Add link to HorzPodAuto; add that there are other full pipelines (#15863)
Add link to Horizontal Pod Autoscaler; add that there are other full metrics pipelines but those outside of CNCF are beyond the scope of the k8s docspull/14863/head
aimeeu
Kubernetes Prow Robot
parent
d10ac36f2f
commit
361cf02a17
|
|
@ -20,99 +20,39 @@ where bottlenecks can be removed to improve overall performance.
|
|||
|
||||
{{% capture body %}}
|
||||
|
||||
In Kubernetes, application monitoring does not depend on a single monitoring
|
||||
solution. On new clusters, you can use two separate pipelines to collect
|
||||
monitoring statistics by default:
|
||||
|
||||
- The [**resource metrics pipeline**](#resource-metrics-pipeline) provides a limited set of metrics related
|
||||
to cluster components such as the HorizontalPodAutoscaler controller, as well
|
||||
as the `kubectl top` utility. These metrics are collected by
|
||||
[metrics-server](https://github.com/kubernetes-incubator/metrics-server)
|
||||
and are exposed via the `metrics.k8s.io` API. `metrics-server` discovers
|
||||
all nodes on the cluster and queries each node's [Kubelet](/docs/admin/kubelet)
|
||||
for CPU and memory usage. The Kubelet fetches the data from
|
||||
[cAdvisor](https://github.com/google/cadvisor). `metrics-server` is a
|
||||
lightweight short-term in-memory store.
|
||||
|
||||
- A [**full metrics pipeline**](#full-metrics-pipelines), such as Prometheus, gives you access to richer
|
||||
metrics. In addition, Kubernetes can respond to these metrics by automatically
|
||||
scaling or adapting the cluster based on its current state, using mechanisms
|
||||
such as the Horizontal Pod Autoscaler. The monitoring pipeline fetches
|
||||
metrics from the Kubelet, and then exposes them to Kubernetes via an adapter
|
||||
by implementing either the `custom.metrics.k8s.io` or
|
||||
`external.metrics.k8s.io` API.
|
||||
In Kubernetes, application monitoring does not depend on a single monitoring solution. On new clusters, you can use [resource metrics](#resource-metrics-pipeline) or [full metrics](#full-metrics-pipeline) pipelines to collect monitoring statistics.
|
||||
|
||||
## Resource metrics pipeline
|
||||
|
||||
### Kubelet
|
||||
The resource metrics pipeline provides a limited set of metrics related to
|
||||
cluster components such as the [Horizontal Pod Autoscaler](/docs/tasks/run-application/horizontal-pod-autoscale) controller, as well as the `kubectl top` utility.
|
||||
These metrics are collected by the lightweight, short-term, in-memory
|
||||
[metrics-server](https://github.com/kubernetes-incubator/metrics-server) and
|
||||
are exposed via the `metrics.k8s.io` API.
|
||||
|
||||
The Kubelet acts as a bridge between the Kubernetes master and the nodes. It manages the pods and containers running on a machine. Kubelet translates each pod into its constituent containers and fetches individual container usage statistics from the container runtime, through the container runtime interface. For the legacy docker integration, it fetches this information from cAdvisor. It then exposes the aggregated pod resource usage statistics through the kubelet resource metrics api. This api is served at `/metrics/resource/v1alpha1` on the kubelet's authenticated and read-only ports.
|
||||
metrics-server discovers all nodes on the cluster and
|
||||
queries each node's
|
||||
[kubelet](/docs/reference/command-line-tools-reference/kubelet) for CPU and
|
||||
memory usage. The kubelet acts as a bridge between the Kubernetes master and
|
||||
the nodes, managing the pods and containers running on a machine. The kubelet
|
||||
translates each pod into its constituent containers and fetches individual
|
||||
container usage statistics from the container runtime through the container
|
||||
runtime interface. The kubelet fetches this information from the integrated
|
||||
cAdvisor for the legacy Docker integration. It then exposes the aggregated pod
|
||||
resource usage statistics through the metrics-server Resource Metrics API.
|
||||
This API is served at `/metrics/resource/v1beta1` on the kubelet's authenticated and
|
||||
read-only ports.
|
||||
|
||||
### cAdvisor
|
||||
## Full metrics pipeline
|
||||
|
||||
cAdvisor is an open source container resource usage and performance analysis agent. It is purpose-built for containers and supports Docker containers natively. In Kubernetes, cAdvisor is integrated into the Kubelet binary. cAdvisor auto-discovers all containers in the machine and collects CPU, memory, filesystem, and network usage statistics. cAdvisor also provides the overall machine usage by analyzing the 'root' container on the machine.
