A deployment is a supervisor for pods, giving you fine-grained control over how and when a new pod version is rolled out as well as rolled back to a previous state.

Let’s create a deployment called sise-deploy that supervises two replicas of a pod as well as a replica set:

kubectl apply -f https://raw.githubusercontent.com/openshift-evangelists/kbe/main/specs/deployments/d09.yaml

You can have a look at the deployment, as well as the the replica set and the pods the deployment looks after like so:

kubectl get deploy
NAME          DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
sise-deploy   2         2         2            2           10s
kubectl get rs
NAME                     DESIRED   CURRENT   READY     AGE
sise-deploy-3513442901   2         2         2         19s
kubectl get pods
NAME                           READY     STATUS    RESTARTS   AGE
sise-deploy-3513442901-cndsx   1/1       Running   0          25s
sise-deploy-3513442901-sn74v   1/1       Running   0          25s

Note the naming of the pods and replica set, derived from the deployment name.

At this point in time the sise containers running in the pods are configured to return the version 0.9. Let’s verify this from within the cluster using curl:

kubectl exec sise-deploy-3513442901-sn74v -t -- curl -s 127.0.0.1:9876/info
{"host": "127.0.0.1:9876", "version": "0.9", "from": "127.0.0.1"}

Let’s now see what happens if we change that version to 1.0 in an updated deployment:

kubectl apply -f https://raw.githubusercontent.com/openshift-evangelists/kbe/main/specs/deployments/d10.yaml
deployment "sise-deploy" configured

Note that you could have used kubectl edit deploy/sise-deploy alternatively to achieve the same by manually editing the deployment.

What we now see is the rollout of two new pods with the updated version 1.0 as well as the two old pods with version 0.9 being terminated:

kubectl get pods
NAME                           READY     STATUS        RESTARTS   AGE
sise-deploy-2958877261-nfv28   1/1       Running       0          25s
sise-deploy-2958877261-w024b   1/1       Running       0          25s
sise-deploy-3513442901-cndsx   1/1       Terminating   0          16m
sise-deploy-3513442901-sn74v   1/1       Terminating   0          16m

Also, a new replica set has been created by the deployment:

kubectl get rs
NAME                     DESIRED   CURRENT   READY     AGE
sise-deploy-2958877261   2         2         2         4s
sise-deploy-3513442901   0         0         0         24m

Note that during the deployment you can check the progress using kubectl rollout status deploy/sise-deploy.

To verify that if the new 1.0 version is really available, we execute from within the cluster (again using kubectl describe get the IP of one of the pods):

kubectl exec sise-deploy-2958877261-nfv28 -t -- curl -s 127.0.0.1:9876/info
{"host": "127.0.0.1:9876", "version": "1.0", "from": "127.0.0.1"}

A history of all deployments is available via:

kubectl rollout history deploy/sise-deploy
deployments "sise-deploy"
REVISION        CHANGE-CAUSE
1               <none>
2               <none>

If there are problems in the deployment Kubernetes will automatically roll back to the previous version, however you can also explicitly roll back to a specific revision, as in our case to revision 1 (the original pod version):

kubectl rollout undo deploy/sise-deploy --to-revision=1
deployment "sise-deploy" rolled back
kubectl rollout history deploy/sise-deploy
deployments "sise-deploy"
REVISION        CHANGE-CAUSE
2               <none>
3               <none>
kubectl get pods
NAME                           READY     STATUS    RESTARTS   AGE
sise-deploy-3513442901-ng8fz   1/1       Running   0          1m
sise-deploy-3513442901-s8q4s   1/1       Running   0          1m

At this point in time we’re back at where we started, with two new pods serving again version 0.9.

Finally, to clean up, we remove the deployment and with it the replica sets and pods it supervises:

kubectl delete deploy sise-deploy
deployment "sise-deploy" deleted

See also the docs for more options on deployments and when they are triggered.

Previous | Next