post, we’ll explore how to estimate the cost of your Kubernetes deployment on GKE Autopilot. <img alt="" src="https://miro.medium.com/v2/resize:fit:700/1*1Y4R5TEF_TAGXWMYc6hQ3A.png" style="height:308px; width:700px" /> <h1>Understanding GKE Autopilot Billing</h1> GKE Autopilot operates on a unique billing model. It bills you based on the CPU and memory allocations configured for your separate pods, specifically the <code><a href="https://cloud.google.com/kubernetes-engine/docs/concepts/autopilot-resource-requests#resource-limits" rel="noopener ugc nofollow" target="_blank">resources.limits</a></code> parameter. Importantly, it doesn’t consider how much CPU and memory your pods are actually utilizing. Instead, it charges you for what you’ve set as a limit. This means that you could be paying for resources that you’re not fully using. Let’s take a look at an example. <a href="https://levelup.gitconnected.com/estimating-the-cost-of-kubernetes-deployment-on-gke-autopilot-b22d0b922421">Visit Now</a>