Add short section about metrics server

slides/k8s/metrics-server.md

@@ -0,0 +1,66 @@
+# Checking pod and node resource usage
+
+- Since Kubernetes 1.8, metrics are collected by the [core metrics pipeline](https://v1-13.docs.kubernetes.io/docs/tasks/debug-application-cluster/core-metrics-pipeline/)
+
+- The core metrics pipeline is:
+
+  - optional (Kubernetes can function without it)
+
+  - necessary for some features (like the Horizontal Pod Autoscaler)
+
+  - exposed through the Kubernetes API using the [aggregation layer](https://kubernetes.io/docs/concepts/extend-kubernetes/api-extension/apiserver-aggregation/)
+
+  - usually implemented by the "metrics server"
+
+---
+
+## How to know if the metrics server is running?
+
+- The easiest way to know is to run `kubectl top`
+
+.exercise[
+
+- Check if the core metrics pipeline is available:
+  ```bash
+  kubectl top nodes
+  ```
+
+]
+
+If it shows our nodes and their CPU and memory load, we're good!
+
+---
+
+## Installing metrics server
+
+- The  metrics server doesn't have any particular requirement
+
+  (it doesn't need persistence, as it doesn't *store* metrics)
+
+- It has its own repository, [kubernetes-incubator/metrics-server](https://github.com/kubernetes-incubator/metrics-server])
+
+- The repository comes with [YAML files for deployment](https://github.com/kubernetes-incubator/metrics-server/tree/master/deploy/1.8%2B)
+
+- These files may not work on some clusters
+
+  (e.g. if your node names are not in DNS)
+
+- The container.training repository has a [metrics-server.yaml](https://github.com/jpetazzo/container.training/blob/master/k8s/metrics-server.yaml#L90) file to help with that
+
+  (we can `kubectl apply -f` that file if needed)
+
+---
+
+## Showing container resource usage
+
+- Once metrics server is running, we can check container resource usage
+
+.exercise[
+
+- Show resource usage accross all containers:
+  ```bash
+  kuebectl top pods --containers --all-namespaces
+  ```
+]
+
+- We can also use selectors (`-l app=...`)