command to create presigned URL for MLFlow

README.md

@@ -83,7 +83,7 @@ mlflow:
   register_trained_models: true
 ```
 
-In `create` mode, the CLI manages the tracking server name from `infra.stack_name`.
+In `create` mode, the CLI manages the tracking server name from `infra.stack_name`; you do not need to set `tracking_server_name`.
 
 To use an existing MLflow tracking server, set:
 
@@ -101,6 +101,14 @@ uv sync --extra mlflow
 
 When MLflow is enabled, `train start` creates an MLflow run for the SageMaker job. `train status` finalizes that run once the job reaches a terminal state and registers completed model artifacts as pre-release model versions using the `prerelease-latest` MLflow alias.
 
+To open the managed SageMaker MLflow UI, request a fresh presigned URL:
+
+```bash
+qc-cli infra mlflow-url --config config.yaml
+```
+
+This works for `mode: create` and for `mode: existing` when the existing server is managed by Amazon SageMaker. In `create` mode, the command uses the CLI-managed tracking server name. In `existing` mode, it uses `mlflow.tracking_server_name`. If the existing MLflow server is external to SageMaker, open it with that server's own URL instead.
+
 ## Commands
 
 ### `init`
@@ -118,6 +126,7 @@ qc-cli infra setup                         Deploy the CDK stack
 qc-cli infra setup --no-bootstrap          Deploy without running CDK bootstrap
 qc-cli infra setup --cloudformation-execution-policy <arn> Set CDK bootstrap execution policy ARN
 qc-cli infra status                        Show CDK stack/resource status
+qc-cli infra mlflow-url                    Print a presigned MLflow UI URL
 qc-cli infra destroy                       Destroy stack, retaining S3 data
 qc-cli infra destroy --yes                 Destroy stack without confirmation
 qc-cli infra destroy --delete-bucket-data  Destroy stack and delete S3 data