📊 Kubernetes Metrics Overview: Pod, Container, and Node Statuses
🧭 Overview
GermainUX collects Kubernetes KPIs to monitor the health, availability, resource utilization, and stability of clusters, nodes, pods, and containers.
These KPIs can be used for real-time monitoring, dashboards, SLA tracking, alerting, analysis, and automation.
They also provide supporting technology evidence when investigating user-experience, application, or business-process issues in the Analysis Dashboard.
📋 Kubernetes KPIs
|
KPI |
Name |
Example |
Notes |
|---|---|---|---|
|
Kubernetes:PodStatus |
Germain UX DS name : metadata.name of the POD |
d710a3b4:lyjvms-sts-3 |
1 metric per POD |
|
Kubernetes:ContainerStatus |
Germain UX DS name : metadata.name of the POD : Container Name |
d710a3b4:lyjvms-sts-2:apache-pocjvms |
1 metric per Container |
|
Kubernetes:ContainerRestartCount |
Germain UX DS name |
d710a3b4 |
1 metric per Cluster |
|
Kubernetes:Node CPU Usage |
metadata.name of the Node |
10.230.92.57 |
1 metric per Node |
|
Kubernetes:Node Memory Usage |
metadata.name of the Node |
10.230.92.57 |
1 metric per Node |
|
Kubernetes:Container CPU Usage |
metadata.name of the container |
- |
1 metric per container |
|
Kubernetes:Container Memory Usage |
metadata.name of the container |
- |
1 metric per container |
🌱 Pod Status
Kubernetes monitors the status of each Kubernetes Pod.
One metric is generated for each Pod, allowing GermainUX to identify Pods that are not operating in their expected state.
The Data Source name identifies both the GermainUX Kubernetes Data Source and the Pod:
<GermainUX Data Source>:<Pod Name>
Example:
d710a3b4:lyjvms-sts-3
Use this KPI to:
|
Use |
|---|
|
Monitor Pod health |
|
Detect unavailable or unhealthy Pods |
|
Identify affected applications or services |
|
Track Pod status over time |
|
Trigger alerts or automated actions when configured conditions are detected |
📦 Container Status
Kubernetes monitors the status of individual containers running within Kubernetes Pods.
One metric is generated for each Container.
The Data Source name identifies the Kubernetes Data Source, Pod, and Container:
<GermainUX Data Source>:<Pod Name>:<Container Name>
Example:
d710a3b4:lyjvms-sts-2:apache-pocjvms
Use this KPI to identify containers that are unavailable or not operating in their expected state.
🔁 Container Restart Count
Kubernetes monitors container restarts within the Kubernetes cluster.
The Data Source name identifies the monitored Kubernetes cluster.
Example:
d710a3b4
Use restart count to identify container instability and investigate whether repeated restarts are associated with application availability, errors, or performance issues.
🖥️ Node CPU Usage
Kubernetes CPU Usage monitors CPU utilization for each Kubernetes Node.
One metric is generated for each Node.
The Node is identified using its metadata.name.
Example:
10.230.92.57
Use this KPI to identify sustained or abnormal CPU utilization that may affect Pods, Containers, services, or applications running on the Node.
💾 Node Memory Usage
Kubernetes Memory Usage monitors memory utilization for each Kubernetes Node.
One metric is generated for each Node and identified using its metadata.name.
Use this KPI to identify memory pressure or abnormal memory utilization that may affect workloads running on the Node.
🚀 Container CPU Usage
Kubernetes CPU Usage monitors CPU utilization at the individual Container level.
One metric is generated for each Container and identified using the Container's metadata.name.
Use this KPI to:
|
Use |
|---|
|
Identify CPU-intensive Containers |
|
Detect abnormal CPU utilization |
|
Compare resource consumption across Containers |
|
Investigate application or service performance issues |
🧠 Container Memory Usage
Kubernetes Memory Usage monitors memory utilization at the individual Container level.
One metric is generated for each Container and identified using the Container's metadata.name.
Use this KPI to:
|
Use |
|---|
|
Identify memory-intensive Containers |
|
Detect abnormal memory utilization |
|
Identify potential resource constraints |
|
Compare memory consumption across Containers |
|
Investigate application or service degradation |
🔍 Analyze Kubernetes Health
Kubernetes KPIs can be monitored in GermainUX dashboards and analyzed alongside application, service, user-experience, and business KPIs.
For example:
Application Performance Degradation
→ Technology Health
→ Kubernetes Node CPU Usage
→ Affected Node
→ Pods & Containers
→ Related KPIs
→ Analysis
→ Likely Root Cause
Or:
Service Failure
→ Kubernetes
→ Affected Container
→ Pod
→ Container Restart Count
→ Related Application Errors
→ Analysis
💓 Technology Health
Kubernetes KPIs can be surfaced in the Technology Health view of the Operational Dashboard to provide real-time visibility into the infrastructure supporting monitored applications.
This can help identify whether an application or user issue is associated with:
|
Area |
|---|
|
Cluster health |
|
Pod availability |
|
Container availability |
|
Container restarts |
|
Node CPU utilization |
|
Node memory utilization |
|
Container CPU utilization |
|
Container memory utilization |
🔔 Alerts & Automation
Kubernetes KPIs can be associated with SLAs, alerts, Rules, and Automation to detect and respond to abnormal conditions.
For example:
Container Status Changes
→ Detect condition
→ Analyze affected application/service
→ Alert appropriate team
→ Create or update ticket
→ Continue monitoring
→ Validate recovery
The available actions depend on the GermainUX configuration and permissions.
📖 Related Documentation
|
Document |
|---|
|
Kubernetes Monitoring |
|
Technology Health Dashboard |
|
KPIs |
|
SLAs |
|
Analysis Dashboard |
|
Root-Cause Analysis |
|
Monitoring |
|
Automation |
📦 Additional Resources
-
Deploy Monitoring or automation for Kubernetes.
-
AI Insights & Recommendations
-
More Analytics Features
-
More Automation Features
ℹ️ Get Help
The Germain Team can help you set this up. Contact GermainUX Support.
Component: Engine
Feature Availability: 2022.3 or later