# Deployments Kubernetes

Un "Deployment" est l'option la plus courante pour gérer un Pod ou un ensemble de Pods. Ceux-ci sont normalement utilisés à la place des ReplicaSets car ils sont plus flexibles. De la création d'un Deployment résulte un ReplicaSet. Un Deployment fournit des mises à jour déclarative pour les Pods et les ReplicaSets.

Vous décrivez un état désiré (desired state) dans un Deployment et celui-ci change l'état acuel vers l'état désiré.

You describe a desired state in a Deployment, and the Deployment changes the actual state to the desired state at a controlled rate. You can define Deployments to create new ReplicaSets, or to remove existing Deployments and adopt all their resources with new Deployments.

Ne gérez pas directement les ReplicaSets appartenant à un Deployment.

## Cas d'usage

Voici des cas d'usage typiques pour les déploiements :

• Créer un déploiement pour déployer un ReplicaSet. Le ReplicaSet crée des Pods en arrière-plan. Vérifier l'état du déploiement pour voir s'il réussit ou non.
• Déclarer le nouvel état des Pods en mettant à jour le PodTemplateSpec du Deployment. Un nouveau ReplicaSet est créé et le Deployment gère le déplacement des Pods de l'ancien ReplicaSet vers le nouveau à un rythme contrôlé. Chaque nouveau ReplicaSet met à jour la révision du Deployment.
• Revenir (Rollback) à une révision de Deployment précédente si l'état actuel du Deployment n'est pas stable. Chaque retour en arrière met à jour la révision du Deployment.
• Mettre à l'échelle (Scale up) du Deployment pour faciliter une plus grande charge.
• Mettez en pause le Deployment pour appliquer plusieurs correctifs à son PodTemplateSpec, puis le reprendre pour commencer un nouveau déploiement.
• Utiliser l'état du déploiement comme un indicateur qu'un déploiement est bloqué.
• Nettoyer les anciens ReplicaSets dont on n'a plus besoin.

## Création d'un Deployment

L'exemple suivant est un exemple de Deployment. Il crée un ReplicaSet pour faire apparaître trois Pods nginx :

apiVersion: apps/v1
kind: Deployment
name: nginx-deployment
labels:
app: nginx
spec:
replicas: 3
selector:
matchLabels:
app: nginx
template:
labels:
app: nginx
spec:
containers:
- name: nginx
image: nginx:1.7.9
ports:
- containerPort: 80

• Un Deployment nommé nginx-deployment est créé, indiqué par le champ .metadata.name.
• Le Deployment crée trois Pods répliqués, indiqué par le champ replicas .
• Le champ selector définit la manière dont le Deployment les Pods à gérer. Dans ce cas, on sélectionne simplement une étiquette (label) qui est définie dans le template du Pod (app: nginx).

Le champ matchLabels est une table de paires {key,value}. Une seule {clé,valeur} dans la table matchLabels. est équivalent à un élément de matchExpressions, dont le champ clé est "clé" l'opérateur est "In", et le tableau des valeurs ne contient que "value". Toutes ces exigences, qu'il s'agisse des matchLabels ou des matchExpressions', doivent être satisfaites pour qu'il y ait correspondance.

• Le champ template contient les champs inférieurs suivants :

• Les Pods sont étiquetés app: nginx en utilisant le champ labels .
• Les spécifications du modèle (template) de Pod ou le champ .template.spec indique que les pods exécutent un conteneur nginx, avec l'image nginx version 1.7.9 sur Docker Hub.
• Crée une conteneur nommé nginx en utilisant le champ name.

Follow the steps given below to create the above Deployment:

Before you begin, make sure your Kubernetes cluster is up and running.

1. Create the Deployment by running the following command:

You may specify the --record flag to write the command executed in the resource annotation kubernetes.io/change-cause. It is useful for future introspection. For example, to see the commands executed in each Deployment revision.

kubectl apply -f https://k8s.io/examples/controllers/nginx-deployment.yaml

2. Run kubectl get deployments to check if the Deployment was created. If the Deployment is still being created, the output is similar to the following:

NAME               DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
nginx-deployment   3         0         0            0           1s


When you inspect the Deployments in your cluster, the following fields are displayed:

• NAME lists the names of the Deployments in the cluster.
• DESIRED displays the desired number of replicas of the application, which you define when you create the Deployment. This is the desired state.
• CURRENT displays how many replicas are currently running.
• UP-TO-DATE displays the number of replicas that have been updated to achieve the desired state.
• AVAILABLE displays how many replicas of the application are available to your users.
• AGE displays the amount of time that the application has been running.

Notice how the number of desired replicas is 3 according to .spec.replicas field.

3. To see the Deployment rollout status, run kubectl rollout status deployment.v1.apps/nginx-deployment. The output is similar to this:

Waiting for rollout to finish: 2 out of 3 new replicas have been updated...
deployment.apps/nginx-deployment successfully rolled out

4. Run the kubectl get deployments again a few seconds later. The output is similar to this:

NAME               DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
nginx-deployment   3         3         3            3           18s


Notice that the Deployment has created all three replicas, and all replicas are up-to-date (they contain the latest Pod template) and available.

