Add guide for monitoring a k8s cluster with Netdata
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Joel Hans
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<!--
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title: "Monitor a Kubernetes (k8s) cluster with Netdata"
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description: "Use Netdata's helmchart, service discovery plugin, and Kubelet/kube-proxy collectors for real-time visibility into your Kubernetes cluster."
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image: /img/seo/guides/monitor/kubernetes-k8s-netdata.png
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custom_edit_url: https://github.com/netdata/netdata/edit/master/docs/guides/monitor/kubernetes-k8s-netdata.md
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-->
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# Monitor a Kubernetes cluster with Netdata
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While Kubernetes (k8s) might simplify the way you deploy, scale, and load-balance your applications, not all clusters
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come with "batteries included" when it comes to monitoring. Doubly so for a monitoring stack that helps you actively
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troubleshoot issues with your cluster.
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Some k8s providers, like GKE (Google Kubernetes Engine), do deploy clusters bundled with monitoring capabilities, such
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as Google Stackdriver Monitoring. However, these pre-configured solutions might not offer the depth of metrics,
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customization, or integration with your perferred alerting methods.
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Without this visibility, it's like you built an entire house and _then_ smashed your way through the finished walls to
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add windows.
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At Netdata, we're working to build Kubernetes monitoring tools that add visibility without complexity while also helping
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you actively troubleshoot anomalies or outages. Better yet, this toolkit includes a few complementary collectors that
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let you monitor the many layers of a Kubernetes cluster entirely for free.
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We already have a few complementary tools and collectors for monitoring the many layers of a Kubernetes cluster,
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_entirely for free_. These methods work together to help you troubleshoot performance or availablility issues across
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your k8s infrastructure.
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- A [Helm chart](https://github.com/netdata/helmchart), which bootstraps a Netdata Agent pod on every node in your
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cluster, plus an additional parent pod for storing metrics and managing alarm notifications.
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- A [service discovery plugin](https://github.com/netdata/agent-service-discovery), which discovers and immediately
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monitors 22 different services that might be running inside of your cluster's pods. Service discovery happens
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without manual intervention as pods are created, destroyed, or moved between nodes. [Compatible
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services](https://github.com/netdata/helmchart#service-discovery-and-supported-services) include Nginx, Apache,
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MySQL, CoreDNS, and much more.
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- A [Kubelet collector](https://learn.netdata.cloud/docs/agent/collectors/go.d.plugin/modules/k8s_kubelet), which runs
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on each node in a k8s cluster to monitor the number of pods/containers, the volume of operations on each container,
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and more.
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- A [kube-proxy collector](https://learn.netdata.cloud/docs/agent/collectors/go.d.plugin/modules/k8s_kubeproxy), which
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also runs on each node and monitors latency and the volume of HTTP requests to the proxy.
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- A [cgroups collector](/collectors/cgroups.plugin/README.md), which collects CPU, memory, and bandwidth metrics for
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each container running on your k8s cluster.
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By following this guide, you'll learn how to discover, explore, and take away insights from each of these layers in your
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Kubernetes cluster. Let's get started.
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## Prerequisites
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To follow this guide, you need:
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- A working cluster running Kubernetes v1.9 or newer.
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- The [kubectl](https://kubernetes.io/docs/reference/kubectl/overview/) command line tool, within [one minor version
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difference](https://kubernetes.io/docs/tasks/tools/install-kubectl/#before-you-begin) of your cluster, on an
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administrative system.
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- The [Helm package manager](https://helm.sh/) v3.0.0 or newer on the same administrative system.
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**You need to install the Netdata Helm chart on your cluster** before you proceed. See our [Kubernetes installation
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process](/packaging/installer/methods/kubernetes.md) for details.
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This guide uses a 3-node cluster, running on Digital Ocean, as an example. This cluster runs CockroachDB, Redis, and
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Apache, which we'll use as examples of how to monitor a Kubernetes cluster with Netdata.
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```bash
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kubectl get nodes
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NAME STATUS ROLES AGE VERSION
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pool-0z7557lfb-3fnbf Ready <none> 51m v1.17.5
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pool-0z7557lfb-3fnbx Ready <none> 51m v1.17.5
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pool-0z7557lfb-3fnby Ready <none> 51m v1.17.5
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kubectl get pods
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NAME READY STATUS RESTARTS AGE
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cockroachdb-0 1/1 Running 0 44h
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cockroachdb-1 1/1 Running 0 44h
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cockroachdb-2 1/1 Running 1 44h
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cockroachdb-init-q7mp6 0/1 Completed 0 44h
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httpd-6f6cb96d77-4zlc9 1/1 Running 0 2m47s
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httpd-6f6cb96d77-d9gs6 1/1 Running 0 2m47s
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httpd-6f6cb96d77-xtpwn 1/1 Running 0 11m
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netdata-child-5p2m9 2/2 Running 0 42h
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netdata-child-92qvf 2/2 Running 0 42h
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netdata-child-djc6w 2/2 Running 0 42h
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netdata-parent-0 1/1 Running 0 42h
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redis-6bb94d4689-6nn6v 1/1 Running 0 73s
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redis-6bb94d4689-c2fk2 1/1 Running 0 73s
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redis-6bb94d4689-tjcz5 1/1 Running 0 88s
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```
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## Explore Netdata's Kubernetes charts
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The Helm chart installs and enables everything you need for visibility into your k8s cluster, including the service
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discovery plugin, Kubelet collector, kube-proxy collector, and cgroups collector.
