If you are looking to start evaluating Zeebe in your own Kubernetes Cluster or if you are already doing so with our Helm Charts you should take a look at the following GitHub repository which contains a set of configurations (profiles) based on different use cases.

Zeebe Helm Profiles are just configurations for the official Zeebe Helm Charts.

The idea behind these profiles is to configure Zeebe and surrounding components for different use cases.

A common requirement is to evaluate Zeebe into Minikube or Kubernetes KIND, or in a Cloud Provider. For each of these scenarios, you will need to configure the charts in slightly different ways.

If you want to run Zeebe on your own laptop, one of the first challenges that you will face is Memory and CPU. This is only because the default configuration in the official Zeebe Helm Charts creates 3 Zeebe Brokers and 1 Zeebe Gateway, and installs ElasticSearch in a full HA setup. This default setup will not work in your laptop unless you have loads of CPUs and RAM memory to configure your Minikube instance. For that reason, you can get started with the Dev profile which just starts a single Zeebe Broker plus one Gateway with a single ElasticSearch node.

The good thing about profiles is that you don’t even need to download the file to use it, you can use these profiles directly from GitHub by using the following one-liner:

helm install my-zeebe-cluster zeebe/zeebe-full –values https://raw.githubusercontent.com/zeebe-io/zeebe-helm-profiles/master/zeebe-dev-profile.yaml

If you have a full-fledge Kubernetes Cluster with more resources you can try the Zeebe Core Team Profile which starts the default configuration but using the latest Docker images (SNAPSHOTS).

If you are doing some kind of performance testing with different configurations for partitions and you want to share your profile, please feel free to get in touch (Zeebe forums, create an issue in the repository or send me a DM via twitter @salaboy) and we will happily add your profile to this repository for other people to use and test.

Because this is a community-driven initiative, the profiles also go further into configuring other components created by the community, such as ZeeQS and alpha components such as Task List.

These profiles and the content of the GitHub repository will evolve if teams using Zeebe contribute with their own configurations, tweaks and improvements.

Once again, If you are interested in contributing to these profiles or if you find uses while running them in different Cloud Providers please create an issue in this repository.

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