guide-kubernetes-intro

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// INSTRUCTION: Please remove all comments that start INSTRUCTION prior to commit. Most comments should be removed, although not the copyright. // INSTRUCTION: The copyright statement must appear at the top of the file // // Copyright (c) 2018, 2023 IBM Corporation and others. // Licensed under Creative Commons Attribution-NoDerivatives // 4.0 International (CC BY-ND 4.0) // https://creativecommons.org/licenses/by-nd/4.0/ // // Contributors: // IBM Corporation // :projectid: kubernetes-intro :page-layout: guide-multipane :page-duration: 25 minutes :page-releasedate: 2018-10-05 :page-description: Explore how to deploy microservices to Kubernetes and manage your cluster. :page-tags: ['Kubernetes', 'Docker'] :page-permalink: /guides/{projectid} :page-related-guides: ['docker', 'istio-intro'] :common-includes: https://raw.githubusercontent.com/OpenLiberty/guides-common/prod :source-highlighter: prettify :page-seo-title: Deploying Java microservices to Kubernetes :page-seo-description: A getting started tutorial on how to deploy Java microservices in Docker containers to a Kubernetes cluster with examples of how to manage and scale the Kubernetes deployment. :guide-author: Open Liberty = Deploying microservices to Kubernetes

[.hidden] NOTE: This repository contains the guide documentation source. To view the guide in published form, view it on the https://openliberty.io/guides/{projectid}.html[Open Liberty website].

Deploy microservices in Open Liberty Docker containers to Kubernetes and manage them with the Kubernetes CLI, kubectl.

:minikube-ip: 192.168.99.100 :kube: Kubernetes :hashtag: # :win: WINDOWS :mac: MAC :linux: LINUX :system-api: http://[hostname]:31000/system/properties :inventory-api: http://[hostname]:32000/inventory/systems

// ================================================================================================= // What is {kube} // =================================================================================================

== What is {kube}?

{kube} is an open source container orchestrator that automates many tasks involved in deploying, managing, and scaling containerized applications.

Over the years, {kube} has become a major tool in containerized environments as containers are being further leveraged for all steps of a continuous delivery pipeline.

=== Why use {kube}?

Managing individual containers can be challenging. A small team can easily manage a few containers for development but managing hundreds of containers can be a headache, even for a large team of experienced developers. {kube} is a tool for deployment in containerized environments. It handles scheduling, deployment, as well as mass deletion and creation of containers. It provides update rollout abilities on a large scale that would otherwise prove extremely tedious to do. Imagine that you updated a Docker image, which now needs to propagate to a dozen containers. While you could destroy and then re-create these containers, you can also run a short one-line command to have {kube} make all those updates for you. Of course, this is just a simple example. {kube} has a lot more to offer.

=== Architecture

Deploying an application to Kubernetes means deploying an application to a Kubernetes cluster.

A typical {kube} cluster is a collection of physical or virtual machines called nodes that run containerized applications. A cluster is made up of one parent node that manages the cluster, and many worker nodes that run the actual application instances inside {kube} objects called pods.

A pod is a basic building block in a {kube} cluster. It represents a single running process that encapsulates a container or in some scenarios many closely coupled containers. Pods can be replicated to scale applications and handle more traffic. From the perspective of a cluster, a set of replicated pods is still one application instance, although it might be made up of dozens of instances of itself. A single pod or a group of replicated pods are managed by {kube} objects called controllers. A controller handles replication, self-healing, rollout of updates, and general management of pods. One example of a controller that you will use in this guide is a deployment.

A pod or a group of replicated pods are abstracted through {kube} objects called services that define a set of rules by which the pods can be accessed. In a basic scenario, a {kube} service exposes a node port that can be used together with the cluster IP address to access the pods encapsulated by the service.

To learn about the various Kubernetes resources that you can configure, see the https://kubernetes.io/docs/concepts/[official {kube} documentation^].

// ================================================================================================= // Introduction // =================================================================================================

== What you'll learn

You will learn how to deploy two microservices in Open Liberty containers to a local {kube} cluster. You will then manage your deployed microservices using the kubectl command line interface for {kube}. The kubectl CLI is your primary tool for communicating with and managing your {kube} cluster.

The two microservices you will deploy are called system and inventory. The system microservice returns the JVM system properties of the running container and it returns the pod's name in the HTTP header making replicas easy to distinguish from each other. The inventory microservice adds the properties from the system microservice to the inventory. This process demonstrates how communication can be established between pods inside a cluster.

