🦀databricks-kube-operator
A Kubernetes operator for Databricks
[!IMPORTANT] As of 2025/06 this project is archived. We recommend using Upjet to generate a Crossplane provider from the official Databricks Terraform Provider
A kube-rs operator to enable GitOps style management of Databricks resources. It supports the following APIs:
Jobs 2.1
DatabricksJob
Git Credentials 2.0
GitCredential
Repos 2.0
Repo
Secrets 2.0
DatabricksSecretScope, DatabricksSecret
Experimental headed towards stable. See the GitHub project board for the roadmap. Contributions and feedback are welcome!
Quick Start
Looking for a more in-depth example? Read the tutorial.
Installation
Add the Helm repository and install the chart:
helm repo add mach https://mach-kernel.github.io/databricks-kube-operator
helm install databricks-kube-operator mach/databricks-kube-operatorCreate a config map in the same namespace as the operator. To override the configmap name, --set configMapName=my-custom-name:
cat <<EOF | kubectl apply -f -
apiVersion: v1
kind: ConfigMap
metadata:
name: databricks-kube-operator
data:
api_secret_name: databricks-api-secret
EOFCreate a secret with your API URL and credentials:
Usage
See the examples directory for samples of Databricks CRDs. Resources that are created via Kubernetes are owned by the operator: your checked-in manifests are the source of truth.
Changes made by users in the Databricks webapp will be overwritten by the operator if drift is detected:
Look at jobs (allowed to be viewed by the operator's access token):
A job's status key surfaces API information about the latest run. The status is polled every 60s:
Developers
Begin by creating the configmap as per the Helm instructions.
Generate and install the CRDs by running the crd_gen bin target:
The quickest way to test the operator is with a working minikube cluster:
Generating API Clients
The client is generated by openapi-generator and then lightly postprocessed so we get models that derive JsonSchema and fix some bugs.
Expand CRD macros
Deriving CustomResource uses macros to generate another struct. For this example, the output struct name would be DatabricksJob:
rust-analyzer shows squiggles when you use crds::databricks_job::DatabricksJob, but one may want to look inside. To see what is generated with cargo-expand:
Adding a new CRD
Want to add support for a new API? Provided it has an OpenAPI definition, these are the steps. Look for existing examples in the codebase:
Download API definition into
openapi/and make a Rust generator configuration (feel free to copy the others and change name)Generate the SDK, add it to the Cargo workspace and dependencies for
databricks-kube/Implement
RestConfig<TSDKConfig>for your new clientDefine the new CRD Spec type (follow kube-rs tutorial)
impl RemoteAPIResource<TAPIResource> for MyNewCRDimpl StatusAPIResource<TStatusType> for MyNewCRDand specifyTStatusTypein your CRDAdd the new resource to the context ensure CRDs condition
Add the new resource to
crdgen.rs
Running tests
Tests must be run with a single thread since we use a stateful singleton to 'mock' the state of a remote API. Eventually it would be nice to have integration tests targetting Databricks.
License
Last updated