Viewing Kubernetes Resources
You can view right-sizing information about Kubernetes resources on the Cost Saving Opportunities (CSO) page. Cloud Cost Management (CCM) supports AWS Elastic Kubernetes Service (EKS) and Azure Kubernetes Service (AKS).
From the Recommendation Details table you can see the current type and cost of your Kubernetes resources, as well as the proposed changes and potential savings. The drop-down for each row in the table provides additional details, including the name of the cluster and namespace that each container belongs to.
For Amazon EKS, CCM provides recommendations for both EC2 and Fargate instances, based on the constraints you set in the associated policy.
When viewing recommendations for Kubernetes, the Current Type and Proposed Type columns display recommended values, based on the Kubernetes configurations for CPU and memory. CPU and memory values are set in the configuration file, as shown in the Kubernetes documentation.
The following image show examples of Kubernetes recommended values, displayed as CPU-memory, such as 1000mCPU-128MiB. CPU values are in milli-CPUs.
Containers on which a Prometheus service is deployed for Kubernetes are not right-sized, and are therefore not included in reports.
Tip
When running Kubernetes and hosting your own instances on your cloud provider, no cost data is associated with the container recommendations, and only the limit sizes display. In this circumstance, cost data is displayed for the instance rather than the container. Cost values in the Container column will display as dashes.
When right-sizing in this circumstance, we recommend that you size your containers first, then size the underlying EC2s or VMs.
From the Right-Sizing tab, you can do the following:
View recommendations for optimizing Kubernetes containers based on performance, cost, and risk.
See an overview of potential savings for Kubernetes entities.
Edit the policy for the Kubernetes resource and configure policy constraints based on required CPU and memory utilization, and adjust the data aggregation method.
View details of recommendations to see how various performance indicators would be affected by implementing the recommendations.
Configure reports for emailing.
Implement change requests.
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