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add Dynatrace Kubernetes monitoring (#9504)

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* add Dynatrace Kubernetes monitoring

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This commit is contained in:
Gerald Haydtner
2018-08-20 21:34:13 +02:00
committed by k8s-ci-robot
parent 9d7329a54f
commit 713976fe55
1 changed files with 17 additions and 14 deletions
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content/en/docs/tasks/debug-application-cluster/resource-usage-monitoring.md
+17 -14
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@@ -2,7 +2,7 @@
reviewers:
- mikedanese
content_template: templates/concept
title: Tools for Monitoring Compute, Storage, and Network Resources
title: Tools for Monitoring Resources
---
{{% capture overview %}}
@@ -26,7 +26,7 @@ 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** provides a limited set of metrics related
- 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)
@@ -36,17 +36,19 @@ monitoring statistics by default:
[cAdvisor](https://github.com/google/cadvisor). `metrics-server` is a
lightweight short-term in-memory store.
- A **full monitoring pipeline**, such as Prometheus, gives you access to richer
- 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. See
[Full metrics pipeline](#full-metrics-pipelines) for more information about
some popular pipelines that implement these APIs and enable these
capabilities.
`external.metrics.k8s.io` API.
## Resource metrics pipeline
### Kubelet
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 cAdvisor. It then exposes the aggregated pod resource usage statistics via a REST API.
### cAdvisor
@@ -56,14 +58,9 @@ On most Kubernetes clusters, cAdvisor exposes a simple UI for on-machine contain
![cAdvisor](/images/docs/cadvisor.png)
### Kubelet
## Full metrics pipelines
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 cAdvisor. It then exposes the aggregated pod resource usage statistics via a REST API.
## Full Metrics Pipelines
Many full metrics solutions exist for Kubernetes. Prometheus and Google Cloud
Monitoring are two of the most popular.
Many full metrics solutions exist for Kubernetes.
### Prometheus
@@ -92,4 +89,10 @@ This video shows how to configure and run a Google Cloud Monitoring backed Heaps
{{< 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." >}}
### Dynatrace Kubernetes monitoring
With [Dynatrace Kubernetes monitoring](https://www.dynatrace.com/technologies/cloud-and-microservices/kubernetes-monitoring/), you can monitor application and cluster health in highly-dynamic Kubernetes environments.
Dynatrace automatically discovers all containers running on Kubernetes and presents you with a real-time view of all the connections between your containerized processes, hosts, and cloud instances. Dynatrace includes root cause analysis and the ability to replay problems to see how they evolved over time.
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