Yes it is possible. Briefly you will need to ensure following:
- Make sure all your applications store event logs in a specific location (
filesystem, s3, hdfs etc).
- Deploy the history server in your cluster with access to above event logs location.
Now spark (by default) only read from the filesystem path so I will elaborate this case in details with spark operator:
- Create a
PVC with a volume type that supports ReadWriteMany mode. For example NFS volume. The following snippet assumes you have storage class for NFS (nfs-volume) already configured:
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: spark-pvc
namespace: spark-apps
spec:
accessModes:
- ReadWriteMany
volumeMode: Filesystem
resources:
requests:
storage: 5Gi
storageClassName: nfs-volume
- Make sure all your spark applications have event logging enabled and at the correct path:
sparkConf:
"spark.eventLog.enabled": "true"
"spark.eventLog.dir": "file:/mnt"
- With event logs volume mounted to each application (you can also use operator mutating web hook to centralize it ) pod. An example manifest with mentioned config is show below:
---
apiVersion: "sparkoperator.k8s.io/v1beta2"
kind: SparkApplication
metadata:
name: spark-java-pi
namespace: spark-apps
spec:
type: Java
mode: cluster
image: gcr.io/spark-operator/spark:v2.4.4
mainClass: org.apache.spark.examples.SparkPi
mainApplicationFile: "local:///opt/spark/examples/jars/spark-examples_2.11-2.4.4.jar"
imagePullPolicy: Always
sparkVersion: 2.4.4
sparkConf:
"spark.eventLog.enabled": "true"
"spark.eventLog.dir": "file:/mnt"
restartPolicy:
type: Never
volumes:
- name: spark-data
persistentVolumeClaim:
claimName: spark-pvc
driver:
cores: 1
coreLimit: "1200m"
memory: "512m"
labels:
version: 2.4.4
serviceAccount: spark
volumeMounts:
- name: spark-data
mountPath: /mnt
executor:
cores: 1
instances: 1
memory: "512m"
labels:
version: 2.4.4
volumeMounts:
- name: spark-data
mountPath: /mnt
- Install spark history server mounting the shared volume. Then you will have access events in history server UI:
apiVersion: apps/v1beta1
kind: Deployment
metadata:
name: spark-history-server
namespace: spark-apps
spec:
replicas: 1
template:
metadata:
name: spark-history-server
labels:
app: spark-history-server
spec:
containers:
- name: spark-history-server
image: gcr.io/spark-operator/spark:v2.4.0
resources:
requests:
memory: "512Mi"
cpu: "100m"
command:
- /sbin/tini
- -s
- --
- /opt/spark/bin/spark-class
- -Dspark.history.fs.logDirectory=/data/
- org.apache.spark.deploy.history.HistoryServer
ports:
- name: http
protocol: TCP
containerPort: 18080
readinessProbe:
timeoutSeconds: 4
httpGet:
path: /
port: http
livenessProbe:
timeoutSeconds: 4
httpGet:
path: /
port: http
volumeMounts:
- name: data
mountPath: /data
volumes:
- name: data
persistentVolumeClaim:
claimName: spark-pvc
readOnly: true
Feel free to configure Ingress, Service for accessing the UI.

Also you can use Google Cloud Storage, Azrue Blob Storage or AWS S3 as event log location. For this you will need to install some extra jars so I would recommend having a look at lightbend spark history server image and charts.