What considerations should guide the containerization and Kubernetes deployment of a Ballerina service to maintain portability, observability, and resource efficiency?

Deploying a Ballerina service as a Docker container and running it in a Kubernetes cluster involves compiling the source to a native binary, building an image that contains the runtime, and defining manifests that describe pods, services, and scaling policies. The challenge is to keep the image small, expose appropriate health signals, and manage configuration securely across environments.

How should the Dockerfile be structured to minimize image size while preserving required Ballerina runtime dependencies? Which Kubernetes probes and metrics are most effective for monitoring service liveness and performance? What strategies exist for managing configuration secrets and environment‑specific settings in the deployment manifests?