VertiGIS Solution Manager: Backward Compatibility Support

Description:
We would like to request support for deploying and managing applications that are based on older VertiGIS Studio Web versions through VertiGIS Solution Manager.

At the moment, deployments are primarily aligned with the latest VertiGIS Studio Web releases. In real customer projects, however, it is common to maintain applications on an older Studio Web version for an extended period due to validation processes, project timelines, dependency constraints, or planned upgrade strategies.

Requested Enhancement:
Allow VertiGIS Solution Manager to deploy and manage solution packages targeting older (but still supported) VertiGIS Studio Web versions.

Use Case:

• Customers cannot always upgrade to the latest Studio Web release immediately.
• Multiple customer environments may run different Studio Web versions simultaneously.
• Project teams need a reliable way to deploy, update, and manage applications without being forced to upgrade the underlying Studio Web version.

Expected Behavior:

• Solution Manager should support version-aware deployments.
• The target VertiGIS Studio Web version should either be selectable or automatically detected.
• Compatibility checks should validate whether a package can be deployed to the selected version and provide meaningful warnings when incompatibilities exist.

Business Value:

• Simplifies maintenance of existing customer environments.
• Reduces operational effort and manual workarounds.
• Supports phased upgrade strategies.
• Increases adoption of Solution Manager in long-term customer projects with conservative release cycles.

Example Scenario:
A customer application is running on an older VertiGIS Studio Web version that remains supported. The application should still be deployable and maintainable through Solution Manager without requiring an upgrade to the latest Studio Web release first.

Additional Benefit:
This would enable organizations to separate application lifecycle management from platform upgrade decisions, resulting in more flexible and predictable deployment processes.