5. To see the ReplicaSet (rs) created by the Deployment, run kubectl get rs. The output is similar to this:

NAME                          DESIRED   CURRENT   READY   AGE
nginx-deployment-75675f5897   3         3         3       18s


Notice that the name of the ReplicaSet is always formatted as [DEPLOYMENT-NAME]-[RANDOM-STRING]. The random string is randomly generated and uses the pod-template-hash as a seed.

6. To see the labels automatically generated for each Pod, run kubectl get pods --show-labels. The following output is returned:

NAME                                READY     STATUS    RESTARTS   AGE       LABELS
nginx-deployment-75675f5897-7ci7o   1/1       Running   0          18s       app=nginx,pod-template-hash=3123191453
nginx-deployment-75675f5897-kzszj   1/1       Running   0          18s       app=nginx,pod-template-hash=3123191453
nginx-deployment-75675f5897-qqcnn   1/1       Running   0          18s       app=nginx,pod-template-hash=3123191453


The created ReplicaSet ensures that there are three nginx Pods.

You must specify an appropriate selector and Pod template labels in a Deployment (in this case, app: nginx). Do not overlap labels or selectors with other controllers (including other Deployments and StatefulSets). Kubernetes doesn't stop you from overlapping, and if multiple controllers have overlapping selectors those controllers might conflict and behave unexpectedly.

### Pod-template-hash label

Do not change this label.

The pod-template-hash label is added by the Deployment controller to every ReplicaSet that a Deployment creates or adopts.

This label ensures that child ReplicaSets of a Deployment do not overlap. It is generated by hashing the PodTemplate of the ReplicaSet and using the resulting hash as the label value that is added to the ReplicaSet selector, Pod template labels, and in any existing Pods that the ReplicaSet might have.

## Updating a Deployment

A Deployment's rollout is triggered if and only if the Deployment's Pod template (that is, .spec.template) is changed, for example if the labels or container images of the template are updated. Other updates, such as scaling the Deployment, do not trigger a rollout.

1. Let's update the nginx Pods to use the nginx:1.9.1 image instead of the nginx:1.7.9 image.

 kubectl --record deployment.apps/nginx-deployment set image deployment.v1.apps/nginx-deployment nginx=nginx:1.9.1


or simply use the following command:

 kubectl set image deployment/nginx-deployment nginx=nginx:1.9.1 --record


The output is similar to this:

 deployment.apps/nginx-deployment image updated


Alternatively, you can edit the Deployment and change .spec.template.spec.containers[0].image from nginx:1.7.9 to nginx:1.9.1:

 kubectl edit deployment.v1.apps/nginx-deployment


The output is similar to this:

 deployment.apps/nginx-deployment edited

2. To see the rollout status, run:

 kubectl rollout status deployment.v1.apps/nginx-deployment


The output is similar to this:

 Waiting for rollout to finish: 2 out of 3 new replicas have been updated...


or

 deployment.apps/nginx-deployment successfully rolled out


Get more details on your updated Deployment:

• After the rollout succeeds, you can view the Deployment by running kubectl get deployments. The output is similar to this:

  NAME               DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
nginx-deployment   3         3         3            3           36s

• Run kubectl get rs to see that the Deployment updated the Pods by creating a new ReplicaSet and scaling it up to 3 replicas, as well as scaling down the old ReplicaSet to 0 replicas.

  kubectl get rs


The output is similar to this:

  NAME                          DESIRED   CURRENT   READY   AGE
nginx-deployment-1564180365   3         3         3       6s
nginx-deployment-2035384211   0         0         0       36s

• Running get pods should now show only the new Pods:

  kubectl get pods


The output is similar to this:

  NAME                                READY     STATUS    RESTARTS   AGE
nginx-deployment-1564180365-khku8   1/1       Running   0          14s
nginx-deployment-1564180365-nacti   1/1       Running   0          14s
nginx-deployment-1564180365-z9gth   1/1       Running   0          14s


Next time you want to update these Pods, you only need to update the Deployment's Pod template again.

Deployment ensures that only a certain number of Pods are down while they are being updated. By default, it ensures that at least 75% of the desired number of Pods are up (25% max unavailable).

Deployment also ensures that only a certain number of Pods are created above the desired number of Pods. By default, it ensures that at most 125% of the desired number of Pods are up (25% max surge).

For example, if you look at the above Deployment closely, you will see that it first created a new Pod, then deleted some old Pods, and created new ones. It does not kill old Pods until a sufficient number of new Pods have come up, and does not create new Pods until a sufficient number of old Pods have been killed. It makes sure that at least 2 Pods are available and that at max 4 Pods in total are available.

• Get details of your Deployment:

kubectl describe deployments


The output is similar to this:

