Camunda BPM on Kubernetes

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Running Camunda BPM on Kubernetes

Are you running Kubernetes now? Ready to move your Camunda BPM instances off of VMs, or just try it out on Kubernetes? We will address some common configurations and provide some building blocks you can tailor to your particular needs.

Skill level: Intermediate

You’ve used Kubernetes before. If not, why not try a tutorial and spin up your first cluster?


  • Alastair Firth is a Senior Site Reliability Engineer on the Camunda Cloud team.
  • Lars Lange is a Devops Engineer at Camunda.


git clone
cd camunda-examples/camunda-bpm-demo
make skaffold

Ok that probably didn’t work unless you have skaffold and kustomize installed. Read on!

What is Camunda BPM

Camunda BPM is an open source platform for workflow and decision automation that brings business users and software developers together. It is ideal for coordinating and connecting humans, (micro)services, or even robots! You can read more about some use cases here.

Why run on Kubernetes

Kubernetes has become the de facto standard for running modern applications on Linux. By using system calls instead of emulating the hardware layer, and allowing the kernel to manage memory and task switching, overhead and startup times are minimized. However, the greatest benefit may come in the standard API it provides for configuring the infrastructure all applications need, such as storage, networking, and monitoring. 5 years old in June 2019, it’s arguably the second largest open source project ever (behind Linux), and is stabilizing in feature set after the rapid iteration of the past few years as it becomes critical to production workloads around the globe.

Camunda BPM Engine can easily connect easily to other applications running in the same cluster, and Kubernetes provides great scalability, allowing you to grow your infrastructure costs only when the software really needs it (and shrink it moments later).

Visibility is also greatly improved by tools like Prometheus, Grafana, Loki, Fluentd and Elasticsearch allowing a centralized view of all cluster workloads. We’ll look at how to inject a Prometheus exporter into the JVM today.


We’ll address several areas where we can configure the Camunda BPM docker image (GitHub) to play nicely with Kubernetes.

  1. Logs and metrics
  2. Database connections
  3. Authentication
  4. Session Management

We will go through some techniques to address these, and show a workflow that might work for you.

Note: Using Enterprise? See here and update the image references accordingly.

Development Workflow

Development Workflow

For this demo, we’ll use Skaffold to build docker images with google cloud build. It has good support for a variety of templating tools (like Kustomize and Helm), CI and build tools, and infrastructure providers. The skaffold.yaml.tmpl included is configured for google cloud build and GKE, which provides a very easy way to get going on production grade infrastructure.

make skaffold will upload the Dockerfile context to cloudbuild, build the image and save it to your project’s GCR, then apply the manifests to your cluster. This is the behavior of make skaffold, but Skaffold has many other capabilities.

For Kubernetes yaml templating we’re using kustomize for managing yaml overlays without forking the whole manifest, allowing you to git pull --rebase future improvements. It’s now in kubectl and works well for this kind of thing.

We also use envsubst to fill in a hostname and GCP project id in the *.yaml.tmpl files. You can see how this works in makefile or just follow along.


  • A working Kubernetes cluster
    • GKE or minikube are a good way to get started
  • Kustomize
  • Skaffold for building your own docker images and deploying easily to GKE
    • download the latest release
    • curl -Lo skaffold && chmod +x skaffold && sudo mv skaffold /usr/local/bin
    • if you’re using google cloud build, then
    • gcloud auth application-default login
    • otherwise configure skaffold.yaml.tmpl for your providers
  • A copy of this code
    • git clone
  • envsubst
    • OSX installation
    • Linux install gettext with your package manager
    • used for the demo to avoid hardcoding hostnames and cloud project ids

Manifests Only Workflow

If you don’t want to use kustomize or skaffold, you can refer to the manifests in generated-manifest.yaml, and adapt them to the workflow of your choice.

Logs and Metrics

Prometheus has become the standard for capturing metrics in Kubernetes. It fills the same niche as AWS Cloudwatch Metrics, Cloudwatch Alerts, Stackdriver Metrics, StatsD, Datadog, Nagios, vSphere Metrics and others. It’s open source and has a powerful query language. The front end of choice is Grafana, and it comes with lots of dashboards available out of the box. They are bundled together and relatively easy to install with the prometheus-operator helm chart.

