Monitoring Spark Applications with Prometheus and JMX Exporter

Using the Spark operator to setup Java Metrics Exporter (JMX) and send metrics to Prometheus

Spark Operator supports exporting Spark metrics in Prometheus format using the JMX Prometheus Exporter. This allows detailed monitoring of your Spark drivers and executors with tools like Prometheus and Grafana.

Warning

The older documentation in Kubeflow’s monitoring section is outdated and fails with newer Spark images. This updated guide addresses Issue #2380.

1. Build a Spark Image with the JMX Exporter Jar

Start by building a custom Docker image that includes the JMX Prometheus Java agent.

Dockerfile example:

ARG SPARK_IMAGE=docker.io/spark:3.4.1
FROM ${SPARK_IMAGE}

# Switch to user root so we can add additional jars and configuration files.
USER root

# Setup for the Prometheus JMX exporter.
ENV JMX_EXPORTER_AGENT_VERSION=1.1.0
ADD https://github.com/prometheus/jmx_exporter/releases/download/${JMX_EXPORTER_AGENT_VERSION}/jmx_prometheus_javaagent-${JMX_EXPORTER_AGENT_VERSION}.jar /opt/spark/jars
RUN chmod 644 /opt/spark/jars/jmx_prometheus_javaagent-${JMX_EXPORTER_AGENT_VERSION}.jar

USER ${spark_uid}

Build and push the image:

docker build -t <your-repo>/spark-jmx:3.4.1 .
docker push <your-repo>/spark-jmx:3.4.1

2. Configure the SparkApplication with Monitoring Enabled

Use the monitoring.prometheus section to enable the JMX exporter in both the driver and executor containers.

SparkApplication YAML example:

apiVersion: "sparkoperator.k8s.io/v1beta2"
kind: SparkApplication
metadata:
  name: spark-pi
spec:
  type: Java
  mode: cluster
  image: "<your-repo>/spark-jmx:3.4.1"
  imagePullPolicy: Always
  mainClass: org.apache.spark.examples.SparkPi
  mainApplicationFile: "local:///opt/spark/examples/jars/spark-examples_2.12-3.4.1.jar"
  sparkVersion: "3.4.1"
  driver:
    cores: 1
    coreLimit: "1200m"
    memory: "512m"
    labels:
      version: 3.4.1
    serviceAccount: spark-operator-spark
  executor:
    cores: 1
    instances: 1
    memory: "512m"
    labels:
      version: 3.4.1
  monitoring:
    exposeDriverMetrics: true
    exposeExecutorMetrics: true
    prometheus:
      jmxExporterJar: "/opt/spark/jars/jmx_prometheus_javaagent-1.1.0.jar"
      port: 8090

3. Access and Monitor Metrics

Prometheus Scraping

Set up a PodMonitor or ServiceMonitor to scrape the metrics:

apiVersion: monitoring.coreos.com/v1
kind: PodMonitor
metadata:
  name: spark-pi
spec:
  selector:
    matchExpressions:
      - key: "spark-role"
        operator: "Exists"
  podMetricsEndpoints:
    - port: jmx-exporter

4. Quick Access to Grafana and Prometheus

Before accessing dashboards, make sure you have a Prometheus stack installed and configured.

ℹ️ Note: You need to install a Prometheus stack to collect and visualize metrics.
A good option is the kube-prometheus-stack Helm chart.
In your values.yaml, be sure to set the following to ensure Prometheus scrapes PodMonitor and ServiceMonitor objects cluster-wide:
serviceMonitorSelectorNilUsesHelmValues: false
podMonitorSelectorNilUsesHelmValues: false

Access Grafana:

kubectl port-forward $(kubectl get pods --selector=app.kubernetes.io/name=grafana -n monitoring --output=jsonpath="{.items..metadata.name}") -n monitoring 3001:3000

# Visit:
http://localhost:3001
# Login: admin / prom-operator

# Then import dashboard inside Grafana https://grafana.com/grafana/dashboards/23304
# Dashboard ID is: 23304

Access Prometheus:

kubectl port-forward -n monitoring prometheus-prometheus-stack-kube-prom-prometheus-0 9090

# Visit:
http://localhost:9090

5. Troubleshooting

# Check prometheus exporter behavior
kubectl exec -it -n spark <driver-pod-name> -- curl http://localhost:8090/metrics

# Access prometheus exporter configuration
kubectl exec -it -n spark <driver-pod-name> -- cat /etc/metrics/conf/prometheus.yaml

# Check metrics are avaible inside Prometheus database
kubectl run -i --rm --tty shell --image=curlimages/curl -- sh
METRIC_NAME="spark_driver_livelistenerbus_queue_streams_size_type_gauges"
curl "http://prometheus-stack-kube-prom-prometheus.monitoring:9090/api/v1/query?query=$METRIC_NAME"

Summary

Step	Description
1️⃣	Build a custom Spark image with `jmx_prometheus_javaagent`
2️⃣	Use the `monitoring.prometheus` section in your SparkApplication
3️⃣	Use `PodMonitor` or `ServiceMonitor` to scrape metrics
4️⃣	Access Grafana and Prometheus via port-forward or SSH
5️⃣	Troubleshoot with `curl` and `kubectl exec`

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Last modified June 17, 2025: spark-operator: Document how to monitor with jmx and prometheus (#4098) (8a99b4da)