Name:                   nginx-deployment
Namespace:              default
CreationTimestamp:      Thu, 30 Nov 2017 10:56:25 +0000
Labels:                 app=nginx
Annotations:            deployment.kubernetes.io/revision=2
Selector:               app=nginx
Replicas:               3 desired | 3 updated | 3 total | 3 available | 0 unavailable
StrategyType:           RollingUpdate
RollingUpdateStrategy:  25% max unavailable, 25% max surge
Pod Template:
Labels:  app=nginx
Containers:
nginx:
Image:        nginx:1.9.1
Port:         80/TCP
Environment:  <none>
Mounts:       <none>
Volumes:        <none>
Conditions:
Type           Status  Reason
----           ------  ------
Available      True    MinimumReplicasAvailable
Progressing    True    NewReplicaSetAvailable
OldReplicaSets:  <none>
NewReplicaSet:   nginx-deployment-1564180365 (3/3 replicas created)
Events:
Type    Reason             Age   From                   Message
----    ------             ----  ----                   -------
Normal  ScalingReplicaSet  2m    deployment-controller  Scaled up replica set nginx-deployment-2035384211 to 3
Normal  ScalingReplicaSet  24s   deployment-controller  Scaled up replica set nginx-deployment-1564180365 to 1
Normal  ScalingReplicaSet  22s   deployment-controller  Scaled down replica set nginx-deployment-2035384211 to 2
Normal  ScalingReplicaSet  22s   deployment-controller  Scaled up replica set nginx-deployment-1564180365 to 2
Normal  ScalingReplicaSet  19s   deployment-controller  Scaled down replica set nginx-deployment-2035384211 to 1
Normal  ScalingReplicaSet  19s   deployment-controller  Scaled up replica set nginx-deployment-1564180365 to 3
Normal  ScalingReplicaSet  14s   deployment-controller  Scaled down replica set nginx-deployment-2035384211 to 0


Here you see that when you first created the Deployment, it created a ReplicaSet (nginx-deployment-2035384211) and scaled it up to 3 replicas directly. When you updated the Deployment, it created a new ReplicaSet (nginx-deployment-1564180365) and scaled it up to 1 and then scaled down the old ReplicaSet to 2, so that at least 2 Pods were available and at most 4 Pods were created at all times. It then continued scaling up and down the new and the old ReplicaSet, with the same rolling update strategy. Finally, you'll have 3 available replicas in the new ReplicaSet, and the old ReplicaSet is scaled down to 0.

### Rollover (aka multiple updates in-flight)

Each time a new Deployment is observed by the Deployment controller, a ReplicaSet is created to bring up the desired Pods. If the Deployment is updated, the existing ReplicaSet that controls Pods whose labels match .spec.selector but whose template does not match .spec.template are scaled down. Eventually, the new ReplicaSet is scaled to .spec.replicas and all old ReplicaSets is scaled to 0.

If you update a Deployment while an existing rollout is in progress, the Deployment creates a new ReplicaSet as per the update and start scaling that up, and rolls over the ReplicaSet that it was scaling up previously -- it will add it to its list of old ReplicaSets and start scaling it down.

For example, suppose you create a Deployment to create 5 replicas of nginx:1.7.9, but then update the Deployment to create 5 replicas of nginx:1.9.1, when only 3 replicas of nginx:1.7.9 had been created. In that case, the Deployment immediately starts killing the 3 nginx:1.7.9 Pods that it had created, and starts creating nginx:1.9.1 Pods. It does not wait for the 5 replicas of nginx:1.7.9 to be created before changing course.

It is generally discouraged to make label selector updates and it is suggested to plan your selectors up front. In any case, if you need to perform a label selector update, exercise great caution and make sure you have grasped all of the implications.

In API version apps/v1, a Deployment's label selector is immutable after it gets created.

• Selector additions require the Pod template labels in the Deployment spec to be updated with the new label too, otherwise a validation error is returned. This change is a non-overlapping one, meaning that the new selector does not select ReplicaSets and Pods created with the old selector, resulting in orphaning all old ReplicaSets and creating a new ReplicaSet.
• Selector updates changes the existing value in a selector key -- result in the same behavior as additions.
• Selector removals removes an existing key from the Deployment selector -- do not require any changes in the Pod template labels. Existing ReplicaSets are not orphaned, and a new ReplicaSet is not created, but note that the removed label still exists in any existing Pods and ReplicaSets.

## Rolling Back a Deployment

Sometimes, you may want to rollback a Deployment; for example, when the Deployment is not stable, such as crash looping. By default, all of the Deployment's rollout history is kept in the system so that you can rollback anytime you want (you can change that by modifying revision history limit).

A Deployment's revision is created when a Deployment's rollout is triggered. This means that the new revision is created if and only if the Deployment's Pod template (.spec.template) is changed, for example if you update the labels or container images of the template. Other updates, such as scaling the Deployment, do not create a Deployment revision, so that you can facilitate simultaneous manual- or auto-scaling. This means that when you roll back to an earlier revision, only the Deployment's Pod template part is rolled back.

• Suppose that you made a typo while updating the Deployment, by putting the image name as nginx:1.91 instead of nginx:1.9.1:

  kubectl set image deployment.v1.apps/nginx-deployment nginx=nginx:1.91 --record=true


The output is similar to this:

  deployment.apps/nginx-deployment image updated

• The rollout gets stuck. You can verify it by checking the rollout status:

  kubectl rollout status deployment.v1.apps/nginx-deployment


The output is similar to this:

  Waiting for rollout to finish: 1 out of 3 new replicas have been updated...

• Press Ctrl-C to stop the above rollout status watch. For more information on stuck rollouts, read more here.

