Kubernetes Optimization with Kubecost

posted by Cristian Russo on

The benefits and abstractions that Kubernetes brings to IT infrastructure has significantly changed how companies build and deploy applications. The increased managed Kubernetes offerings from both, private and public Cloud Providers, and the ability to run kubernetes on premises has enabled multi cloud as a new way to release software.

But such dynamic infrastructure has increased complexity. It is a challenge to keep costs down while cloud providers keep changing their offering and new services are been added. Mistakes can result on expensive charges and, often, on service degradation or even downtimes. This is where Kubecost comes to help.


Kubecost is an opencore platform built by a team of engineers that worked running containerized workloads for Google. It was created with the goal of assisting teams working with multi-tenant clusters and optimize costs.


It relies on several components:



Kubeview representation of kubecost’s components.



Multi-Cloud Cost Optimization

Keeping costs down across cloud providers

As kubecost has integrations with Kubernetes and Cloud Billing API’s, it provides real-time visibility into how resources are being used across multiple cloud providers. Kubecost will suggest saving actions taking into account how your different applications are using cluster resources and the capabilities of each Cloud Provider.

Cloud providers pricing comparison.


Kubecost savings recommendations




Infrastructure Assessments

Suggestions for improving efficiency and reliability

Kubecost continuously run efficiency, stability and performance assessments that analyzes your configuration and it compares against similar blueprints running on similar environments.

Alerts can help teams to identify cost and infrastructure concerns. Receive dynamic recommendations for optimizing cloud spend and managing capacity to avoid performance degradation and application outages. Track key infrastructure tasks for improving resource efficiency and reliability.



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