You will use a local single-node {kube} cluster.

// ================================================================================================= // Prerequisites // ================================================================================================= [role='command'] include::{common-includes}/kube-prereq.adoc[]

// ================================================================================================= // Getting Started // ================================================================================================= [role='command'] include::{common-includes}/gitclone.adoc[]

// no "try what you'll build" section in this guide because it would be too long due to all setup the user will have to do.

// ================================================================================================= // Staring and preparing your cluster for deployment // ================================================================================================= // Static guide instruction ifndef::cloud-hosted[] [role='command'] include::{common-includes}/kube-start.adoc[] endif::[]

// ================================================================================================= // Building and containerizing the microservices // =================================================================================================

== Building and containerizing the microservices

The first step of deploying to {kube} is to build your microservices and containerize them with Docker.

The starting Java project, which you can find in the start directory, is a multi-module Maven project that's made up of the system and inventory microservices. Each microservice resides in its own directory, start/system and start/inventory. Each of these directories also contains a Dockerfile, which is necessary for building Docker images. If you're unfamiliar with Dockerfiles, check out the https://openliberty.io/guides/containerize.html[Containerizing Microservices^] guide, which covers Dockerfiles in depth.

Navigate to the start directory and build the applications by running the following commands: [role='command']

cd start
mvn clean package

Next, run the docker build commands to build container images for your application: [role='command']

docker build -t system:1.0-SNAPSHOT system/.
docker build -t inventory:1.0-SNAPSHOT inventory/.

The -t flag in the docker build command allows the Docker image to be labeled (tagged) in the name[:tag] format. The tag for an image describes the specific image version. If the optional [:tag] tag is not specified, the latest tag is created by default.

During the build, you'll see various Docker messages describing what images are being downloaded and built. When the build finishes, run the following command to list all local Docker images: [role='command']

docker images

// Static guide instruction ifndef::cloud-hosted[] Verify that the system:1.0-SNAPSHOT and inventory:1.0-SNAPSHOT images are listed among them, for example:

include::{common-includes}/os-tabs.adoc[]

[.tab_content.windows_section.mac_section]

[source, role="no_copy"]

REPOSITORY TAG inventory 1.0-SNAPSHOT system 1.0-SNAPSHOT openliberty/open-liberty kernel-slim-java11-openj9-ubi k8s.gcr.io/kube-proxy-amd64 v1.10.3 k8s.gcr.io/kube-scheduler-amd64 v1.10.3 k8s.gcr.io/kube-controller-manager-amd64 v1.10.3 k8s.gcr.io/kube-apiserver-amd64 v1.10.3 k8s.gcr.io/etcd-amd64 3.1.12 k8s.gcr.io/k8s-dns-dnsmasq-nanny-amd64 1.14.8 k8s.gcr.io/k8s-dns-sidecar-amd64 1.14.8 k8s.gcr.io/k8s-dns-kube-dns-amd64 1.14.8 k8s.gcr.io/pause-amd64 3.1

--

[.tab_content.linux_section]

[source, role="no_copy"]

REPOSITORY TAG inventory 1.0-SNAPSHOT system 1.0-SNAPSHOT openliberty/open-liberty kernel-slim-java11-openj9-ubi k8s.gcr.io/kube-proxy-amd64 v1.10.0 k8s.gcr.io/kube-controller-manager-amd64 v1.10.0 k8s.gcr.io/kube-apiserver-amd64 v1.10.0 k8s.gcr.io/kube-scheduler-amd64 v1.10.0 quay.io/kubernetes-ingress-controller/nginx-ingress-controller 0.12.0 k8s.gcr.io/etcd-amd64 3.1.12 k8s.gcr.io/kube-addon-manager v8.6 k8s.gcr.io/k8s-dns-dnsmasq-nanny-amd64 1.14.8 k8s.gcr.io/k8s-dns-sidecar-amd64 1.14.8 k8s.gcr.io/k8s-dns-kube-dns-amd64 1.14.8 k8s.gcr.io/pause-amd64 3.1 k8s.gcr.io/kubernetes-dashboard-amd64 v1.8.1 k8s.gcr.io/kube-addon-manager v6.5 gcr.io/k8s-minikube/storage-provisioner v1.8.0 gcr.io/k8s-minikube/storage-provisioner v1.8.1 k8s.gcr.io/defaultbackend 1.4 k8s.gcr.io/k8s-dns-sidecar-amd64 1.14.4 k8s.gcr.io/k8s-dns-kube-dns-amd64 1.14.4 k8s.gcr.io/k8s-dns-dnsmasq-nanny-amd64 1.14.4 k8s.gcr.io/etcd-amd64 3.0.17 k8s.gcr.io/pause-amd64 3.0