• You see that the number of old replicas (nginx-deployment-1564180365 and nginx-deployment-2035384211) is 2, and new replicas (nginx-deployment-3066724191) is 1.

  kubectl get rs


The output is similar to this:

  NAME                          DESIRED   CURRENT   READY   AGE
nginx-deployment-1564180365   3         3         3       25s
nginx-deployment-2035384211   0         0         0       36s
nginx-deployment-3066724191   1         1         0       6s

• Looking at the Pods created, you see that 1 Pod created by new ReplicaSet is stuck in an image pull loop.

  kubectl get pods


The output is similar to this:

  NAME                                READY     STATUS             RESTARTS   AGE
nginx-deployment-1564180365-70iae   1/1       Running            0          25s
nginx-deployment-1564180365-jbqqo   1/1       Running            0          25s
nginx-deployment-1564180365-hysrc   1/1       Running            0          25s
nginx-deployment-3066724191-08mng   0/1       ImagePullBackOff   0          6s


The Deployment controller stops the bad rollout automatically, and stops scaling up the new ReplicaSet. This depends on the rollingUpdate parameters (maxUnavailable specifically) that you have specified. Kubernetes by default sets the value to 25%.

• Get the description of the Deployment:

  kubectl describe deployment


The output is similar to this:

  Name:           nginx-deployment
Namespace:      default
CreationTimestamp:  Tue, 15 Mar 2016 14:48:04 -0700
Labels:         app=nginx
Selector:       app=nginx
Replicas:       3 desired | 1 updated | 4 total | 3 available | 1 unavailable
StrategyType:       RollingUpdate
RollingUpdateStrategy:  25% max unavailable, 25% max surge
Pod Template:
Labels:  app=nginx
Containers:
nginx:
Image:        nginx:1.91
Port:         80/TCP
Host Port:    0/TCP
Environment:  <none>
Mounts:       <none>
Volumes:        <none>
Conditions:
Type           Status  Reason
----           ------  ------
Available      True    MinimumReplicasAvailable
Progressing    True    ReplicaSetUpdated
OldReplicaSets:     nginx-deployment-1564180365 (3/3 replicas created)
NewReplicaSet:      nginx-deployment-3066724191 (1/1 replicas created)
Events:
FirstSeen LastSeen    Count   From                    SubobjectPath   Type        Reason              Message
--------- --------    -----   ----                    -------------   --------    ------              -------
1m        1m          1       {deployment-controller }                Normal      ScalingReplicaSet   Scaled up replica set nginx-deployment-2035384211 to 3
22s       22s         1       {deployment-controller }                Normal      ScalingReplicaSet   Scaled up replica set nginx-deployment-1564180365 to 1
22s       22s         1       {deployment-controller }                Normal      ScalingReplicaSet   Scaled down replica set nginx-deployment-2035384211 to 2
22s       22s         1       {deployment-controller }                Normal      ScalingReplicaSet   Scaled up replica set nginx-deployment-1564180365 to 2
21s       21s         1       {deployment-controller }                Normal      ScalingReplicaSet   Scaled down replica set nginx-deployment-2035384211 to 1
21s       21s         1       {deployment-controller }                Normal      ScalingReplicaSet   Scaled up replica set nginx-deployment-1564180365 to 3
13s       13s         1       {deployment-controller }                Normal      ScalingReplicaSet   Scaled down replica set nginx-deployment-2035384211 to 0
13s       13s         1       {deployment-controller }                Normal      ScalingReplicaSet   Scaled up replica set nginx-deployment-3066724191 to 1


To fix this, you need to rollback to a previous revision of Deployment that is stable.

### Checking Rollout History of a Deployment

Follow the steps given below to check the rollout history:

1. First, check the revisions of this Deployment:

 kubectl rollout history deployment.v1.apps/nginx-deployment


The output is similar to this:

 deployments "nginx-deployment"
REVISION    CHANGE-CAUSE
1           kubectl apply --filename=https://k8s.io/examples/controllers/nginx-deployment.yaml --record=true
2           kubectl set image deployment.v1.apps/nginx-deployment nginx=nginx:1.9.1 --record=true
3           kubectl set image deployment.v1.apps/nginx-deployment nginx=nginx:1.91 --record=true


CHANGE-CAUSE is copied from the Deployment annotation kubernetes.io/change-cause to its revisions upon creation. You can specify theCHANGE-CAUSE message by:

• Annotating the Deployment with kubectl annotate deployment.v1.apps/nginx-deployment kubernetes.io/change-cause="image updated to 1.9.1"
• Append the --record flag to save the kubectl command that is making changes to the resource.
• Manually editing the manifest of the resource.
2. To see the details of each revision, run:

 kubectl rollout history deployment.v1.apps/nginx-deployment --revision=2


The output is similar to this:

 deployments "nginx-deployment" revision 2
Labels:       app=nginx
pod-template-hash=1159050644
Annotations:  kubernetes.io/change-cause=kubectl set image deployment.v1.apps/nginx-deployment nginx=nginx:1.9.1 --record=true
Containers:
nginx:
Image:      nginx:1.9.1
Port:       80/TCP
QoS Tier:
cpu:      BestEffort
memory:   BestEffort
Environment Variables:      <none>
No volumes.


### Rolling Back to a Previous Revision

Follow the steps given below to rollback the Deployment from the current version to the previous version, which is version 2.

1. Now you've decided to undo the current rollout and rollback to the previous revision:

 kubectl rollout undo deployment.v1.apps/nginx-deployment


The output is similar to this:

 deployment.apps/nginx-deployment


Alternatively, you can rollback to a specific revision by specifying it with --to-revision:

 kubectl rollout undo deployment.v1.apps/nginx-deployment --to-revision=2


The output is similar to this:

 deployment.apps/nginx-deployment


For more details about rollout related commands, read kubectl rollout.

