What's new with BlueXP workload factory for GenAI
Learn what's new with the Generative AI workloads capability of workload factory.
29 June 2025
Support for data sources hosted on generic NFS/SMB filesystems
You can now add a data source from a generic SMB or NFS share. This enables you to include files that are stored on volumes hosted by filesystems other than Amazon FSx for NetApp ONTAP.
03 June 2025
Tracker available for monitoring and tracking operations
The Tracker monitoring capability is now available in GenAI. You can use Tracker to monitor and track the progress and status of pending, ongoing, and completed operations, review details for operation tasks and subtasks, diagnose any issues or failures, edit parameters for failed operations, and retry failed operations.
Choose a reranker model for a knowledge base
You can now increase the relevance of reranked query results by selecting a specific reranker model to use with a knowledge base. GenAI supports the Cohere Rerank and Amazon Rerank models.
04 May 2025
Support for NetApp Connector for Amazon Q Business
This release of GenAI introduces support for NetApp Connector for Amazon Q Business, enabling you to create connectors for Amazon Q Business. Quickly and easily take advantage of the Amazon Q Business AI assistant with less initial configuration than building a GenAI knowledge base for Amazon Bedrock.
Enhanced chat model support
GenAI now supports the following additional chat models for knowledge bases:
GenAI supports the models from each provider that Amazon Bedrock supports: Supported foundation models in Amazon Bedrock
Updated permissions terminology
The workload factory user interface and documentation now use "read-only" to refer to read permissions and "read/write" to refer to automate permissions. == 02 March 2025
Embedded chatbot enhancements
You can now copy questions and responses directly to the clipboard, adjust the size of the chat window, and change its title. Additionally, chat responses can now include tables, which are also copyable.
Chat response citation support
Chat responses now include citations that list the files and chunks of data that were used to generate the response.
Enhanced file type support
This release of GenAI provides enhanced file support:
-
Chat models feature improved CSV support. This enables more useful responses when querying data from CSV files.
-
GenAI can now ingest Apache Parquet files from data sources.
-
GenAI now supports ingesting Microsoft Word DOCX files that include images. Images embedded within DOCX documents are scanned, and text insights from the embedded images are included in responses to knowledge base queries.
02 February 2025
Support for Amazon Nova foundation models
GenAI now supports the Amazon Nova foundation models. Amazon Nova Micro, Amazon Nova Lite, and Amazon Nova Pro are supported.
File type filtering for data sources
GenAI now supports selecting specific file types to include in the data source scan when you add a data source.
File modification date filtering for data sources
GenAI now supports filtering files to include in the data source scan by modification date when you add a data source. You can choose a modification date range for the included files.
Support for image files and enhanced support for PDF files
GenAI now supports enhancing responses to knowledge base queries with insights from images and graph descriptions, as well as document text, leading to richer and higher quality answers. GenAI can now scan image files and images within PDF files (also known as multi-modal file support). If you choose to scan images or PDF files, the text from the images (including images embedded in PDF documents) is scanned into the data source and insights from the scans are included in the responses to knowledge base queries.
Hybrid search and rerank support
GenAI can now significantly enhances the relevance and accuracy of search results by using hybrid search and re-ranking the results. Hybrid search combines the strengths of traditional keyword-based search with advanced dense vector-based semantic search techniques. The standard keyword search results are augmented with close matches and linguistic nuance, enhancing relevance. GenAI then refines these results further by using advanced re-ranking models, such as Cohere Rerank and Amazon Rerank, and returns the most relevant results. This capability is available for newly created knowledge bases.
05 January 2025
Custom snapshot name
You can now provide a snapshot name for an ad-hoc snapshot.
Custom AI engine instance name
You can now give a custom name to the AI engine instance during deployment.
Rebuild corrupted or missing GenAI infrastructure
If your AI engine instance becomes corrupted or is somehow deleted, you can let workload factory rebuild it for you. Workload factory automatically reattaches your knowledge bases to the infrastructure after rebuilding is complete, so that they are ready to use.
01 December 2024
Clone a knowledgebase from a snapshot
BlueXP workload factory for GenAI now supports cloning a knowledge base from a snapshot. This enables quick recovery of knowledge bases and creation of new knowledge bases with existing data sources, and helps with data recovery and development.
On-premises ONTAP cluster discovery and replication
Discover and replicate on-premises ONTAP cluster data to an FSx for ONTAP file system so that it can be used to enrich AI knowledge bases. All on-premises discovery and replication workflows are possible from the new On-Premises ONTAP tab in the Storage inventory.
3 November 2024
Mask Personal Identifiable Information with data guardrails
The Generative AI workload introduces the data guardrails feature, powered by BlueXP classification. The data guardrails feature identifies and masks Personal Identifiable Information (PII) helping you maintain compliance and strengthen security for your sensitive organizational data.
29 September 2024
Snapshot and restore support for knowledge base volumes
You can now protect your Generative AI workloads data by taking a point-in-time copy of a knowledge base. This enables you to protect your data against accidental loss or test changes to the settings of the knowledge base. You can restore the previous version of the knowledge base volume at any time.
Pause scheduled scans
You can now pause scheduled data source scans. By default, Generative AI workloads scans each data source daily to ingest new data into each knowledge base. If you don't want the latest changes to be ingested (during testing or while restoring a snapshot, for example) you can pause the scheduled scans and resume them at any time.
Data protection volumes now supported for knowledge bases
When selecting a knowledge base volume, you can now choose a data protection volume that is part of a NetApp SnapMirror replication relationship. This enables you to store knowledge bases on volumes that are already protected by SnapMirror replication.
1 September 2024
Additional chunking strategies
Generative AI workloads now supports multi-sentence chunking and overlap-based chunking for data sources.
Dedicated volume for each knowledge base
Generative AI workloads now creates a dedicated Amazon FSx for NetApp ONTAP volume for each new knowledge base, enabling individual snapshot policies for each knowledge base and improved protection against failures and data poisoning.
4 August 2024
Amazon CloudWatch Logs integration
Generative AI workloads is now integrated with Amazon CloudWatch Logs, enabling you to monitor Generative AI workloads log files.
Example chatbot application
The NetApp workload factory GenAI sample application enables you to test authentication and retrieval from your published NetApp workload factory knowledge base by interacting directly with it in a web-based chatbot application.
7 July 2024
Initial release of the workload factory for GenAI
The initial release includes the capability to develop a knowledge base that is customized by embedding your organization's data. The knowledge base can be accessed by a chatbot application for your users. This capability ensures accurate and relevant responses to organization-specific questions, enhancing the satisfaction and productivity for all of your users.