Kubernetes view
The Kubernetes view enables you to manage the capacity and efficiency of containerized environments managed by the Kubernetes platform, and presents key capacity metrics and charts for Kubernetes clusters, nodes, namespaces, deployments and pods.
You can use the Kubernetes view to complete tasks such as:
- Understand resource bottlenecks and aggregate residual capacity of Kubernetes clusters as well as individual nodes
- Detect current or imminent resource saturation conditions and days before the resource is saturated for every major Kubernetes resource (For example: cluster, nodes, deployments, pods)
- Assess the level of infrastructure efficiency, by comparing allocated vs actually resources, and identify most wasteful deployments or pods
- Identify application in resource usage patterns and detect resource shortage conditions
- Characterize the footprint of infrastructure resources on a containers image basis
- Understand resource utilization of namespaces, including the level of usage of resource quotas
Resolve issues that are identified for your Kubernetes environment by providing a set of recommended actions
Certified data sources
The certified data sources for the views are the following:
- Kubernetes (K8S) Heapster
- Kubernetes (K8S) Prometheus
You must configure and run one of these ETL modules to import data into the view.
Data Visibility
The Kubernetes view provides summarized, high-level capacity KPIs designed for capacity management. The following common conventions around naming and metrics aggregation are valid for all data presented in the view:
- Standard table column names: Metric name [unit of measurement]. For example, Memory [GB].
- Unit of measurement is not used when implicitly evident.
- The metric value is the aggregation of the last 30 days.
- The metric value is computed as follows: for each day, the daily peak is considered (at hourly resolution). Then, the mean value of the daily peak over the last 30 days is displayed.
This is only valid for summary metrics presented in tables and overall page. The charts presented in the details pages follow regular over time metrics semantics, whose time frame and time resolution available as filters in the top of the page.
Thresholds, Status & Bottleneck
The Resource column is defined as: "Resource taken into account: status"; the defined resources are:
- CPU: all the metrics related to the CPU (For example, CPU utilization or CPU Request over CPU Number)
- MEM: all the metrics related to the memory (For example, memory utilization or memory Request over memory capacity)
- SAT: days before saturation of the resource
- POD: percentage of pods required over pod creation limit
The following table shows the thresholds used in the view.
Resource | Cluster | Node | Namespace | Deployment | Pod |
|---|---|---|---|---|---|
CPU: OK | < 80% | < 80% | < 80% | < 80% | < 80% |
CPU: ALERT | > 90% | > 90% | > 90% | > 90% | > 90% |
MEM: OK | < 75% | < 75% | < 75% | < 75% | < 75% |
MEM: ALERT | > 85% | > 85% | > 85% | > 85% | > 85% |
SAT: OK | > 90 days | > 90 days | > 90 days | > 90 days | > 90 days |
SAT: ALERT | < 30 days | < 30 days | < 30 days | < 30 days | < 30 days |
POD: OK | < 70% | < 70% | < 70% | < 70% | < 70% |
POD: ALERT | > 80% | > 80% | > 80% | > 80% | > 80% |
Materializer Task
The Kubernetes view takes advantage of BMC Helix Continuous Optimization materialized data marts in order to enable faster page loading times during user browsing, by pre-computing the underlying data. To achieve this result, a proper DataMartMaterializer task is deployed as part of the view installation process. By default, the task is scheduled to run every day at midnight. Please modify the scheduling parameters to fit the environment needs, such as:
- Data loading scheduling and warehouse latency
- Multiple refresh in the same day
- Kubernetes View user need
The Kubernetes View materializer can be found under System Tasks.
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