The Deployment is now rolled back to a previous stable revision. As you can see, a DeploymentRollback event for rolling back to revision 2 is generated from Deployment controller.

2. Check if the rollback was successful and the Deployment is running as expected, run:

 kubectl get deployment nginx-deployment


The output is similar to this:

 NAME               DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
nginx-deployment   3         3         3            3           30m

3. Get the description of the Deployment:
 kubectl describe deployment nginx-deployment

The output is similar to this:
 Name:                   nginx-deployment
Namespace:              default
CreationTimestamp:      Sun, 02 Sep 2018 18:17:55 -0500
Labels:                 app=nginx
Annotations:            deployment.kubernetes.io/revision=4
kubernetes.io/change-cause=kubectl set image deployment.v1.apps/nginx-deployment nginx=nginx:1.9.1 --record=true
Selector:               app=nginx
Replicas:               3 desired | 3 updated | 3 total | 3 available | 0 unavailable
StrategyType:           RollingUpdate
RollingUpdateStrategy:  25% max unavailable, 25% max surge
Pod Template:
Labels:  app=nginx
Containers:
nginx:
Image:        nginx:1.9.1
Port:         80/TCP
Host Port:    0/TCP
Environment:  <none>
Mounts:       <none>
Volumes:        <none>
Conditions:
Type           Status  Reason
----           ------  ------
Available      True    MinimumReplicasAvailable
Progressing    True    NewReplicaSetAvailable
OldReplicaSets:  <none>
NewReplicaSet:   nginx-deployment-c4747d96c (3/3 replicas created)
Events:
Type    Reason              Age   From                   Message
----    ------              ----  ----                   -------
Normal  ScalingReplicaSet   12m   deployment-controller  Scaled up replica set nginx-deployment-75675f5897 to 3
Normal  ScalingReplicaSet   11m   deployment-controller  Scaled up replica set nginx-deployment-c4747d96c to 1
Normal  ScalingReplicaSet   11m   deployment-controller  Scaled down replica set nginx-deployment-75675f5897 to 2
Normal  ScalingReplicaSet   11m   deployment-controller  Scaled up replica set nginx-deployment-c4747d96c to 2
Normal  ScalingReplicaSet   11m   deployment-controller  Scaled down replica set nginx-deployment-75675f5897 to 1
Normal  ScalingReplicaSet   11m   deployment-controller  Scaled up replica set nginx-deployment-c4747d96c to 3
Normal  ScalingReplicaSet   11m   deployment-controller  Scaled down replica set nginx-deployment-75675f5897 to 0
Normal  ScalingReplicaSet   11m   deployment-controller  Scaled up replica set nginx-deployment-595696685f to 1
Normal  DeploymentRollback  15s   deployment-controller  Rolled back deployment "nginx-deployment" to revision 2
Normal  ScalingReplicaSet   15s   deployment-controller  Scaled down replica set nginx-deployment-595696685f to 0


## Scaling a Deployment

You can scale a Deployment by using the following command:

kubectl scale deployment.v1.apps/nginx-deployment --replicas=10


The output is similar to this:

deployment.apps/nginx-deployment scaled


Assuming horizontal Pod autoscaling is enabled in your cluster, you can setup an autoscaler for your Deployment and choose the minimum and maximum number of Pods you want to run based on the CPU utilization of your existing Pods.

kubectl autoscale deployment.v1.apps/nginx-deployment --min=10 --max=15 --cpu-percent=80


The output is similar to this:

deployment.apps/nginx-deployment scaled


### Proportional scaling

RollingUpdate Deployments support running multiple versions of an application at the same time. When you or an autoscaler scales a RollingUpdate Deployment that is in the middle of a rollout (either in progress or paused), the Deployment controller balances the additional replicas in the existing active ReplicaSets (ReplicaSets with Pods) in order to mitigate risk. This is called proportional scaling.

For example, you are running a Deployment with 10 replicas, maxSurge=3, and maxUnavailable=2.

• Ensure that the 10 replicas in your Deployment are running.

kubectl get deploy


The output is similar to this:

NAME                 DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
nginx-deployment     10        10        10           10          50s

• You update to a new image which happens to be unresolvable from inside the cluster.

  kubectl set image deployment.v1.apps/nginx-deployment nginx=nginx:sometag


The output is similar to this:

  deployment.apps/nginx-deployment image updated

• The image update starts a new rollout with ReplicaSet nginx-deployment-1989198191, but it's blocked due to the maxUnavailable requirement that you mentioned above. Check out the rollout status:

  kubectl get rs

The output is similar to this:

  NAME                          DESIRED   CURRENT   READY     AGE
nginx-deployment-1989198191   5         5         0         9s
nginx-deployment-618515232    8         8         8         1m

• Then a new scaling request for the Deployment comes along. The autoscaler increments the Deployment replicas to 15. The Deployment controller needs to decide where to add these new 5 replicas. If you weren't using proportional scaling, all 5 of them would be added in the new ReplicaSet. With proportional scaling, you spread the additional replicas across all ReplicaSets. Bigger proportions go to the ReplicaSets with the most replicas and lower proportions go to ReplicaSets with less replicas. Any leftovers are added to the ReplicaSet with the most replicas. ReplicaSets with zero replicas are not scaled up.