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To get started, open your browser and navigate to your cluster's Netdata dashboard. See our [Kubernetes installation
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instructions](/packaging/installer/methods/kubernetes.md) for how to access the dashboard based on your cluster's
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configuration.
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You'll see metrics from the parent pod as soon as you navigate to the dashboard:
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Remember that the parent pod is responsible for storing metrics from all the child pods and sending alarms.
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Take note of the **Replicated Nodes** menu, which shows not only the parent pod, but also the three child pods. This
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example cluster has three child pods, but the number of child pods depends entirely on the number of nodes in your
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cluster.
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You'll use the links in the **Replicated Nodes** menu to navigate between the various pods in your cluster. Let's do
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that now to explore the pod-level Kubernetes monitoring Netdata delivers.
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### Pods
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Click on any of the nodes under **netdata-parent-0**. Netdata redirects you to a separate instance of the Netdata
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dashboard, run by the Netdata child pod, which visualizes thousands of metrics from that node.
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From this dashboard, you can see all the familiar charts showing the health and performance of an individual node, just
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like you would if you installed Netdata on a single physical system. Explore CPU, memory, bandwidth, networking, and
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more.
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You can use the menus on the right-hand side of the dashboard to navigate between different sections of charts and
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metrics.
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For example, click on the **Applications** section to view per-application metrics, collected by
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[apps.plugin](/collectors/apps.plugin/README.md). The first chart you see is **Apps CPU Time (100% = 1 core)
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(apps.cpu)**, which shows the CPU utilization of various applications running on the node. You shouldn't be surprised to
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find Netdata processes (`netdata`, `sd-agent`, and more) alongside Kubernetes processes (`kubelet`, `kube-proxy`, and
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`containers`).
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Beneath the **Applications** section, you'll begin to see sections for **k8s kubelet**, **k8s kubeproxy**, and long
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strings that start with **k8s**, which are sections for metrics collected by
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[`cgroups.plugin`](/collectors/cgroups.plugin/README.md). Let's skip over those for now and head further down to see
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Netdata's service discovery in action.
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### Service discovery (services running inside of pods)
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Thanks to Netdata's service discovery feature, you monitor containerized applications running in k8s pods with zero
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configuration or manual intervention. Service discovery is like a watchdog for created or deleted pods, recognizing the
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service they run based on the image name and port and immediately attempting to apply a logical default configuration.
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Service configuration supports [22
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services](https://github.com/netdata/helmchart#service-discovery-and-supported-services), which are automatically added
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or removed from Netdata as soon as the pods are created or destroyed.
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You can find these service discovery sections near the bottom of the menu. The names for these sections follow a
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pattern: the name of the detected service, followed by a string of the module name, pod TUID, service type, port
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protocol, and port number. See the graphic below to help you identify service discovery sections.
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For example, the first service discovery section shows metrics for a pod running an Apache web server running on port 80
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in a pod named `httpd-6f6cb96d77-xtpwn`.
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> If you don't see any service discovery sections, it's either because your services are not compatible with service
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> discovery or you changed their default configuration, such as the listening port. See the [list of supported
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> services](https://github.com/netdata/helmchart#service-discovery-and-supported-services) for details about whether
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> your installed services are compatible with service discovery, or read the [configuration
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> instructions](/packaging/installer/methods/kubernetes.md#configure-service-discovery) to change how it discovers the
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> supported services.
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Click on any of these service discovery sections to see metrics from that particular service. For example, click on the
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**Apache apache-default httpd-6f6cb96d77-xtpwn httpd tcp 80** section brings you to a series of charts populated by the
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[Apache collector](https://learn.netdata.cloud/docs/agent/collectors/go.d.plugin/modules/apache) itself.
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With service discovery, you can now see valuable metrics like requests, bandwidth, workers, and more for this pod.
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The same goes for metrics coming from the CockroachDB pod running on this same node.
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Service discovery helps you monitor the health of specific applications running on your Kubernetes cluster, which in
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turn gives you a complete resource when troubleshooting your infrastructure's health and performance.
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### Kubelet
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Let's head back up the menu to the **k8s kubelet** section. Kubelet is an agent that runs on every node in a cluster. It
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receives a set of PodSpecs from the Kubernetes Control Plane and ensures the pods described there are both running and
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healthy. Think of it as a manager for the various pods on that node.
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Monitoring each node's Kubelet can be invaluable when diagnosing issues with your Kubernetes cluster. For example, you
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can see when the volume of running containers/pods has dropped.
