Nintex Process Discovery Release Notes v. 21.12
Release Date: January 2022
New Features and Improvements
Nintex Process Discovery v21.12 release provides a number of significant improvements including:
Kubernetes Deployment
We now support Kubernetes deployment.
Kubernetes (K8S) is an open-source container orchestration system for automating software deployment, scaling, and management. All of the system components are suitable to run as microservices and can be deployed on K8S and Linux.
Docs Manager
DocsManager, the service responsible for exporting the documents into BPMN, CSV, and WORD files, was refactored from .NET to Node.js. The service is now scalable, and it resolved many other bugs, including the missing thumbnail that indicates user action in the exported Word document.
For more information, see Doc Manager
Multi GUID Indexing
Due to a prior bug, not all recording/GUID process repetitions were being gathered into the same process. Now, running discovery will yield more effective and superior results.
Penetration Testing and Security
There were many vulnerability fixes and updates to all packages, including third-party components. The new version of the components and the CVEs which they resolve can be found in Third-Party Vulnerability Fixes.
Username Hashing : By hashing usernames, we have now significantly increased the security, making it even harder to decrypt and identify the real user behind the recording.
Refactored PD Admin
PD Admin is responsible for:
→ License management
→ Team management
→ Robot management
→ Permissions
It was fully refactored from .NET service to several Node.js micro-services, and resulted in:
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Increased system performance and stability
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Many resolved bugs
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The ability to support a larger number of robots and licenses
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Improved console visibility
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New architecture
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Documentation can be found in System Architecture
Image Masking
New masking capabilities were added, including:
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Icons/UI element detection is considerably more accurate
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Surrounding Text – Dense text areas help us detect words that the OCR struggles to detect correctly
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For example, to detect words in other languages that the OCR can't detect directly
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The masking now detects URLs better
For more information, see Image Masking