In our example above, 3 replicas are added to the old ReplicaSet and 2 replicas are added to the new ReplicaSet. The rollout process should eventually move all replicas to the new ReplicaSet, assuming the new replicas become healthy. To confirm this, run:

kubectl get deploy


The output is similar to this:

NAME                 DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
nginx-deployment     15        18        7            8           7m


The rollout status confirms how the replicas were added to each ReplicaSet.

kubectl get rs


The output is similar to this:

NAME                          DESIRED   CURRENT   READY     AGE
nginx-deployment-1989198191   7         7         0         7m
nginx-deployment-618515232    11        11        11        7m


## Pausing and Resuming a Deployment

You can pause a Deployment before triggering one or more updates and then resume it. This allows you to apply multiple fixes in between pausing and resuming without triggering unnecessary rollouts.

• For example, with a Deployment that was just created: Get the Deployment details:

kubectl get deploy


The output is similar to this:

NAME      DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
nginx     3         3         3            3           1m


Get the rollout status:

kubectl get rs


The output is similar to this:

NAME               DESIRED   CURRENT   READY     AGE
nginx-2142116321   3         3         3         1m

• Pause by running the following command:

  kubectl rollout pause deployment.v1.apps/nginx-deployment


The output is similar to this:

  deployment.apps/nginx-deployment paused

• Then update the image of the Deployment:

  kubectl set image deployment.v1.apps/nginx-deployment nginx=nginx:1.9.1


The output is similar to this:

  deployment.apps/nginx-deployment image updated

• Notice that no new rollout started:

  kubectl rollout history deployment.v1.apps/nginx-deployment


The output is similar to this:

  deployments "nginx"
REVISION  CHANGE-CAUSE
1   <none>

• Get the rollout status to ensure that the Deployment is updates successfully:

  kubectl get rs


The output is similar to this:

  NAME               DESIRED   CURRENT   READY     AGE
nginx-2142116321   3         3         3         2m

• You can make as many updates as you wish, for example, update the resources that will be used:

  kubectl set resources deployment.v1.apps/nginx-deployment -c=nginx --limits=cpu=200m,memory=512Mi


The output is similar to this:

  deployment.apps/nginx-deployment resource requirements updated


The initial state of the Deployment prior to pausing it will continue its function, but new updates to the Deployment will not have any effect as long as the Deployment is paused.

• Eventually, resume the Deployment and observe a new ReplicaSet coming up with all the new updates:

  kubectl rollout resume deployment.v1.apps/nginx-deployment


The output is similar to this:

  deployment.apps/nginx-deployment resumed

• Watch the status of the rollout until it's done.

  kubectl get rs -w


The output is similar to this:

  NAME               DESIRED   CURRENT   READY     AGE
nginx-2142116321   2         2         2         2m
nginx-3926361531   2         2         0         6s
nginx-3926361531   2         2         1         18s
nginx-2142116321   1         2         2         2m
nginx-2142116321   1         2         2         2m
nginx-3926361531   3         2         1         18s
nginx-3926361531   3         2         1         18s
nginx-2142116321   1         1         1         2m
nginx-3926361531   3         3         1         18s
nginx-3926361531   3         3         2         19s
nginx-2142116321   0         1         1         2m
nginx-2142116321   0         1         1         2m
nginx-2142116321   0         0         0         2m
nginx-3926361531   3         3         3         20s

• Get the status of the latest rollout:

  kubectl get rs


The output is similar to this:

  NAME               DESIRED   CURRENT   READY     AGE
nginx-2142116321   0         0         0         2m
nginx-3926361531   3         3         3         28s


You cannot rollback a paused Deployment until you resume it.

## Deployment status

A Deployment enters various states during its lifecycle. It can be progressing while rolling out a new ReplicaSet, it can be complete, or it can fail to progress.

### Progressing Deployment

Kubernetes marks a Deployment as progressing when one of the following tasks is performed:

• The Deployment creates a new ReplicaSet.
• The Deployment is scaling up its newest ReplicaSet.
• The Deployment is scaling down its older ReplicaSet(s).

You can monitor the progress for a Deployment by using kubectl rollout status.

### Complete Deployment

Kubernetes marks a Deployment as complete when it has the following characteristics:

• All of the replicas associated with the Deployment have been updated to the latest version you've specified, meaning any updates you've requested have been completed.
• All of the replicas associated with the Deployment are available.
• No old replicas for the Deployment are running.

You can check if a Deployment has completed by using kubectl rollout status. If the rollout completed successfully, kubectl rollout status returns a zero exit code.

kubectl rollout status deployment.v1.apps/nginx-deployment


The output is similar to this:

Waiting for rollout to finish: 2 of 3 updated replicas are available...
deployment.apps/nginx-deployment successfully rolled out
$echo$?
0


### Failed Deployment

Your Deployment may get stuck trying to deploy its newest ReplicaSet without ever completing. This can occur due to some of the following factors:

• Insufficient quota
• Image pull errors
• Insufficient permissions
• Limit ranges
• Application runtime misconfiguration

One way you can detect this condition is to specify a deadline parameter in your Deployment spec: (.spec.progressDeadlineSeconds). .spec.progressDeadlineSeconds denotes the number of seconds the Deployment controller waits before indicating (in the Deployment status) that the Deployment progress has stalled.

