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235 lines
13 KiB
Plaintext
235 lines
13 KiB
Plaintext
# Kubernetes monitoring with Netdata
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This document gives an overview of what visualizations Netdata provides on Kubernetes deployments.
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At Netdata, we've built Kubernetes monitoring tools that add visibility without complexity while also helping you
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actively troubleshoot anomalies or outages. This guide walks you through each of the visualizations and offers best
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practices on how to use them to start Kubernetes monitoring in a matter of minutes, not hours or days.
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Netdata's Kubernetes monitoring solution uses a handful of [complementary tools and
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collectors](#related-reference-documentation) for peeling back the many complex layers of a Kubernetes cluster,
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_entirely for free_. These methods work together to give you every metric you need to troubleshoot performance or
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availability issues across your Kubernetes infrastructure.
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## Challenge
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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 preferred 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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## Solution
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In this tutorial, you'll learn how to navigate Netdata's Kubernetes monitoring features, using
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[robot-shop](https://github.com/instana/robot-shop) as an example deployment. Deploying robot-shop is purely optional.
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You can also follow along with your own Kubernetes deployment if you choose. While the metrics might be different, the
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navigation and best practices are the same for every cluster.
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## What you need to get started
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To follow this tutorial, you need:
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- A free Netdata Cloud account. [Sign up](https://app.netdata.cloud/sign-up?cloudRoute=/spaces) if you don't have one
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already.
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- A working cluster running Kubernetes v1.9 or newer, with a Netdata deployment and connected parent/child nodes. See
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our [Kubernetes deployment process](/packaging/installer/methods/kubernetes.md) for details on deployment and
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connecting to Cloud.
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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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### Install the `robot-shop` demo (optional)
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Begin by downloading the robot-shop code and using `helm` to create a new deployment.
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```bash
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git clone git@github.com:instana/robot-shop.git
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cd robot-shop/K8s/helm
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kubectl create ns robot-shop
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helm install robot-shop --namespace robot-shop .
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```
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Running `kubectl get pods` shows both the Netdata and robot-shop deployments.
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```bash
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kubectl get pods --all-namespaces
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NAMESPACE NAME READY STATUS RESTARTS AGE
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default netdata-child-29f9c 2/2 Running 0 10m
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default netdata-child-8xphf 2/2 Running 0 10m
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default netdata-child-jdvds 2/2 Running 0 11m
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default netdata-parent-554c755b7d-qzrx4 1/1 Running 0 11m
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kube-system aws-node-jnjv8 1/1 Running 0 17m
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kube-system aws-node-svzdb 1/1 Running 0 17m
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kube-system aws-node-ts6n2 1/1 Running 0 17m
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kube-system coredns-559b5db75d-f58hp 1/1 Running 0 22h
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kube-system coredns-559b5db75d-tkzj2 1/1 Running 0 22h
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kube-system kube-proxy-9p9cd 1/1 Running 0 17m
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kube-system kube-proxy-lt9ss 1/1 Running 0 17m
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kube-system kube-proxy-n75t9 1/1 Running 0 17m
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robot-shop cart-b4bbc8fff-t57js 1/1 Running 0 14m
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robot-shop catalogue-8b5f66c98-mr85z 1/1 Running 0 14m
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robot-shop dispatch-67d955c7d8-lnr44 1/1 Running 0 14m
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robot-shop mongodb-7f65d86c-dsslc 1/1 Running 0 14m
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robot-shop mysql-764c4c5fc7-kkbnf 1/1 Running 0 14m
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robot-shop payment-67c87cb7d-5krxv 1/1 Running 0 14m
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robot-shop rabbitmq-5bb66bb6c9-6xr5b 1/1 Running 0 14m
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robot-shop ratings-94fd9c75b-42wvh 1/1 Running 0 14m
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robot-shop redis-0 0/1 Pending 0 14m
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robot-shop shipping-7d69cb88b-w7hpj 1/1 Running 0 14m
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robot-shop user-79c445b44b-hwnm9 1/1 Running 0 14m
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robot-shop web-8bb887476-lkcjx 1/1 Running 0 14m
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```
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## Explore Netdata's Kubernetes monitoring charts
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The Netdata Helm chart deploys and enables everything you need for monitoring Kubernetes on every layer. Once you deploy
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Netdata and connect your cluster's nodes, you're ready to check out the visualizations **with zero configuration**.
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To get started, [sign in](https://app.netdata.cloud/sign-in?cloudRoute=/spaces) to your Netdata Cloud account. Head over
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to the Room you connected your cluster to, if not **General**.
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Let's walk through monitoring each layer of a Kubernetes cluster using the Overview as our framework.
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## Cluster and node metrics
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The gauges and time-series charts you see right away in the Overview show aggregated metrics from every node in your
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cluster.
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For example, the `apps.cpu` chart (in the **Applications** menu item), visualizes the CPU utilization of various
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applications/services running on each of the nodes in your cluster. The **X Nodes** dropdown shows which nodes
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contribute to the chart and links to jump a single-node dashboard for further investigation.
