A while back, I wrote a blog post on creating a low-cost managed Kubernetes cluster. The solution centers around Google Kubernetes Engines’s (GKE) free zonal cluster and preemptive node pools. This allows for a very low-cost Kubernetes cluster which is useful for learning purposes or for small workloads. The same setup is in use today for me; however, over time, the GKE cluster has by default become bloated. Google have enabled by default logging, monitoring, and other features to the cluster, which is great for production workloads, but if you are looking to cut costs, then many of these features don’t make sense.

OpenCost is an open-source tool designed to help you monitor and understand the cost of your cloud infrastructure. As a project under the Cloud Native Computing Foundation (CNCF), OpenCost offers a transparent and powerful solution for cloud cost management. It provides both a user-friendly interface for visualizing cloud costs and Prometheus metrics, enabling you to query and visualize these costs using Grafana. The popular tool KubeCost is built on top of OpenCost, offering an enhanced feature set and user experience. However, KubeCost is not open-source, and its free plan has limitations on data retention and storage. Given these constraints and a preference for consolidating data visualization within Grafana, I opted to use OpenCost. This blog post will introduce the opencost-mixin - a set of Prometheus rules and Grafana dashboards for OpenCost.

Kubernetes is an open-source system that’s popular amongst developers. It automatically deploys, scales, and manages containerized applications. Yet for those working outside of the traditional startup or corporate setting, Kubernetes can be CPU and memory-intensive, disincentivizing developers from using a strategically beneficial tool. We’ll highlight some of the constraints posed by using Kubernetes and offer a series of low-cost, practically-beneficial solution: Google Kubernetes Engine deployed and managed with Terraform.