--

If you don't see the system:1.0-SNAPSHOT and inventory:1.0-SNAPSHOT images, then check the Maven build log for any potential errors. In addition, if you are using Minikube, make sure your Docker CLI is configured to use Minikube's Docker daemon instead of your host's Docker daemon. endif::[]

// Cloud hosted guide instruction ifdef::cloud-hosted[] Verify that the system:1.0-SNAPSHOT and inventory:1.0-SNAPSHOT images are listed among them, for example:

REPOSITORY                                TAG                       
inventory                                 1.0-SNAPSHOT
system                                    1.0-SNAPSHOT
openliberty/open-liberty                  kernel-slim-java11-openj9-ubi

If you don't see the system:1.0-SNAPSHOT and inventory:1.0-SNAPSHOT images, then check the Maven build log for any potential errors. If the images built without errors, push them to your container registry on IBM Cloud with the following commands:

docker tag inventory:1.0-SNAPSHOT us.icr.io/$SN_ICR_NAMESPACE/inventory:1.0-SNAPSHOT
docker tag system:1.0-SNAPSHOT us.icr.io/$SN_ICR_NAMESPACE/system:1.0-SNAPSHOT
docker push us.icr.io/$SN_ICR_NAMESPACE/inventory:1.0-SNAPSHOT
docker push us.icr.io/$SN_ICR_NAMESPACE/system:1.0-SNAPSHOT

endif::[]

// ================================================================================================= // Deploying the microservices // =================================================================================================

== Deploying the microservices

Now that your Docker images are built, deploy them using a Kubernetes resource definition.

A Kubernetes resource definition is a yaml file that contains a description of all your deployments, services, or any other resources that you want to deploy. All resources can also be deleted from the cluster by using the same yaml file that you used to deploy them.

[role="code_command hotspot", subs="quotes"]

#Create the Kubernetes configuration file in the start directory.# kubernetes.yaml

kubernetes.yaml [source, yaml, linenums, role="code_column hide_tags=rolling1,readinessProbe1,rolling2,readinessProbe2"]

include::finish/kubernetes.yaml[]

This file defines four {kube} resources. It defines two deployments and two services. A {kube} deployment is a resource that controls the creation and management of pods. A service exposes your deployment so that you can make requests to your containers. Three key items to look at when creating the deployments are the [hotspot=labels1 hotspot=labels2 hotspot=labels3 hotspot=labels4]labels, [hotspot=image1 hotspot=image2]image, and [hotspot=containerPort1 hotspot=containerPort2]containerPort fields. The [hotspot=labels1 hotspot=labels2 hotspot=labels3 hotspot=labels4]labels is a way for a {kube} service to reference specific deployments. The [hotspot=image1 hotspot=image2]image is the name and tag of the Docker image that you want to use for this container. Finally, the [hotspot=containerPort1 hotspot=containerPort2]containerPort is the port that your container exposes to access your application. For the services, the key point to understand is that they expose your deployments. The binding between deployments and services is specified by labels -- in this case the [hotspot=app1 hotspot=app2 hotspot=app3 hotspot=app4 hotspot=app5 hotspot=app6 hotspot=app7 hotspot=app8]app label. You will also notice the service has a type of [hotspot=NodePort1 hotspot=NodePort2]NodePort. This means you can access these services from outside of your cluster via a specific port. In this case, the ports are 31000 and 32000, but port numbers can also be randomized if the [hotspot=nodePort1 hotspot=nodePort2]nodePort field is not used.

