{"id":38112,"date":"2019-10-31T22:21:44","date_gmt":"2019-10-31T19:21:44","guid":{"rendered":"https:\/\/prohoster.info\/blog\/obzor-kubecost-dlya-ekonomii-sredstv-na-kubernetes-v-oblakah\/"},"modified":"2019-10-31T22:21:44","modified_gmt":"2019-10-31T19:21:44","slug":"obzor-kubecost-dlya-ekonomii-sredstv-na-kubernetes-v-oblakah","status":"publish","type":"post","link":"https:\/\/prohoster.info\/en\/blog\/administrirovanie\/obzor-kubecost-dlya-ekonomii-sredstv-na-kubernetes-v-oblakah","title":{"rendered":"Kubecost Review for Kubernetes Cost Savings in the Cloud","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

\"Kubecost
\n
\nCurrently, more and more companies are migrating their infrastructure from physical servers and private virtual machines to the cloud. This decision is easy to explain: there is no need to worry about hardware, the cluster can be configured in many different ways... and most importantly, existing technologies (like Kubernetes) allow for easy scaling of computing power based on load.<\/p>\n

The financial aspect is always important. The tool discussed in this article aims to help reduce budgets when using cloud infrastructure with Kubernetes.<\/a><\/noindex><\/p>\n

Introduction<\/h2>\n

\nKubecost<\/a><\/noindex> \u2014 a California startup founded by former Google employees, creating a solution for calculating infrastructure costs in cloud services (within a Kubernetes cluster + shared resources), identifying bottlenecks in cluster configurations, and sending corresponding notifications to Slack.<\/p>\n

We have clients using Kubernetes in both familiar clouds like AWS and GCP, as well as in the less common Azure for the Linux community \u2014 in general, on all platforms supported by Kubecost. For some of them, we track costs for in-cluster services independently (using a methodology similar to that used by Kubecost) and also monitor infrastructure expenses to optimize them. Therefore, it makes sense that we were interested in the possibility of automating such tasks.<\/p>\n

The source code of the main Kubecost module is open under the Open Source license (Apache License 2.0). It can be used freely, and the available features should be sufficient for small projects. However, business is business: the rest of the product is closed and can be accessed through paid subscriptions<\/a><\/noindex>, which also include commercial support. Additionally, the authors offer a free license for small clusters (1 cluster with up to 10 nodes \u2014 at the time of writing, this limit has expanded to 20 nodes) or a trial period with full capabilities for 1 month.<\/p>\n

How Everything Works<\/h2>\n

\nSo, the main part of Kubecost is an application cost-model<\/b><\/a><\/noindex>, written in Go. The Helm chart describing the entire system is called cost-analyzer<\/b><\/a><\/noindex> and essentially is an assembly of cost-model with Prometheus, Grafana, and several dashboards.<\/p>\n

Generally speaking, the cost model has its own web interface that displays graphs and detailed statistics on expenses in tabular form, as well as, of course, tips for optimizing costs. The dashboards presented in Grafana are an earlier stage of Kubecost\u2019s development and contain largely the same data as the cost model, supplemented by familiar statistics on CPU\/memory\/network\/storage space usage in the cluster and its components.<\/p>\n

How does Kubecost work?<\/p>\n