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For example, the chart above shows a spike in the CPU utilization from `rabbitmq` every minute or so, along with a
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baseline CPU utilization of 10-15% across the cluster.
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## Pod and container metrics
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Click on the **Kubernetes xxxxxxx...** section to jump down to Netdata Cloud's unique Kubernetes visualizations for view
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real-time resource utilization metrics from your Kubernetes pods and containers.
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### Health map
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The first visualization is the [health map](/docs/dashboards-and-charts/kubernetes-tab.md#health-map),
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which places each container into its own box, then varies the intensity of their color to visualize the resource
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utilization. By default, the health map shows the **average CPU utilization as a percentage of the configured limit**
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for every container in your cluster.
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Let's explore the most colorful box by hovering over it.
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The **Context** tab shows `rabbitmq-5bb66bb6c9-6xr5b` as the container's image name, which means this container is
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running a [RabbitMQ](/src/go/plugin/go.d/modules/rabbitmq/README.md) workload.
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Click the **Metrics** tab to see real-time metrics from that container. Unsurprisingly, it shows a spike in CPU
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utilization at regular intervals.
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### Time-series charts
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Beneath the health map is a variety of time-series charts that help you visualize resource utilization over time, which
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is useful for targeted troubleshooting.
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The default is to display metrics grouped by the `k8s_namespace` label, which shows resource utilization based on your
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different namespaces.
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Each composite chart has a [definition bar](/docs/dashboards-and-charts/netdata-charts.md#definition-bar)
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for complete customization. For example, grouping the top chart by `k8s_container_name` reveals new information.
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## Service metrics
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Netdata has a [service discovery plugin](https://github.com/netdata/agent-service-discovery), which discovers and
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creates configuration files for [compatible
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services](https://github.com/netdata/helmchart#service-discovery-and-supported-services) and any endpoints covered by
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our [generic Prometheus collector](/src/go/plugin/go.d/modules/prometheus/README.md).
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Netdata uses these files to collect metrics from any compatible application as they run _inside_ of a pod. Service
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discovery happens without manual intervention as pods are created, destroyed, or moved between nodes.
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Service metrics show up on the Overview as well, beneath the **Kubernetes** section, and are labeled according to the
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service in question. For example, the **RabbitMQ** section has numerous charts from the [`rabbitmq`
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collector](/src/go/plugin/go.d/modules/rabbitmq/README.md):
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> The robot-shop cluster has more supported services, such as MySQL, which are not visible with zero configuration. This
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> is usually because of services running on non-default ports, using non-default names, or required passwords. Read up
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> on [configuring service discovery](/packaging/installer/methods/kubernetes.md#configure-service-discovery) to collect
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> more service metrics.
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Service metrics are essential to infrastructure monitoring, as they're the best indicator of the end-user experience,
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and key signals for troubleshooting anomalies or issues.
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## Kubernetes components
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Netdata also automatically collects metrics from two essential Kubernetes processes.
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### kubelet
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The **k8s kubelet** section visualizes metrics from the Kubernetes agent responsible for managing every pod on a given
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node. This also happens without any configuration thanks to the [kubelet
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collector](/src/go/plugin/go.d/modules/k8s_kubelet/README.md).
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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 if the number of running containers/pods has dropped, which could signal a fault or crash in a particular
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Kubernetes service or deployment (see `kubectl get services` or `kubectl get deployments` for more details). If the
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number of pods increases, it may be because of something more benign, like another team member scaling up a
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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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### kube-proxy
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The **k8s kube-proxy** section displays metrics about the network proxy that runs on each node in your Kubernetes
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cluster. kube-proxy lets pods communicate with each other and accept sessions from outside your cluster. Its metrics are
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collected by the [kube-proxy
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collector](/src/go/plugin/go.d/modules/k8s_kubeproxy/README.md).
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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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## What's next?
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After reading this guide, you should now be able to monitor any Kubernetes cluster with Netdata, including nodes, pods,
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containers, services, and more.
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With the health map, time-series charts, and the ability to drill down into individual nodes, you can see hundreds of
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per-second metrics with zero configuration and less time remembering all the `kubectl` options. Netdata moves with your
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cluster, automatically picking up new nodes or services as your infrastructure scales. And it's entirely free for
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clusters of all sizes.
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### Related reference documentation
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- [Netdata Helm chart](https://github.com/netdata/helmchart)
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- [Netdata service discovery](https://github.com/netdata/agent-service-discovery)
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- [Netdata Agent · `kubelet`
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collector](/src/go/plugin/go.d/modules/k8s_kubelet/README.md)
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- [Netdata Agent · `kube-proxy`
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collector](/src/go/plugin/go.d/modules/k8s_kubeproxy/README.md)
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- [Netdata Agent · `cgroups.plugin`](/src/collectors/cgroups.plugin/README.md)
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