Difficulty: Intermediate
Estimated Time: 45-60 minutes

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Welcome to the Digital Academy's "Kubernetes Fundamentals 1" series. This is Module 4 - Introduction to Deployments

In this lab, we will explain the concept of ReplicaSets, Deployments, and have us create multiple Deployments using different strategies.

For more information, see the Kubernetes documentation.

Developer(s): William Hearn and Zachary Seguin

Now with the understanding of Deployments in hand we now have the requisite knowledge of how to configure and deploy applications in Kubernetes.

However, there are still more effective strategies that we can leverage.

Module 4: Kubernetes Deployments

Step 1 of 7


Before we work with Deployments, we'll go over the basics of ReplicaSets. A ReplicaSet will ensure that the desired number of replicas of each Pod are up and running. Any time a Pod goes down, the ReplicaSet will deploy a new one to maintain high availability.

Now inspect the file cat ./resources/vue-rs.yaml.

It should look familiar to the Pod resource. We do have a few additions. These additions are what configure our ReplicaSet.

The biggest additions are replicas: 3 and selector. The first component configures the total number of replicas of the Pod should be active at all times. The selector matches a set of constraints to identify Pods to represent. In this case, the ReplicaSet will track Pods with the label app=vue.

We can deploy this ReplicaSet the same way we did Pods:

kubectl create -f ./resources/vue-rs.yaml

Now watch Kubernets create 3 vue Pods based on the specification in the vue-rs.yaml file.

kubectl get po --watch

Wait for the pods to be created. You can press CTRL-C to stop watching.

Inspect the ReplicaSet.

NOTE: rs is shorthand for ReplicaSet

kubectl describe rs vue-rs

Now modify the ReplicaSet to instantiate 5 pods by changing the replicas: 3 value.

kubectl edit rs vue-rs

With edit, you can live edit the configuration of the resource in Kubernetes. However, it will not edit the underlying Manifest file representing the object.


In the last step you scaled up the vue-rs ReplicaSet to 5 pods by editing the spec file. Those changes were automatically applied.

Manual Scaling

To manually scale a ReplicaSet up or down, use the scale command. Scale the vue pods down to 2 with the command:

kubectl scale rs vue-rs --replicas=2

You can verify that 3 of the 5 vue instances have been terminated:

kubectl get pods

or watch them until they finish

kubectl get po --watch

Of course, the ideal way to do this is to update our Manifest to reflect these changes.


Kubernetes provides native autoscaling of your Pods. However, kube-scheduler might not be able to schedule additional Pods if your cluster is under high load. In addition, if you have a limited set of compute resources, autoscaling Pods can have severe consequences, unless your worker nodes can automatically scale as well (e.g. AWS autoscaling groups).

apiVersion: autoscaling/v1
kind: HorizontalPodAutoscaler
  name: frontend-scaler
    kind: ReplicaSet
    name: vue-rs
  minReplicas: 3
  maxReplicas: 10
  targetCPUUtilizationPercentage: 50

To see all the autoscale options:

kubectl autoscale --help

It is also possible to automatically generate a config file, which we've seen before. The command to output a YAML config looks like this:

kubectl autoscale rs vue-rs --max=10 --min=3 --cpu-percent=50 --dry-run=true -o=yaml

Note --dry-run=true, this means that Kubernetes will not apply the desired state changes to our cluster. However, we provided it with -o=yaml, which means output the configuration as YAML. This lets us easily generate a Manifest.

Tip --dry-run with -o=yaml is an excellent way to generate configurations!

We've provided this content in ./resources/hpa-vue.yaml.

Now actually apply the configuration: kubectl create -f ./resources/hpa-vue.yaml

At this point, we have a ReplicaSet managing the vue Pods, with Horizontal Pod Autoscaling configured. Let's clean up our environment:

kubectl delete -f ./resources/hpa-vue.yaml

kubectl delete -f ./resources/vue-rs.yaml