Kubernetes Resources
Track and analyze Kubernetes resource changes over time
Overview
Metoro provides comprehensive tracking of Kubernetes resources, capturing every update to give you a complete history of your cluster’s state. This “time-travel” capability allows you to view your cluster’s state at any point in time, not just its current state.
Resource Tracking
The cluster agent watches and exports the following Kubernetes resources:
- Pods
- Deployments
- StatefulSets
- ReplicaSets
- DaemonSets
- Nodes
- ConfigMaps
- Services
- Jobs
- CronJobs
- Endpoints
- Events
- Horizontal Pod Autoscalers
- Ingresses
- Namespaces
Metoro explicitly does not export secrets. If you have resources you want to exclude from exporting, you can remove them from the service account permissions given to the cluster agent. See the permissions here.
Resource Metrics
Kubernetes resources can be analyzed using the kubernetes_resource
metric type. This allows you to:
Count Resources
Track the number of resources by various attributes:
Resource Attributes
Common attributes available for filtering and grouping:
- Environment
- Namespace
- Kind
- Resource name
- Service name
- Additional attributes specific to resource types
Track Resource State
Monitor specific resource attributes over time:
Viewing Resources
You can view resources associated with each service in the Metoro UI:
- Navigate to a service page
- Select the Kubernetes tab
- View current and historical resource states
Use Cases
- Change Tracking:
- Track configuration changes
- Monitor scaling events
- Debug resource modifications
- Resource Analysis:
- Count resources by type
- Monitor replica counts
- Track resource distribution
- Historical Debugging:
- View past cluster states
- Analyze resource evolution
- Investigate incidents
Best Practices
- Resource Monitoring:
- Track critical resource counts
- Monitor scaling patterns
- Set up alerts for unexpected changes
- Historical Analysis:
- Use time-travel for debugging
- Compare states across time periods
- Track configuration evolution
- Metric Usage:
- Group resources meaningfully
- Track relevant attributes
- Combine with other metric types
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