Prometheus defaults to a pull model scraping <service>/metrics, and adding a sidecar container to expose this is common. Unfortunately the JMX metrics are best captured from inside the JVM, so a sidecar isn’t as effective. Let’s plug the open source jmx_exporter from Prometheus into the JVM by adding it to the container image, which will expose a /metrics path on another port.

Add the Prometheus jmx_exporter to the container

-- images/camunda-bpm/Dockerfile
FROM camunda/camunda-bpm-platform:tomcat-7.11.0

## Add prometheus exporter
RUN wget -P lib/
#9404 is the reserved prometheus-jmx port
ENV CATALINA_OPTS -javaagent:lib/jmx_prometheus_javaagent-0.11.0.jar=9404:/etc/config/prometheus-jmx.yaml

Well that was easy. The exporter will monitor tomcat and expose it’s metrics in Prometheus format at <svc>:9404/metrics

Configure the exporter

The sharp-eyed reader may wonder where prometheus-jmx.yaml is coming from. There are many different things that can run in a JVM, and tomcat is just one of them, so the exporter needs some configuration. Standard configurations for tomcat, WildFly, kafka, etc are available here. We’ll add the tomcat one as a ConfigMap in Kubernetes, and then mount it as a volume.

First, we add the tomcat-flavored exporter config file to our platform/config/ directory:

└── prometheus-jmx.yaml

Then we add a ConfigMapGenerator to kustomization.yaml.tmpl:

-- platform/kustomization.yaml.tmpl
kind: Kustomization
  - name: config
      - config/prometheus-jmx.yaml

This will add each element of files[] as an element of the config ConfigMap. ConfigMapGenerators are great because they hash the data in the config and trigger a pod restart if it changes. They also reduce the amount of configuration in the Deployment, as you can mount the whole “folder” of config files in one VolumeMount.

Finally we need to mount the ConfigMap as a volume to the pod:

-- platform/deployment.yaml
apiVersion: apps/v1
kind: Deployment
        - name: config
            name: config
            defaultMode: 0744
        - name: camunda-bpm
            - mountPath: /etc/config/
              name: config

Nice. If your Prometheus isn’t configured to scrape everything, you may need to tell it to scrape the pods. Prometheus-operator users can use service-monitor.yaml to get started. See service-monitor.yaml, operator design, and spec to get started.

Extending this pattern to other use cases

All files we add to the ConfigMapGenerator will be exposed in the new /etc/config directory. You can extend this pattern to mount any other configuration files you need. You can even mount a new startup script. You can use the subpath object to mount a single file. If you find yourself needing to update xml files in place, please consider using xmlstarlet instead of sed. It’s already included in the image.


Great news! The application logs are already available on stdout, for example with kubectl logs. Fluentd (installed by default on GKE) will forward your logs to Elasticsearch, Loki, or your enterprise log platform. If you want to jsonify your logs, you could follow the pattern above to set up logback.


By default, the image will come up with an ephemeral H2 database. This is NOT what you want for production.
We use Google Cloud SQL, with the cloudsql-proxy in front of it for some internal uses, and this is an easy option if you don’t have a preferred database setup. On AWS, RDS provides a similar service. See setup instructions for the cloudsql-proxy on kubernetes.

Regardless of the database you choose, unless it’s H2 you’ll need to set the appropriate environment variables in platform/deployment.yaml. This might look something like:

-- platform/deployment.yaml
apiVersion: apps/v1
kind: Deployment
        - name: camunda-bpm
            - name: DB_DRIVER
              value: org.postgresql.Driver
            - name: DB_URL
              value: jdbc:postgresql://postgres-proxy.db:5432/process-engine
            - name: DB_USERNAME
                  name: cambpm-db-credentials
                  key: db_username
            - name: DB_PASSWORD
                  name: cambpm-db-credentials
                  key: db_password

Note: You could also use Kustomize to patch the deployment for different environments using an overlay: example.

Note: the use of valueFrom: secretKeyRef. Please use this wonderful feature of Kubernetes, even during development, to keep your secrets secure.