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This drop might signal a fault or crash in a particular Kubernetes service or deployment (see `kubectl get services` or
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`kubectl get deployments` for more details). If the number of pods increases, it may be because of something more
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benign, like another member of your team scaling up a service with `kubectl scale`.
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You can also view charts for the Kubelet API server, the volume of runtime/Docker operations by type,
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configuration-related errors, and the actual vs. desired numbers of volumes, plus a lot more.
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Kubelet metrics are collected and visualized thanks to the [kubelet
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collector](https://learn.netdata.cloud/docs/agent/collectors/go.d.plugin/modules/k8s_kubelet), which is enabled with
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zero configuration on most Kubernetes clusters with standard configurations.
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### kube-proxy
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Scroll down into the **k8s kubeproxy** section to see metrics about the network proxy that runs on each node in your
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Kubernetes cluster. kube-proxy allows for pods to communicate with each other and accept sessions from outside your
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cluster.
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With Netdata, you can monitor how often your k8s proxies are syncing proxy rules between nodes. Dramatic changes in
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these figures could indicate an anomaly in your cluster that's worthy of further investigation.
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kube-proxy metrics are collected and visualized thanks to the [kube-proxy
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collector](https://learn.netdata.cloud/docs/agent/collectors/go.d.plugin/modules/k8s_kubeproxy), which is enabled with
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zero configuration on most Kubernetes clusters with standard configurations.
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### Containers
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We can finally talk about the final piece of Kubernetes monitoring: containers. Each Kubernetes pod is a set of one or
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more cooperating containers, sharing the same namespace, all of which are resourced and tracked by the cgroups feature
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of the Linux kernel. Netdata automatically detects and monitors each running container by interfacing with the cgroups
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feature itself.
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You can find these sections beneath **Users**, **k8s kubelet**, and **k8s kubeproxy**. Below, a number of containers
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devoted to running services like CockroachDB, Apache, Redis, and more.
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Let's look at the section devoted to the container that runs the Apache pod named `httpd-6f6cb96d77-xtpwn`, as described
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in the previous part on [service discovery](#service-discovery-services-running-inside-of-pods).
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At first glance, these sections might seem redundant. You might ask, "Why do I need both a service discovery section
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_and_ a container section? It's just one pod, after all!"
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The difference is that while the service discovery section shows _Apache_ metrics, the equivalent cgroups section shows
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that container's CPU, memory, and bandwidth usage. You can use the two sections in conjunction to monitor the health and
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performance of your pods and the services they run.
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For example, let's say you get an alarm notification from `netdata-parent-0` saying the
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`ea287694-0f22-4f39-80aa-2ca066caf45a` container (also known as the `httpd-6f6cb96d77-xtpwn` pod) is using 99% of its
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available RAM. You can then hop over to the **Apache apache-default httpd-6f6cb96d77-xtpwn httpd tcp 80** section to
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further investigate why Apache is using an unexpected amount of RAM.
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All container metrics, whether they're managed by Kubernetes or the Docker service directly, are collected by the
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[cgroups collector](/collectors/cgroups.plugin/README.md). Because this collector integrates with the cgroups Linux
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kernel feature itself, monitoring containers requires zero configuration on most Kubernetes clusters.
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## What's next?
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After following this guide, you should have a more comprehensive understanding of how to monitor your Kubernetes cluster
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with Netdata. With this setup, you can monitor the health and performance of all your nodes, pods, services, and k8s
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agents. Pre-configured alarms will tell you when something goes awry, and this setup gives you every per-second metric
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you need to make informed decisions about your cluster.
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The best part of monitoring a Kubernetes cluster with Netdata is that you don't have to worry about constantly running
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complex `kubectl` commands to see hundreds of highly granular metrics from your nodes. And forget about using `kubectl
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exec -it pod bash` to start up a shell on a pod to find and diagnose an issue with any given pod on your cluster.
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And with service discovery, all your compatible pods will automatically appear and disappear as they scale up, move, or
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scale down across your cluster.
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To monitor your Kubernetes cluster with Netdata, start by [installing the Helm
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chart](/packaging/installer/methods/kubernetes.md) if you haven't already. The Netdata Agent is open source and entirely
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free for every cluster and every organization, whether you have 10 or 10,000 pods. A few minutes and one `helm install`
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later and you'll have started on the path of building an effective platform for troubleshooting the next performance or
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availability issue on your Kubernetes cluster.
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[](<>)
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@ -149,6 +149,9 @@ helm upgrade netdata ./netdata-helmchart
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## What's next?
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Read the [monitoring a Kubernetes cluster guide](/docs/guides/monitor/kubernetes-k8s-netdata.md) for details on the
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various metrics and charts created by the Helm chart and some best practices on real-time troubleshooting using Netdata.
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Check out our [Agent's getting started guide](/docs/getting-started.md) for a quick overview of Netdata's capabilities,
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especially if you want to change any of the configuration settings for either the parent or child nodes.
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