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Setting up the dev environment#

Before you start building an app, you'll need to prepare the development environment. This guide assumes you have EDA installed already and if you don't, you can quickly spin one up by following the Try EDA guide.

Your primary tools when developing an app:

  • edabuilder for scaffolding, building, and publishing your app.
  • go sdk for authoring the API of your custom resources.
  • python runtime for getting syntax highlighting and IDE support when writing intents optional.
  • kubectl for creating resources.
  • edactl for verifying installation workflows and debugging.

These tools are available for all major OSes and architectures, so you can develop on your preferred platform, no matter where you are.

edabuilder is a CLI tool that helps to scaffold a new EDA app, build the container for it and then publish the application to the catalog. The CLI can be downloaded from the GitHub repository as well as from the eda-toolbox1 Pod.

Download the latest edabuilder binary from the GitHub repository directly, or leverage the downloader script that comes with the EDA Playground:

Run in the EDA Playground repository
make download-edabuilder

This will download the edabuilder binary to the ./tools directory in the EDA Playground repository. For convenience, you can move the binary somewhere to your $PATH.

If you're developing on a linux/amd64 machine, you can get the edabuilder binary from the eda-toolbox Pod:

TOOLBOX_POD=$(kubectl get -n eda-system pod -l eda.nokia.com/app=eda-toolbox \
  -o jsonpath='{.items[0].metadata.name}')
kubectl -n eda-system \
cp ${TOOLBOX_POD}:/eda/tools/edabuilder /usr/local/bin/edabuilder
sudo chmod +x /usr/local/bin/edabuilder

We will define the API of our declarative apps exactly like in Kubernetes - by crafting the Go files that extend the API of the EDA core. For this, we need a Go SDK.

Install Go SDK by following the upstream installation instructions.

The minimum Go version required is 1.22.

While being optional, we recommend installing the Python runtime and initialize a virtual environment for development.

If you already have a Python environment dialed in, you can skip this step, but if not, then the easiest way to get Python on your dev machine is by installing uv - a modern multiplatform Python distribution and package manager.

kubectl is the Kubernetes command-line tool. During development, you may find it easier to create resources with it, rather than venturing into the EDA UI.

If you have completed the Try EDA step, then kubectl has already been downloaded for you and you can just copy it out to a permanent location in your $PATH.

edactl will help you query the EDA cluster and debug your application. You don't even need to download it directly, you can use an alias to run it from within the EDA cluster as explained in the CLI Tools guide.

And now with these tools in your toolchest, you've got everything you need to start building your first app! Choose your preferred path, would you want to put the code to the compiler right away or want to beef up your knowledge on the matter?

  1. eda-toolbox pod is by default deployed in the eda-system namespace. ↩