# Running our first containers on Kubernetes - First things first: we cannot run a container -- - We are going to run a pod, and in that pod there will be a single container -- - In that container in the pod, we are going to run a simple `ping` command - Then we are going to start additional copies of the pod --- ## Starting a simple pod with `kubectl run` - We need to specify at least a *name* and the image we want to use .exercise[ - Let's ping `goo.gl`: ```bash kubectl run pingpong --image alpine ping goo.gl ``` ] -- OK, what just happened? --- ## Behind the scenes of `kubectl run` - Let's look at the resources that were created by `kubectl run` .exercise[ - List most resource types: ```bash kubectl get all ``` ] -- We should see the following things: - `deploy/pingpong` (the *deployment* that we just created) - `rs/pingpong-xxxx` (a *replica set* created by the deployment) - `po/pingpong-yyyy` (a *pod* created by the replica set) --- ## Deployments, replica sets, and replication controllers - A *deployment* is a high-level construct - allows scaling, rolling updates, rollbacks - multiple deployments can be used together to implement a [canary deployment](https://kubernetes.io/docs/concepts/cluster-administration/manage-deployment/#canary-deployments) - delegates pods management to *replica sets* - A *replica set* is a low-level construct - makes sure that a given number of identical pods are running - allows scaling - rarely used directly - A *replication controller* is the (deprecated) predecessor of a replica set --- ## Our `pingpong` deployment - `kubectl run` created a *deployment*, `deploy/pingpong` - That deployment created a *replica set*, `rs/pingpong-xxxx` - That replica set created a *pod*, `po/pingpong-yyyy` - We'll see later how these folks play together for: - scaling - high availability - rolling updates --- ## Viewing container output - Let's use the `kubectl logs` command - We will pass either a *pod name*, or a *type/name* (E.g. if we specify a deployment or replica set, it will get the first pod in it) - Unless specified otherwise, it will only show logs of the first container in the pod (Good thing there's only one in ours!) .exercise[ - View the result of our `ping` command: ```bash kubectl logs deploy/pingpong ``` ] --- ## Streaming logs in real time - Just like `docker logs`, `kubectl logs` supports convenient options: - `-f`/`--follow` to stream logs in real time (à la `tail -f`) - `--tail` to indicate how many lines you want to see (from the end) - `--since` to get logs only after a given timestamp .exercise[ - View the latest logs of our `ping` command: ```bash kubectl logs deploy/pingpong --tail 1 --follow ``` ] --- ## Scaling our application - We can create additional copies of our container (I mean, our pod) with `kubectl scale` .exercise[ - Scale our `pingpong` deployment: ```bash kubectl scale deploy/pingpong --replicas 8 ``` ] Note: what if we tried to scale `rs/pingpong-xxxx`? We could! But the *deployment* would notice it right away, and scale back to the initial level. --- ## Resilience - The *deployment* `pingpong` watches its *replica set* - The *replica set* ensures that the right number of *pods* are running - What happens if pods disappear? .exercise[ - In a separate window, list pods, and keep watching them: ```bash kubectl get pods -w ``` - Destroy a pod: ```bash kubectl delete pod pingpong-yyyy ``` ] --- ## What if we wanted something different? - What if we wanted to start a "one-shot" container that *doesn't* get restarted? - We could use `kubectl run --restart=OnFailure` or `kubectl run --restart=Never` - These commands would create *jobs* or *pods* instead of *deployments* - Under the hood, `kubectl run` invokes "generators" to create resource descriptions - We could also write these resource descriptions ourselves (typically in YAML),
and create them on the cluster with `kubectl apply -f` (discussed later) - With `kubectl run --schedule=...`, we can also create *cronjobs* --- ## Viewing logs of multiple pods - When we specify a deployment name, only one single pod's logs are shown - We can view the logs of multiple pods by specifying a *selector* - A selector is a logic expression using *labels* - Conveniently, when you `kubectl run somename`, the associated objects have a `run=somename` label .exercise[ - View the last line of log from all pods with the `run=pingpong` label: ```bash kubectl logs -l run=pingpong --tail 1 ``` ] Unfortunately, `--follow` cannot (yet) be used to stream the logs from multiple containers. --- class: title .small[ Meanwhile, at the Google NOC ... .small[ Why the hell
are we getting 1000 packets per second
of ICMP ECHO traffic from EC2 ?!? ] ]