// Cloud hosted guide instruction ifdef::cloud-hosted[] Update the image names so that the images in your IBM Cloud container registry are used, and remove the nodePort fields so that the ports can be generated automatically:

sed -i 's=system:1.0-SNAPSHOT=us.icr.io/'"$SN_ICR_NAMESPACE"'/system:1.0-SNAPSHOT\n        imagePullPolicy: Always=g' kubernetes.yaml
sed -i 's=inventory:1.0-SNAPSHOT=us.icr.io/'"$SN_ICR_NAMESPACE"'/inventory:1.0-SNAPSHOT\n        imagePullPolicy: Always=g' kubernetes.yaml
sed -i 's=nodePort: 31000==g' kubernetes.yaml
sed -i 's=nodePort: 32000==g' kubernetes.yaml

endif::[]

Run the following commands to deploy the resources as defined in kubernetes.yaml: [role='command']

kubectl apply -f kubernetes.yaml

When the apps are deployed, run the following command to check the status of your pods: [role='command']

kubectl get pods

You'll see an output similar to the following if all the pods are healthy and running:

[source, role="no_copy"]

NAME READY STATUS RESTARTS AGE system-deployment-6bd97d9bf6-4ccds 1/1 Running 0 15s inventory-deployment-645767664f-nbtd9 1/1 Running 0 15s

You can also inspect individual pods in more detail by running the following command: [role='command']

kubectl describe pods

You can also issue the kubectl get and kubectl describe commands on other {kube} resources, so feel free to inspect all other resources.

// Static guide instruction ifndef::cloud-hosted[] Next you will make requests to your services.

include::{common-includes}/os-tabs.adoc[]

[.tab_content.windows_section.mac_section]

The default host name for Docker Desktop is localhost.

[.tab_content.linux_section]

The default host name for minikube is {minikube-ip}. Otherwise it can be found using the minikube ip command.

Then, run the curl command or visit the following URLs to access your microservices, substituting the appropriate host name:

• {system-api}
• {inventory-api}/system-service

The first URL returns system properties and the name of the pod in an HTTP header called X-Pod-Name. To view the header, you may use the -I option in the curl when making a request to {system-api}. The second URL adds properties from the system-service endpoint to the inventory {kube} Service. Visiting {inventory-api}/[kube-service] in general adds to the inventory depending on whether kube-service is a valid {kube} service that can be accessed. endif::[]

// Cloud-hosted guide instruction ifdef::cloud-hosted[] In this execise, you need to access the services by using the Kubernetes API. Run the following command to start a proxy to the Kubernetes API server:

kubectl proxy

Open another command-line session by selecting Terminal > New Terminal from the menu of the IDE. Run the following commands to store the proxy path of the system and inventory services.

SYSTEM_PROXY=localhost:8001/api/v1/namespaces/$SN_ICR_NAMESPACE/services/system-service/proxy
INVENTORY_PROXY=localhost:8001/api/v1/namespaces/$SN_ICR_NAMESPACE/services/inventory-service/proxy

Run the following echo commands to verify the variables:

echo $SYSTEM_PROXY && echo $INVENTORY_PROXY

The output appears as shown in the following example:

localhost:8001/api/v1/namespaces/sn-labs-yourname/services/system-service/proxy
localhost:8001/api/v1/namespaces/sn-labs-yourname/services/inventory-service/proxy

Then, use the following curl command to access your system microservice:

curl -s http://$SYSTEM_PROXY/system/properties | jq

Also, use the following curl command to access your inventory microservice:

curl -s http://$INVENTORY_PROXY/inventory/systems/system-service | jq

The http://$SYSTEM_PROXY/system/properties URL returns system properties and the name of the pod in an HTTP header that is called X-Pod-Name. To view the header, you can use the -I option in the curl command when you make a request to the http://$SYSTEM_PROXY/system/properties URL.

curl -I http://$SYSTEM_PROXY/system/properties

The http://$INVENTORY_PROXY/inventory/systems/system-service URL adds properties from the system-service endpoint to the inventory {kube} Service. Making a request to the http://$INVENTORY_PROXY/inventory/systems/[kube-service] URL in general adds to the inventory. That result depends on whether the kube-service endpoint is a valid {kube} service that can be accessed. endif::[]

// ================================================================================================= // Scaling a deployment // ================================================================================================

== Rolling update

Without continuous updates, a Kubernetes cluster is susceptible to a denial of a service attack. Rolling updates continually install Kubernetes patches without disrupting the availability of the deployed applications. Update the yaml file as follows to add the rollingUpdate configuration.