|
||||
A full metrics pipeline gives you access to richer metrics. Kubernetes can
|
||||
respond to these metrics by automatically scaling or adapting the cluster
|
||||
based on its current state, using mechanisms such as the Horizontal Pod
|
||||
Autoscaler. The monitoring pipeline fetches metrics from the kubelet and
|
||||
then exposes them to Kubernetes via an adapter by implementing either the
|
||||
`custom.metrics.k8s.io` or `external.metrics.k8s.io` API.
|
||||
|
||||
Kubelet exposes a simple cAdvisor UI for containers on a machine, via the default port 4194.
|
||||
The picture below is an example showing the overall machine usage. However, this feature has been marked
|
||||
deprecated in v1.10 and completely removed in v1.12.
|
||||
|
||||
|
||||
|
||||
Starting from v1.13, you can [deploy cAdvisor as a DaemonSet](https://github.com/google/cadvisor/tree/master/deploy/kubernetes) for an access to the cAdvisor UI.
|
||||
|
||||
## Full metrics pipelines
|
||||
|
||||
Many full metrics solutions exist for Kubernetes.
|
||||
|
||||
### Prometheus
|
||||
|
||||
[Prometheus](https://prometheus.io) can natively monitor kubernetes, nodes, and prometheus itself.
|
||||
The [Prometheus Operator](https://coreos.com/operators/prometheus/docs/latest/)
|
||||
simplifies Prometheus setup on Kubernetes, and allows you to serve the
|
||||
custom metrics API using the
|
||||
[Prometheus adapter](https://github.com/directxman12/k8s-prometheus-adapter).
|
||||
Prometheus provides a robust query language and a built-in dashboard for
|
||||
querying and visualizing your data. Prometheus is also a supported
|
||||
data source for [Grafana](https://prometheus.io/docs/visualization/grafana/).
|
||||
|
||||
### Sysdig
|
||||
[Sysdig](http://sysdig.com) provides full spectrum container and platform intelligence, and is a
|
||||
true container native solution. Sysdig pulls together data from system calls, Kubernetes events,
|
||||
Prometheus metrics, statsD, JMX, and more into a single pane that gives you a comprehensive picture
|
||||
of your environment. Sysdig also provides an API to query for providing robust and customizable
|
||||
solutions. Sysdig is built on Open Source. [Sysdig and Sysdig Inspect](https://sysdig.com/opensource/inspect/) give you the
|
||||
ability to freely perform troubleshooting, performance analyis and forensics.
|
||||
|
||||
### Google Cloud Monitoring
|
||||
|
||||
Google Cloud Monitoring is a hosted monitoring service you can use to
|
||||
visualize and alert on important metrics in your application. You can collect
|
||||
metrics from Kubernetes, and you can access them
|
||||
using the [Cloud Monitoring Console](https://app.google.stackdriver.com/).
|
||||
You can create and customize dashboards to visualize the data gathered
|
||||
from your Kubernetes cluster.
|
||||
|
||||
This video shows how to configure and run a Google Cloud Monitoring backed Heapster:
|
||||
|
||||
[](https://www.youtube.com/watch?v=xSMNR2fcoLs)
|
||||
|
||||
|
||||
{{< figure src="/images/docs/gcm.png" alt="Google Cloud Monitoring dashboard example" title="Google Cloud Monitoring dashboard example" caption="This dashboard shows cluster-wide resource usage." >}}
|
||||
|
||||
## CronJob monitoring
|
||||
|
||||
### Kubernetes Job Monitor
|
||||
|
||||
With the [Kubernetes Job Monitor](https://github.com/pietervogelaar/kubernetes-job-monitor) dashboard a Cluster Administrator can see which jobs are running and view the status of completed jobs.
|
||||
|
||||
### New Relic Kubernetes monitoring integration
|
||||
|
||||
[New Relic Kubernetes](https://docs.newrelic.com/docs/integrations/host-integrations/host-integrations-list/kubernetes-monitoring-integration) integration provides increased visibility into the performance of your Kubernetes environment. New Relic's Kubernetes integration instruments the container orchestration layer by reporting metrics from Kubernetes objects. The integration gives you insight into your Kubernetes nodes, namespaces, deployments, replica sets, pods, and containers.
|
||||
|
||||
Marquee capabilities:
|
||||
View your data in pre-built dashboards for immediate insight into your Kubernetes environment.
|
||||
Create your own custom queries and charts in Insights from automatically reported data.
|
||||
Create alert conditions on Kubernetes data.
|
||||
Learn more on this [page](https://docs.newrelic.com/docs/integrations/host-integrations/host-integrations-list/kubernetes-monitoring-integration).
|
||||
[Prometheus](https://prometheus.io), a CNCF project, can natively monitor Kubernetes, nodes, and Prometheus itself.
|
||||
Full metrics pipeline projects that are not part of the CNCF are outside the scope of Kubernetes documentation.
|
||||
|
||||
{{% /capture %}}
|
||||
|
|
|
|||
Binary file not shown.
|
Before Width: | Height: | Size: 204 KiB |
Loading…
Reference in New Issue