Optimize Docker Image Size

**Summary**
Reduce Docker image size to improve deployment speed, decrease storage consumption, and minimize security exposure from unnecessary packages and dependencies.

**Description**
Review the current Docker image build process and identify opportunities to reduce image size. This may include:

- Coordinate with product teams with the code changes.
- Using a smaller base image where appropriate.(https://github.com/googlecontainertools/distroless)
- Implementing multi-stage builds.(https://github.com/GoogleContainerTools/distroless/blob/main/examples/python3-requirements/Dockerfile)
- Removing unnecessary packages, build tools, and cached files.
- Consolidating image layers where practical.
- Excluding non-essential files through .dockerignore.
- Verifying that application functionality remains unchanged after optimization.
- Verifying flask db upgrade remains functioning.

**Acceptance Criteria**

- Docker image size is reduced compared to the current baseline.
- Application functionality and performance are validated after optimization.
- Build and deployment pipelines continue to operate successfully.
- Changes are documented, including before-and-after image size metrics.
- Any base image or dependency changes are reviewed and approved.

**Definition of Done**

- Optimized Dockerfile committed to source control.
- CI/CD pipeline passes successfully.
- Image size reduction documented in the ticket.
- Container vulnerability scan results show improvement compared to the baseline image.

**Example**
https://github.com/bcgov/bcros-common/blob/main/notify-service/notify-api/Dockerfile
https://console.cloud.google.com/artifacts/docker/c4hnrd-tools/northamerica-northeast1/cloud-run-repo/notify-api?project=c4hnrd-tools

Locate the current Dockerfile, .dockerignore, and build or deployment pipeline configuration, then measure the existing image size and review how the Flask application and `flask db upgrade` run in the container. Compare the optimized image against that baseline, verify application behavior and pipeline success, and document image-size and vulnerability-scan results.

Written by the indexing model from the issue text.