[role="code_command hotspot", subs="quotes"]

#Replace the Kubernetes configuration file# kubernetes.yaml

kubernetes.yaml [source, yaml, linenums, role="code_column"]

include::finish/kubernetes.yaml[]

The [hotspot=rolling1 hotspot=rolling2]rollingUpdate configuration has two attributes, maxUnavailable and maxSurge. The [hotspot=maxUnavailable1 hotspot=maxUnavailable2]maxUnavailable attribute specifies the the maximum number of Kubernetes pods that can be unavailable during the update process. Similarly, the [hotspot=maxSurge1 hotspot=maxSurge2]maxSurge attribute specifies the maximum number of additional pods that can be created during the update process.

The [hotspot=readinessProbe1 hotspot=readinessProbe2]readinessProbe allows Kubernetes to know whether the service is ready to handle requests. The readiness health check classes for the /health/ready endpoint to the inventory and system services are provided for you. If you want to learn more about how to use health checks in Kubernetes, check out the https://openliberty.io/guides/kubernetes-microprofile-health.html[Kubernetes-microprofile-health^] guide.

ifdef::cloud-hosted[] Update the image names and remove the nodePort fields by running the following commands:

cd /home/project/guide-kubernetes-intro/start
sed -i 's=system:1.0-SNAPSHOT=us.icr.io/'"$SN_ICR_NAMESPACE"'/system:1.0-SNAPSHOT\n        imagePullPolicy: Always=g' kubernetes.yaml
sed -i 's=inventory:1.0-SNAPSHOT=us.icr.io/'"$SN_ICR_NAMESPACE"'/inventory:1.0-SNAPSHOT\n        imagePullPolicy: Always=g' kubernetes.yaml
sed -i 's=nodePort: 31000==g' kubernetes.yaml
sed -i 's=nodePort: 32000==g' kubernetes.yaml

endif::[]

Run the following command to deploy the inventory and system microservices with the new configuration: [role='command']

kubectl apply -f kubernetes.yaml

Run the following command to check the status of your pods are ready and running: [role='command']

kubectl get pods

== Scaling a deployment

To use load balancing, you need to scale your deployments. When you scale a deployment, you replicate its pods, creating more running instances of your applications. Scaling is one of the primary advantages of {kube} because you can replicate your application to accommodate more traffic, and then descale your deployments to free up resources when the traffic decreases.

As an example, scale the system deployment to three pods by running the following command: [role='command']

kubectl scale deployment/system-deployment --replicas=3

Use the following command to verify that two new pods have been created. [role='command']

kubectl get pods

[source, role="no_copy"]

NAME READY STATUS RESTARTS AGE system-deployment-6bd97d9bf6-4ccds 1/1 Running 0 1m system-deployment-6bd97d9bf6-jf9rs 1/1 Running 0 25s system-deployment-6bd97d9bf6-x4zth 1/1 Running 0 25s inventory-deployment-645767664f-nbtd9 1/1 Running 0 1m

// Static guide instruction ifndef::cloud-hosted[] Wait for your two new pods to be in the ready state, then make a curl -I request to, or visit the {system-api} URL. endif::[]

// Cloud-hosted guide instruction ifdef::cloud-hosted[] Wait for your two new pods to be in the ready state, then make the following curl command:

curl -I http://$SYSTEM_PROXY/system/properties

endif::[]

Notice that the X-Pod-Name header has a different value when you call it multiple times. The value changes because three pods that all serve the system application are now running. Similarly, to descale your deployments you can use the same scale command with fewer replicas.

[role='command']

kubectl scale deployment/system-deployment --replicas=1

== Redeploy microservices

When you're building your application, you might want to quickly test a change. To run a quick test, you can rebuild your Docker images then delete and re-create your {kube} resources. Note that there is only one system pod after you redeploy because you're deleting all of the existing pods.

// Static guide instruction ifndef::cloud-hosted[] [role='command']

kubectl delete -f kubernetes.yaml

mvn clean package
docker build -t system:1.0-SNAPSHOT system/.
docker build -t inventory:1.0-SNAPSHOT inventory/.

kubectl apply -f kubernetes.yaml

endif::[]

// Cloud-hosted guide instruction ifdef::cloud-hosted[]

cd /home/project/guide-kubernetes-intro/start
kubectl delete -f kubernetes.yaml

mvn clean package
docker build -t system:1.0-SNAPSHOT system/.
docker build -t inventory:1.0-SNAPSHOT inventory/.
docker tag inventory:1.0-SNAPSHOT us.icr.io/$SN_ICR_NAMESPACE/inventory:1.0-SNAPSHOT
docker tag system:1.0-SNAPSHOT us.icr.io/$SN_ICR_NAMESPACE/system:1.0-SNAPSHOT
docker push us.icr.io/$SN_ICR_NAMESPACE/inventory:1.0-SNAPSHOT
docker push us.icr.io/$SN_ICR_NAMESPACE/system:1.0-SNAPSHOT

kubectl apply -f kubernetes.yaml

endif::[]

Updating your applications in this way is fine for development environments, but it is not suitable for production. If you want to deploy an updated image to a production cluster, you can update the container in your deployment with a new image. Once the new container is ready, {kube} automates both the creation of a new container and the decommissioning of the old one.

