Kubernetes Cost Management with the New OpenCost Plugin for Headlamp
OpenCost, an open-source project, offers real-time cost monitoring for Kubernetes. Its new plugin for Headlamp integrates cost visibility into the UI, enhancing resource management and customization options for users.
Read original articleOpenCost, a prominent open-source project under the Cloud Native Computing Foundation (CNCF), provides real-time cost monitoring for Kubernetes environments, allowing users to track expenses associated with cloud-native applications. The newly developed OpenCost plugin for Headlamp enhances this functionality by integrating cost visibility directly into the Headlamp user interface. This integration helps developers manage their Kubernetes resources more effectively by providing insights into the costs of individual workloads, namespaces, and labels. To utilize the OpenCost plugin, users must first install OpenCost alongside Prometheus metrics export. The installation process can be completed through the Headlamp App Catalog or via command line. Once installed, OpenCost data is displayed in various parts of the Headlamp UI, including resource tables and detailed views, which now feature cost information and historical cost charts. Users can customize how this data is presented, including currency symbols and time spans. The developers of Headlamp encourage user feedback and contributions to enhance the plugin's functionality and overall user experience.
- OpenCost provides real-time cost monitoring for Kubernetes applications.
- The OpenCost plugin integrates cost visibility into the Headlamp UI.
- Users must install OpenCost with Prometheus for the plugin to function.
- Cost data is displayed in resource tables and detailed views within Headlamp.
- Customization options are available for displaying cost data.
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Lets say node has 8 CPUs and 32 GB RAM (1:4 ratio). If every pod uses same ratio for its CPU:MEM then math is simple: node cost is split across all pods proportional to their resource allocation.
How to make fair calculation if pod resource ratio is different? In extreme it is still simple - lets say there is a pod with 8 CPU and 2 GB RAM, because no pods can fit into node whole node cost is allocated to that pod.
What if running pod is 6 CPU and 16 GB RAM and another pod with 2 CPU and 16 GB RAM is squeezed in. How to allocate node cost to each? It can't be just node cost / # of pods, because intiutively beefier pods should recive larger share of node cost as they prevent more smaller pods to fit in, but how exactly to calculate it? "weight" of pod on CPU dimenstion is different than on MEM dimension.
Does the Athena does the actual processing/computation of costs ? What is the usual cost for running Athena ?
It also seems strange that I have to put the IAM keys into secrets instead of using IAM role for service account for configuring it.
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