create-oda-operator

You can build a Kubernetes operator for ODA Canvas using Python by leveraging the KOPF framework. This approach automates operator creation, enforces consistent reconciliation patterns like triple-stacked handlers, and reduces boilerplate for component lifecycle management.

To manage child resource state propagation across multiple CRDs in KOPF, implement adoption, ownership, and status roll-up patterns. These patterns ensure the child resource state is consistently propagated back to the parent Component, ExposedAPI, and DependentAPI CRDs.

Triple-stacked handlers in Kubernetes operator reconciliation consist of resume, create, and update handlers for CRD lifecycle management. This pattern ensures reliable reconciliation across operator restarts by consistently processing Custom Resource Definitions.

You can configure multiple facets of an ODA Canvas component in a data-driven way by using SEGMENT_CONFIG patterns. This enables cross-resource orchestration to manage various component facets dynamically within the Kubernetes operator.

KOPF supports consistent logging and documentation templates for ODA Canvas operators. The framework enforces these patterns to guide operators from initial development through to production readiness while maintaining standardized operational outputs.

You need resume handlers in addition to create and update for KOPF operators to ensure reliable reconciliation across restarts. This triple-stacked handler approach guarantees the operator correctly recovers and processes existing Custom Resources after interruptions.