// ================================================================================================= // Testing microservices that are running on {kube} // =================================================================================================

== Testing microservices that are running on {kube} pom.xml [source, xml, linenums, role='code_column']

include::finish/inventory/pom.xml[]

A few tests are included for you to test the basic functionality of the microservices. If a test failure occurs, then you might have introduced a bug into the code. To run the tests, wait for all pods to be in the ready state before proceeding further. The default properties defined in the [hotspot]pom.xml are:

[cols="15, 100", options="header"] |=== | Property | Description | [hotspot=system.kube.service]system.kube.service | Name of the {kube} Service wrapping the system pods, system-service by default. | [hotspot=system.service.root]system.service.root | The {kube} Service system-service root path, localhost:31000 by default. | [hotspot=inventory.service.root]inventory.service.root | The {kube} Service inventory-service root path, localhost:32000 by default. |===

Navigate back to the start directory.

// Static guide instruction ifndef::cloud-hosted[] include::{common-includes}/os-tabs.adoc[]

[.tab_content.windows_section.mac_section]

Run the integration tests against a cluster running with a host name of localhost: [role='command']

mvn failsafe:integration-test

--

[.tab_content.linux_section]

Run the integration tests with the IP address for Minikube: [role='command']

mvn failsafe:integration-test -Dsystem.service.root=$(minikube ip):31000 -Dinventory.service.root=$(minikube ip):32000

-- endif::[]

// Cloud-hosted guide instruction ifdef::cloud-hosted[] Update the pom.xml files so that the system.service.root and inventory.service.root properties match the values to access the system and inventory* services.

sed -i 's=localhost:31000='"$SYSTEM_PROXY"'=g' inventory/pom.xml
sed -i 's=localhost:32000='"$INVENTORY_PROXY"'=g' inventory/pom.xml
sed -i 's=localhost:31000='"$SYSTEM_PROXY"'=g' system/pom.xml

Run the integration tests by using the following command:

mvn failsafe:integration-test

endif::[]

If the tests pass, you'll see an output similar to the following for each service respectively:

[source, role="no_copy"]

T E S T S

Running it.io.openliberty.guides.system.SystemEndpointIT Tests run: 2, Failures: 0, Errors: 0, Skipped: 0, Time elapsed: 0.372 s - in it.io.openliberty.guides.system.SystemEndpointIT

Results:

Tests run: 2, Failures: 0, Errors: 0, Skipped: 0

[source, role="no_copy"]

T E S T S

Running it.io.openliberty.guides.inventory.InventoryEndpointIT Tests run: 4, Failures: 0, Errors: 0, Skipped: 0, Time elapsed: 0.714 s - in it.io.openliberty.guides.inventory.InventoryEndpointIT

Results:

Tests run: 4, Failures: 0, Errors: 0, Skipped: 0

// ================================================================================================= // Tear Down // =================================================================================================

== Tearing down the environment

// Cloud-hosted guide instruction ifdef::cloud-hosted[] Press CTRL+C to stop the proxy server that was started at step 6 Deploying the microservices. endif::[]

When you no longer need your deployed microservices, you can delete all {kube} resources by running the kubectl delete command: [role='command']

kubectl delete -f kubernetes.yaml

// Static guide only instruction ifndef::cloud-hosted[] [role='command'] include::{common-includes}/kube-minikube-teardown.adoc[] endif::[]

// ================================================================================================= // finish // =================================================================================================

== Great work! You're done!

You have just deployed two microservices that are running in Open Liberty to {kube}. You then scaled a microservice and ran integration tests against miroservices that are running in a {kube} cluster.

// Include the below from the guides-common repo to tell users how they can contribute to the guide

include::{common-includes}/attribution.adoc[subs="attributes"]