Getting Started with Kubernetes Kit
This tutorial guides you through setting up and deploying an application with Kubernetes Kit in a local Kubernetes cluster.
Requirements
This tutorial assumes that you have the following software installed on your local machine:
Additionally, you’ll need to download a new Vaadin project from start.vaadin.com
.
Add Kubernetes Kit Dependency
To get started, add Kubernetes Kit as a dependency to the project:
<dependency>
<groupId>com.vaadin</groupId>
<artifactId>kubernetes-kit-starter</artifactId>
</dependency>
Then add the following to the application configuration file:
1
vaadin.devmode.sessionSerialization.enabled=true
2
vaadin.serialization.transients.include-packages=com.example.application
-
This property enables the session serialization debug tool during development.
-
This property defines the classes which should be inspected for transient fields during session serialization. In this case, inspection is limited to classes within the starter project. For more information, see Session Replication.
Session Replication Backend
You don’t need to enable session replication if you only need rolling updates.
High availability and the possibility to scale applications up and down in a cluster are enabled by storing session data in a backend that is accessible to the cluster. This tutorial uses Hazelcast for this purpose. However, Redis is also supported.
You’ll need to add the Hazelcast dependency to the project:
<dependency>
<groupId>com.hazelcast</groupId>
<artifactId>hazelcast</artifactId>
</dependency>
Then add the following property to the application configuration file:
vaadin.kubernetes.hazelcast.service-name=hazelcast-service
Next, deploy the Hazelcast service to the cluster by running the following command:
kubectl apply -f https://raw.githubusercontent.com/hazelcast/hazelcast/master/kubernetes-rbac.yaml
Note
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Deploying to Another Namespace
If you want to deploy to another namespace than
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Deploy a load balancer service to your cluster. Create the following Kubernetes manifest file:
apiVersion: v1
kind: Service
metadata:
name: hazelcast-service
spec:
selector:
app: my-app
ports:
- name: hazelcast
port: 5701
type: LoadBalancer
Then deploy the manifest to your cluster:
kubectl apply -f hazelcast.yaml
Run the following command to see that the load balancer service is running:
kubectl get svc hazelcast-service
You should see the following output (the IP number can be different):
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
hazelcast-service LoadBalancer 10.96.178.190 <pending> 5701:31516/TCP 18h
Build & Deploy the Application
The next step is to build a container image of the application and deploy it to your Kubernetes cluster.
To do this, clean the project and create a production build of the application:
mvn clean package -Pproduction
Next, create the following Dockerfile
file in the project directory:
FROM openjdk:17-jdk-slim
COPY target/*.jar /usr/app/app.jar
RUN useradd -m myuser
USER myuser
EXPOSE 8080
CMD java -jar /usr/app/app.jar
Open a terminal to the project directory and use Docker to build a container image for the application. Tag it with version 1.0.0. Note the required period .
at the end of the line:
docker build -t my-app:1.0.0 .
Note
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Image Not Found by Cluster
Depending on the Kubernetes cluster you’re using, you may need to publish the image to a local registry or push the image to the cluster. Otherwise, the image will not be found. Refer to your cluster documentation for more information. If you’re using
In a production environment you can publish the image to a registry that is accessible by the cluster. |
Create a deployment manifest for the application:
apiVersion: apps/v1
kind: Deployment
metadata:
name: my-app-v1
spec:
replicas: 4
selector:
matchLabels:
app: my-app
version: 1.0.0
template:
metadata:
labels:
app: my-app
version: 1.0.0
spec:
containers:
- name: my-app
image: my-app:1.0.0
# Sets the APP_VERSION environment variable for the container which is
# used during the version update to compare with the new version
env:
- name: APP_VERSION
value: 1.0.0
ports:
- name: http
containerPort: 8080
- name: multicast
containerPort: 5701 1
---
apiVersion: v1
kind: Service
metadata:
name: my-app-v1
spec:
selector:
app: my-app
version: 1.0.0
ports:
- name: http
port: 80
targetPort: http
-
The multicast port
5701
is only used for session replication using Hazelcast.
Now deploy the manifest to your cluster:
kubectl apply -f app-v1.yaml
Run the following command to verify that you have four pods running:
kubectl get pods
You should see output similar to the following:
NAME READY STATUS RESTARTS AGE
my-app-v1-f87bfcbb4-5qjml 1/1 Running 0 22s
my-app-v1-f87bfcbb4-czkzr 1/1 Running 0 22s
my-app-v1-f87bfcbb4-gjqw6 1/1 Running 0 22s
my-app-v1-f87bfcbb4-rxvjb 1/1 Running 0 22s
Ingress Rules
To access the application, you need to provide some ingress rules. If you don’t already have ingress-nginx
installed in your cluster, install it with the following command:
kubectl apply -f https://raw.githubusercontent.com/kubernetes/ingress-nginx/controller-v1.4.0/deploy/static/provider/cloud/deploy.yaml
Then create an ingress rule manifest file like so:
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
name: my-app
annotations:
kubernetes.io/ingress.class: "nginx"
# --- Optional ---
# If server Push is enabled in the application and uses Websocket for transport,
# these settings replace the default Websocket connection timeouts in Nginx.
nginx.ingress.kubernetes.io/proxy-send-timeout: "86400"
nginx.ingress.kubernetes.io/proxy-read-timeout: "86400"
# ---
nginx.ingress.kubernetes.io/affinity: "cookie"
nginx.ingress.kubernetes.io/affinity-mode: "persistent"
spec:
rules:
- http:
paths:
- path: /
pathType: Prefix
backend:
service:
name: my-app-v1
port:
number: 80
Deploy the manifest to your cluster with the following command:
kubectl apply -f ingress-v1.yaml
The application should now be available at localhost
.
Note
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Accessing Application Locally
To access the application from your local machine, it may be necessary to use the
The application should now be available at |
Scaling the Application
You can use kubectl
commands to increase or reduce the amount of pods used by the deployment. For example, the following command increases the number of pods to five:
kubectl scale deployment/my-app-v1 --replicas=5
You can also simulate the failure of a specific pod by deleting it by name like so:
kubectl delete pod/<pod-name>
Remember to substitute the name with your application pod’s name. You can see the names of all pods with the kubectl get pods
command.
If you’ve enabled session replication, this can be used to check that it’s performing as expected. If you open the application and then delete the pod to which it’s connected, you shouldn’t lose session data after the next user interaction.