You probably already have a system for manage kube secrets. If not, some options include:

  • Encrypting them with your cloud provider’s KMS, and then injecting them into K8S as secrets through a CD pipeline
  • MozillaSOPS
    • this can work very well in combination with Kustomize secret generators
    • lots of other tools like dotGPG do a similar job
  • HashiCorp Vault
  • Kustomize Secret Value Plugins


Unless you just want to use localhost port forwarding, you’ll need an ingress controller configured. If you’re not running ingress-nginx (helm chart), you probably already know that you need to go set some different annotations in ingress-patch.yaml.tmpl or platform/ingress.yaml. If you are running ingress-nginx, and have it watching the nginx ingress class with a load balancer pointing at it and external-dns or a wildcard A record set up, you’re all set. Otherwise set up an ingress controller and DNS now, or skip ahead and port forward straight to the pod.


If you’re using cert-manager or kube-lego, and letsencrypt, your certificates for the new ingress should be automatically provisioned for you. Otherwise, check out ingress-patch.yaml.tmpl and adjust to your needs.

Run it!

If you’ve followed along so far, make skaffold HOSTNAME=<> should bring up an accessible instance at <hostname>/camunda

If you didn’t expose the ingress via a public URL, you can port forward from localhost:
kubectl port-forward -n camunda-bpm-demo svc/camunda-bpm 8080:8080
and browse to localhost:8080/camunda

Give tomcat a few moments to come up, and cert-manager awhile to verify your domain name. You can follow the logs with your log aggregator, a tool like kubetail, or with just kubectl:

kubectl logs -n camunda-bpm-demo $(kubectl get pods -o=name -n camunda-bpm-demo) -f

Next steps


This is more in the “configuring Camunda BPM” bucket than specific to Kubernetes, but it’s important to note that by default the REST API has authentication disabled. You can switch on basic auth, or use another method like JWT. You can use configmaps and volumes to load xml, or use xmlstarlet (see above) to edit existing files in the image, and either wget jars or sideload them with an init container and shared volume.

Session management

Like many other applications, Camunda BPM handles sessions at the JVM, so if you want to run multiple replicas you can either enable sticky sessions, (example for ingress-nginx), which will survive until the replica goes away or the cookie’s Max-Age, or for a more robust solution you can deploy a session manager into tomcat. Lars has a separate post about this topic, but something like:

wget -P lib/ && 
wget -P lib/ && 

sed -i '/^</Context>/i 
<Manager className="de.javakaffee.web.msm.MemcachedBackupSessionManager" 
/>' conf/context.xml

Note: xmlstarlet can replace sed here

We’ve used twemproxy in front of Google Cloud Memorystore, with memcached-session-manager (supports redis) to get this up and running.


If you have sessions sorted out, the first (and often last) limit for scaling Camunda BPM may be database connections. You can tune these to some extent out of the box. We turn down the intialSize in settings.xml too. Add a HorizontalPodAutoscaler (HPA) and you can get to double digit replicas pretty easily.

Requests and Limits

In platform/deployment.yaml you’ll see we have hardcoded the resource field. This works well with HPA, but you may need to tune them. A kustomize patch will work well for this. See ingress-patch.yaml.tmpl and ./kustomization.yaml.tmpl for an example.


We’ve set up Camunda BPM on Kubernetes with Prometheus metrics, logs, an ephemeral H2 database, TLS, and Ingress. We’ve added jars and configuration files using ConfigMaps and a Dockerfile. We’ve talked about sharing data with volumes and directly into environment variables from secrets. We’ve also provided an overview of configuring Camunda for multiple replicas and authenticaticated APIs.


File Map
├── generated-manifest.yaml       <- manifest for use without kustomize
├── images
│   └── camunda-bpm
│       └── Dockerfile            <- overlay docker image
├── ingress-patch.yaml.tmpl       <- site-specific ingress configuration
├── kustomization.yaml.tmpl       <- main Kustomization
├── Makefile                      <- make targets
├── namespace.yaml
├── platform
│   ├── config
│   │   └── prometheus-jmx.yaml   <- prometheus exporter config file
│   ├── deployment.yaml           <- main deployment
│   ├── ingress.yaml
│   ├── kustomization.yaml        <- "base" kustomization
│   ├── service-monitor.yaml      <- example prometheus-operator config
│   └── service.yaml
└── skaffold.yaml.tmpl            <- skaffold directives


Please ask questions specific to Camunda on our forum!

Questions about Kubernetes may be better asked on the k8s slack.

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