McLean, VA – June 8, 2026 – We’re pleased to announce the general availability of Syntasa 9.1, our most comprehensive release to date, delivering major improvements across notebook collaboration, cloud security, AI-powered assistance, job execution, analytics, and platform administration.
Notebook Workspaces Reimagined
Syntasa 9.1 introduces a completely restructured notebook workspace model. The legacy shared/private folder hierarchy has been replaced with a unified flat workspace, making notebooks and resources easier to organize and discover. Every user now receives a personal workspace automatically on first login, alongside shared group workspaces for team collaboration.
Real-time collaboration (RTC) is now built into every notebook by default. Multiple users can edit simultaneously, with live cursors, presence indicators, and shared cell output, enabling true pair programming and joint debugging without any configuration.
Additional notebook improvements include a new JupyterLab Runtime Toolbar for managing Spark compute resources directly within the notebook interface, per-notebook initialization scripts stored inside the .ipynb file for full portability, a unified utility library (synutils) providing a single consistent API across Python and Scala for credentials, data access, cloud storage, and more, and native SQL magic (%sql / %%sql) support in both Python and Scala kernels.
Enterprise Security, Enforced at Every Layer
Security is a central theme of this release. Syntasa 9.1 introduces Data Plane Access Control, which uses AWS IAM Session Policies and GCP scoped tokens to dynamically restrict every Spark and notebook session to only the data a user is authorized to access. Scheduled jobs now execute under the job owner’s identity rather than a broad system account.
Cross-GCP Project Support allows organizations to decouple the platform’s Control Plane from its Data Plane across separate GCP projects, enabling better billing separation, compliance isolation, and a foundation for multi-workspace architectures.
Per-Group Service Accounts let teams bring their own cloud identities (AWS IAM Roles, GCP Service Accounts, or Azure Service Principals) attached directly to workspaces and runtime templates, with AES-encrypted just-in-time credential delivery.
On the application side, a new centralized Credential Store manages API keys, tokens, and passwords as first-class objects, supporting both inline encrypted storage and live references to cloud secret managers. Role-Based Access Control has been unified and restructured across the entire platform, with clearer role definitions and a new separation between module access and create permissions. Granular sharing now supports simultaneous public and group-level access at different permission tiers, and User-Defined Processes (UDPs) can now be shared with “Use Only” access, allowing teams to consume custom logic without viewing or modifying the underlying implementation.
AI-Powered Assistance
Syntasa 9.1 introduces two new AI capabilities. The Syntasa AI Help Assistant is a multi-agent system powered by LLMs and a LangGraph orchestration layer that provides contextual guidance based on where a user is in the platform, surfacing relevant documentation, troubleshooting steps, and configuration guidance in real time.
The AI-Powered Log Analysis agent scans job execution logs, identifies root causes, and provides specific remediation suggestions. Unknown errors are saved to a Known Error Database, improving future incident response across the organization.
Additionally, every process in the development palette now displays an in-app tooltip description covering over 100 standard processes, with support for UDP authors to add their own descriptions as well.
Job Execution Improvements
GPU acceleration is now available for both interactive notebooks and batch Spark jobs across AWS EMR, GCP Dataproc, and Azure, powered by the NVIDIA RAPIDS Accelerator for Apache Spark. Production-grade defaults are included out of the box.
The execution log experience has been redesigned end-to-end: stack traces are automatically collapsed, a new tabbed JupyterLab modal consolidates kernel diagnostics, and concurrent multi-user log access is fully supported.
A new Code Managed process mode gives advanced developers complete control over data reads, writes, partition management, and state, bypassing platform automation for workflows that require custom merge logic, Delta Lake operations, or non-table outputs.
Superset Analytics Upgraded to 6.0.0
The integrated Superset analytics engine has been upgraded from 5.x to 6.0.0, bringing a React 18 frontend rebuild, Ant Design v5, native dark mode, dataset folders, and security groups. All Syntasa-specific plugins have been migrated and optimized. The backend now runs on Python 3.11.
Management Console Enhancements
Platform administrators gain new operational controls in 9.1, including selective pod-group redeployments, in-console deployment scaling and pod management without requiring kubectl access, automated SSL/TLS certificate conversion and cluster-wide distribution, Magic Link password resets, and significantly faster dashboard load times.
For the complete list of changes, visit the Syntasa 9.1.0 Release Notes. To plan your upgrade, contact your Syntasa account team.