Barbara platform release 2.7.0: Deploying models directly in TensorFlow

To this end, we have developed the following key new functionalities:

TensorFlow Model Deployment

Now, Barbara supports the direct deployment of models in TensorFlow, providing users with enhanced flexibility and compatibility.

Batch Processing Enhancements

New batch functionalities allow users to:

• Delete all applications in a single click.
• Perform "prepare and sign" actions on batches separately.

Role-Based Access Control (RBAC)

Barbara v2.7 introduces RBAC, enabling users to control platform features based on their roles. This includes granular control over user management, with the ability to edit user roles.

Export secrets and credentials selectively for specific roles

Administrators can tailor the export process to align with the security and access requirements of their organization. Whether you're managing a diverse team with varying responsibilities or collaborating with external partners, exporting secrets and credentials by role streamlines the sharing process while maintaining a robust security posture.

AppConfig File Management

Users can now upload and download AppConfig files directly from the panel, simplifying the configuration process.

Additional Improvements:

• New graphical images for default nodes enhance the visual experience.
• Select fields now include a search engine, making it easier to locate and manage specific elements within the platform.
• Improved error display…

...and much more to come.

We believe these enhancements will further elevate your experience with Barbara, making it an even more powerful and user-friendly solution for orchestrating the deployment and monitoring of AI models across diverse edge devices. Thank you for choosing Barbara as your preferred choice for AI integration, and we look forward to your continued success with version 2.7.0

You can even suggest improvements and new applications or report issues by dropping us an email at feedback@barbaraiot.com!

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