The following kubectl command sets the spec with progressDeadlineSeconds to make the controller report lack of progress for a Deployment after 10 minutes:

kubectl patch deployment.v1.apps/nginx-deployment -p '{"spec":{"progressDeadlineSeconds":600}}'


The output is similar to this:

deployment.apps/nginx-deployment patched


Once the deadline has been exceeded, the Deployment controller adds a DeploymentCondition with the following attributes to the Deployment's .status.conditions:

• Type=Progressing
• Status=False

Kubernetes takes no action on a stalled Deployment other than to report a status condition with Reason=ProgressDeadlineExceeded. Higher level orchestrators can take advantage of it and act accordingly, for example, rollback the Deployment to its previous version.

If you pause a Deployment, Kubernetes does not check progress against your specified deadline. You can safely pause a Deployment in the middle of a rollout and resume without triggering the condition for exceeding the deadline.

You may experience transient errors with your Deployments, either due to a low timeout that you have set or due to any other kind of error that can be treated as transient. For example, let's suppose you have insufficient quota. If you describe the Deployment you will notice the following section:

kubectl describe deployment nginx-deployment


The output is similar to this:

<...>
Conditions:
Type            Status  Reason
----            ------  ------
Available       True    MinimumReplicasAvailable
Progressing     True    ReplicaSetUpdated
ReplicaFailure  True    FailedCreate
<...>


If you run kubectl get deployment nginx-deployment -o yaml, the Deployment status is similar to this:

status:
availableReplicas: 2
conditions:
- lastTransitionTime: 2016-10-04T12:25:39Z
lastUpdateTime: 2016-10-04T12:25:39Z
message: Replica set "nginx-deployment-4262182780" is progressing.
reason: ReplicaSetUpdated
status: "True"
type: Progressing
- lastTransitionTime: 2016-10-04T12:25:42Z
lastUpdateTime: 2016-10-04T12:25:42Z
message: Deployment has minimum availability.
reason: MinimumReplicasAvailable
status: "True"
type: Available
- lastTransitionTime: 2016-10-04T12:25:39Z
lastUpdateTime: 2016-10-04T12:25:39Z
message: 'Error creating: pods "nginx-deployment-4262182780-" is forbidden: exceeded quota:
object-counts, requested: pods=1, used: pods=3, limited: pods=2'
reason: FailedCreate
status: "True"
type: ReplicaFailure
observedGeneration: 3
replicas: 2
unavailableReplicas: 2


Eventually, once the Deployment progress deadline is exceeded, Kubernetes updates the status and the reason for the Progressing condition:

Conditions:
Type            Status  Reason
----            ------  ------
Available       True    MinimumReplicasAvailable
ReplicaFailure  True    FailedCreate


You can address an issue of insufficient quota by scaling down your Deployment, by scaling down other controllers you may be running, or by increasing quota in your namespace. If you satisfy the quota conditions and the Deployment controller then completes the Deployment rollout, you'll see the Deployment's status update with a successful condition (Status=True and Reason=NewReplicaSetAvailable).

Conditions:
Type          Status  Reason
----          ------  ------
Available     True    MinimumReplicasAvailable
Progressing   True    NewReplicaSetAvailable


Type=Available with Status=True means that your Deployment has minimum availability. Minimum availability is dictated by the parameters specified in the deployment strategy. Type=Progressing with Status=True means that your Deployment is either in the middle of a rollout and it is progressing or that it has successfully completed its progress and the minimum required new replicas are available (see the Reason of the condition for the particulars - in our case Reason=NewReplicaSetAvailable means that the Deployment is complete).

You can check if a Deployment has failed to progress by using kubectl rollout status. kubectl rollout status returns a non-zero exit code if the Deployment has exceeded the progression deadline.

kubectl rollout status deployment.v1.apps/nginx-deployment


The output is similar to this:

Waiting for rollout to finish: 2 out of 3 new replicas have been updated...
error: deployment "nginx" exceeded its progress deadline
$echo$?
1


### Operating on a failed deployment

All actions that apply to a complete Deployment also apply to a failed Deployment. You can scale it up/down, roll back to a previous revision, or even pause it if you need to apply multiple tweaks in the Deployment Pod template.

## Clean up Policy

You can set .spec.revisionHistoryLimit field in a Deployment to specify how many old ReplicaSets for this Deployment you want to retain. The rest will be garbage-collected in the background. By default, it is 10.

Explicitly setting this field to 0, will result in cleaning up all the history of your Deployment thus that Deployment will not be able to roll back.

## Canary Deployment

If you want to roll out releases to a subset of users or servers using the Deployment, you can create multiple Deployments, one for each release, following the canary pattern described in managing resources.

## Writing a Deployment Spec

As with all other Kubernetes configs, a Deployment needs apiVersion, kind, and metadata fields. For general information about working with config files, see deploying applications, configuring containers, and using kubectl to manage resources documents.

A Deployment also needs a .spec section.

### Pod Template

The .spec.template and .spec.selector are the only required field of the .spec.

The .spec.template is a Pod template. It has exactly the same schema as a Pod, except it is nested and does not have an apiVersion or kind.

In addition to required fields for a Pod, a Pod template in a Deployment must specify appropriate labels and an appropriate restart policy. For labels, make sure not to overlap with other controllers. See selector).

