From 713976fe556af4d1cb1499a1d1b16a19829178c0 Mon Sep 17 00:00:00 2001 From: Gerald Haydtner Date: Mon, 20 Aug 2018 21:34:13 +0200 Subject: [PATCH] add Dynatrace Kubernetes monitoring (#9504) * add Dynatrace Kubernetes monitoring * Fix heading structure * Shorten title * nest headers * refactor back heading structure * add links to sections * make img link https * fix space typo --- .../resource-usage-monitoring.md | 31 ++++++++++--------- 1 file changed, 17 insertions(+), 14 deletions(-) diff --git a/content/en/docs/tasks/debug-application-cluster/resource-usage-monitoring.md b/content/en/docs/tasks/debug-application-cluster/resource-usage-monitoring.md index a4855d8ddf..3b7a6c6547 100644 --- a/content/en/docs/tasks/debug-application-cluster/resource-usage-monitoring.md +++ b/content/en/docs/tasks/debug-application-cluster/resource-usage-monitoring.md @@ -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. + {{% /capture %}}