Feasible through the Workflow Engine's rolling drain, but real preparation is needed: dual-version discipline, better tests, or schema care before at-will release is sensible. Legacy runtime: the rolling drain works (stealth releases prove it) but relies on fix-forward risk rather than dual-version safety.

1. Adopt the four-stage discipline from the ZDD engineering standard: pre-deployment compatibility, deployment, feature activation behind a flag, post-release cleanup.
2. Make every change dual-version safe: backwards-compatible APIs (new major version for breaking wire changes), expand and contract for any schema change, and consumers tolerant of unknown fields.
3. Audit serialized data: anything in Redis, queues or shared caches must deserialize cleanly across adjacent versions.
4. Wrap behaviour changes in feature flags so code deploys dark and release becomes a business decision, not a deployment event.
5. Route deployments through the Workflow Engine's automated drain, deploy, health-check, return cycle (the path proven by the first automated production run in mid-2026).
6. Verify with area-scoped regression rather than the whole-platform cycle, and watch error rates after rollout with automated rollback on alert.

No SQL Server dependency is recorded for this repo. Nothing to migrate.

Modern runtime, no hosted legacy transport: this service can follow the estate's proven container path (Dockerfile, shared pipeline template, ECS via Terraform).

1. Add a Dockerfile and make the app read all configuration from environment variables and the secrets manager, never from machine-local files.
2. Log to stdout and expose a health check endpoint so ECS can supervise it.
3. Adopt the shared ci.yml pipeline template with the container parameters (awsRegion, containerAfterBuild, ecsTerraformRepo), which is exactly how the estate's existing AWS services deploy.
4. Define the service in the Terraform repo, deploy to a non-production environment, then shift traffic and disarm the deployment-group release pipeline.