Only a .spec.template.spec.restartPolicy equal to Always is allowed, which is the default if not specified.

### Replicas

.spec.replicas is an optional field that specifies the number of desired Pods. It defaults to 1.

### Selector

.spec.selector is an required field that specifies a label selector for the Pods targeted by this Deployment.

.spec.selector must match .spec.template.metadata.labels, or it will be rejected by the API.

In API version apps/v1, .spec.selector and .metadata.labels do not default to .spec.template.metadata.labels if not set. So they must be set explicitly. Also note that .spec.selector is immutable after creation of the Deployment in apps/v1.

A Deployment may terminate Pods whose labels match the selector if their template is different from .spec.template or if the total number of such Pods exceeds .spec.replicas. It brings up new Pods with .spec.template if the number of Pods is less than the desired number.

You should not create other Pods whose labels match this selector, either directly, by creating another Deployment, or by creating another controller such as a ReplicaSet or a ReplicationController. If you do so, the first Deployment thinks that it created these other Pods. Kubernetes does not stop you from doing this.

If you have multiple controllers that have overlapping selectors, the controllers will fight with each other and won't behave correctly.

### Strategy

.spec.strategy specifies the strategy used to replace old Pods by new ones. .spec.strategy.type can be "Recreate" or "RollingUpdate". "RollingUpdate" is the default value.

#### Recreate Deployment

All existing Pods are killed before new ones are created when .spec.strategy.type==Recreate.

#### Rolling Update Deployment

The Deployment updates Pods in a rolling update fashion when .spec.strategy.type==RollingUpdate. You can specify maxUnavailable and maxSurge to control the rolling update process.

##### Max Unavailable

.spec.strategy.rollingUpdate.maxUnavailable is an optional field that specifies the maximum number of Pods that can be unavailable during the update process. The value can be an absolute number (for example, 5) or a percentage of desired Pods (for example, 10%). The absolute number is calculated from percentage by rounding down. The value cannot be 0 if .spec.strategy.rollingUpdate.maxSurge is 0. The default value is 25%.

For example, when this value is set to 30%, the old ReplicaSet can be scaled down to 70% of desired Pods immediately when the rolling update starts. Once new Pods are ready, old ReplicaSet can be scaled down further, followed by scaling up the new ReplicaSet, ensuring that the total number of Pods available at all times during the update is at least 70% of the desired Pods.

##### Max Surge

.spec.strategy.rollingUpdate.maxSurge is an optional field that specifies the maximum number of Pods that can be created over the desired number of Pods. The value can be an absolute number (for example, 5) or a percentage of desired Pods (for example, 10%). The value cannot be 0 if MaxUnavailable is 0. The absolute number is calculated from the percentage by rounding up. The default value is 25%.

For example, when this value is set to 30%, the new ReplicaSet can be scaled up immediately when the rolling update starts, such that the total number of old and new Pods does not exceed 130% of desired Pods. Once old Pods have been killed, the new ReplicaSet can be scaled up further, ensuring that the total number of Pods running at any time during the update is at most 130% of desired Pods.

.spec.progressDeadlineSeconds is an optional field that specifies the number of seconds you want to wait for your Deployment to progress before the system reports back that the Deployment has failed progressing - surfaced as a condition with Type=Progressing, Status=False. and Reason=ProgressDeadlineExceeded in the status of the resource. The Deployment controller will keep retrying the Deployment. In the future, once automatic rollback will be implemented, the Deployment controller will roll back a Deployment as soon as it observes such a condition.

If specified, this field needs to be greater than .spec.minReadySeconds.

.spec.minReadySeconds is an optional field that specifies the minimum number of seconds for which a newly created Pod should be ready without any of its containers crashing, for it to be considered available. This defaults to 0 (the Pod will be considered available as soon as it is ready). To learn more about when a Pod is considered ready, see Container Probes.

### Rollback To

Field .spec.rollbackTo has been deprecated in API versions extensions/v1beta1 and apps/v1beta1, and is no longer supported in API versions starting apps/v1beta2. Instead, kubectl rollout undo as introduced in Rolling Back to a Previous Revision should be used.

### Revision History Limit

A Deployment's revision history is stored in the ReplicaSets it controls.

.spec.revisionHistoryLimit is an optional field that specifies the number of old ReplicaSets to retain to allow rollback. These old ReplicaSets consume resources in etcd and crowd the output of kubectl get rs. The configuration of each Deployment revision is stored in its ReplicaSets; therefore, once an old ReplicaSet is deleted, you lose the ability to rollback to that revision of Deployment. By default, 10 old ReplicaSets will be kept, however its ideal value depends on the frequency and stability of new Deployments.

More specifically, setting this field to zero means that all old ReplicaSets with 0 replicas will be cleaned up. In this case, a new Deployment rollout cannot be undone, since its revision history is cleaned up.

### Paused

.spec.paused is an optional boolean field for pausing and resuming a Deployment. The only difference between a paused Deployment and one that is not paused, is that any changes into the PodTemplateSpec of the paused Deployment will not trigger new rollouts as long as it is paused. A Deployment is not paused by default when it is created.

## Alternative to Deployments

### kubectl rolling update

kubectl rolling update` updates Pods and ReplicationControllers in a similar fashion. But Deployments are recommended, since they are declarative, server side, and have additional features, such as rolling back to any previous revision even after the rolling update is done.