Metrics in Kubernetes: Difference between revisions
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==Resource Metrics Pipeline== | ==Resource Metrics Pipeline== | ||
{{External|https://kubernetes.io/docs/tasks/debug-application-cluster/resource-usage-monitoring/#resource-metrics-pipeline}} | {{External|https://kubernetes.io/docs/tasks/debug-application-cluster/resource-usage-monitoring/#resource-metrics-pipeline}} | ||
A resource metrics pipeline provides a limited set of metrics that are consumed by the [[Kubernetes Horizontal Pod Autoscaler|horizontal pod autoscaler]] or [[kubernetes top]] utility. The metrics are collected by the lightweight, short-term, in-memory [[Kubernetes Metrics Server|metrics-server]] and exposed via the metrics.k8s.io [[Metrics_in_Kubernetes#Resource_Metrics_API|Resource Metrics API]]. | |||
==Full Metrics Pipeline== | ==Full Metrics Pipeline== | ||
{{External|https://kubernetes.io/docs/tasks/debug-application-cluster/resource-usage-monitoring/#full-metrics-pipeline}} | {{External|https://kubernetes.io/docs/tasks/debug-application-cluster/resource-usage-monitoring/#full-metrics-pipeline}} | ||
Revision as of 23:14, 5 October 2020
Internal
Overview
Application health monitoring, resource consumption monitoring and scaling decisions require metrics collection and analysis. Kubernetes facilitates metrics collection from containers, pods, services and the overall cluster via metric pipelines.
Metric Pipeline
A metric pipeline is a solution that allows metrics collection, propagation, possibly storage, and publishing. In Kubernetes, application monitoring does not depend on a single monitoring solution. Kubernetes allows for different types of metric pipelines: resource metrics pipelines and full metrics pipelines.
Resource Metrics Pipeline
A resource metrics pipeline provides a limited set of metrics that are consumed by the horizontal pod autoscaler or kubernetes top utility. The metrics are collected by the lightweight, short-term, in-memory metrics-server and exposed via the metrics.k8s.io Resource Metrics API.
Full Metrics Pipeline
Resource
Metrics
Resource Metrics
A resource metric is a numeric quantity that tracks either the CPU or memory consumed by containers and pods. By default, the only two supported resource metrics are the CPU utilization and the memory consumed by a container. These resources do not change names from cluster to cluster and they should be available as long the Resource Metrics API is available.
Resource Metrics API
metrics.k8s.io TODO:
- https://github.com/kubernetes/community/blob/master/contributors/design-proposals/instrumentation/resource-metrics-api.md
- https://github.com/kubernetes/community/blob/master/contributors/design-proposals/instrumentation/custom-metrics-api.md
Custom Metrics
Aside from resource metrics, there are two other types of metrics, both of which are considered custom metrics: pod metrics and object metrics. Custom metrics track resources used by Kubernetes objects (pods or otherwise).
Pod Metrics
Pod metrics track resources that describe pods.
Object Metrics
Object metrics track resources describe different objects in the same namespace, instead of describing pods.
Custom Metrics API
custom.metrics.k8s.io
Monitoring systems like Prometheus expose application-specific metrics to the Horizontal Pod Autoscaler controller via the Custom Metrics API.
External Metrics
External Metrics API
external.metrics.k8s.io
Sources of Metrics
Kubernetes Metrics Server
Prometheus
Notes
- More details about resource metrics API.
- Metrics: raw values, utilization values.
- Metric server: https://kubernetes.io/docs/tasks/debug-application-cluster/resource-metrics-pipeline/, https://github.com/kubernetes-sigs/metrics-server
- Custom metrics API: https://github.com/kubernetes/community/blob/master/contributors/design-proposals/instrumentation/custom-metrics-api.md
- External metrics API: https://github.com/kubernetes/community/blob/master/contributors/design-proposals/instrumentation/external-metrics-api.md