Release Notes
Abstract
Hardware and software requirements for installing Machine Learning for IBM z/OS on IBM z.
Content
Machine Learning for IBM z/OS Enterprise Edition is an enterprise machine learning solution that runs on IBM® Z. You can run ML for z/OS as a stand-alone solution or infuse it into your enterprise AI capability as a scalable platform.
Machine Learning for IBM z/OS Core Edition is a lightweight version of MLz providing the essential services that are REST-API-based for machine learning operations including online scoring capabilities on IBM Z. Primarily aiming for AIOps use cases through AI solutions offered by IBM or IBM partners.
What's New in version 3.2.0
- Support multi-user model development environment leveraging JupyterHub.
- Enhanced trustworthy AI capability through improved monitoring configuration and intuitive visualization of explainability results.
- New capability in the Trustworthy AI component to continuously monitor and detect drift in the data distribution of model inputs and outputs, ensuring the model remains accurate and reliable.
- Support IBM Semeru Runtime Certified Edition for z/OS, Version 17, the latest release of Java SDK on z/OS.
- Support for z/OS Spark 4.0.
- Support IBM Z Deep Learning Compiler (IBM zDLC) 5.0.0 for ONNX model compilation and scoring.
- Provide the up to date machine learning support for AI Python packages on z/OS.
- Support multi-class classification model scoring leveraging the on-chip AI accelerator of IBM z16 through Snap ML.
- New option of configuring a RACF® keyring-based keystore with hardware private key for user authentication and SSL/TLS communication
- Enhancement in support of issuing console messages to reflect when the core and scoring services have started, ended, or encountered an error
- Enhancement to drift-related output under Trustworthy AI, including exporting drift results as a PDF
- Enhancement in support of integration with watsonx.ai and watsonx.governance
- Enhancement in support of online scoring timeout for PMML models
- Dual control enhancement to enable an extra layer of security for online deployment changes
- Enhancement in support of Serving ID that enables inferencing using a user-provided ID in place of the auto-generated deployment ID
- Enhancement in support of Scoring service IP binding
- Support for the z17 Telum II on-chip AI accelerator
- Support for a new authorization scheme that leverages XFACILIT class profiles
- Support for Db2 secure port connectivity
- CDA (Cloud Data Access) credential storage for userID and password information for Db2, ONNX, and Trust capabilities
- Support for IBM Semeru Runtime Certified Edition for z/OS, Version 21
Maintenance Level
MLz maintenance level | APAR/PTF for IBM Z |
| Machine Learning for IBM z/OS Core Edition V3.2 | 2026 Jun APAR PH70682/PTF UO08348 2026 Mar APAR PH69959/PTF UO07048 2025 Nov APAR PH68837/PTF UO05782 2025 Aug APAR PH67684/PTF UO04511 2025 Jul APAR PH66196/PTF UO04081 APAR PH66213/PTF UO04082 APAR PH66214/PTF UO04083 2025 Mar APAR PH64998/PTF UO02576 APAR PH65690/PTF UO02574 APAR PH65691/PTF UO02575 2024 Dec APAR PH61600/PTF UI99430 APAR PH64473/PTF UI99431 APAR PH64474/PTF UI99432 |
| Machine Learning for IBM z/OS Enterprise Edition V3.2 | 2026 Jun APAR PH70682/PTF UO08354 2026 Mar APAR PH69959/PTF UO07055 2025 Nov APAR PH68837/PTF UO05783 APAR PH68898/PTF UO05784 2025 Aug APAR PH67684/PTF UO04512 2025 Jul APAR PH66196/PTF UO04084 APAR PH66213/PTF UO04085 APAR PH66214/PTF UO04086 APAR PH66215/PTF UO04087 APAR PH66216/PTF UO04088 APAR PH66217/PTF UO04089 2025 May APAR PH66197/PTF UO03447 APAR PH66786/PTF UO03448 2025 Mar APAR PH64998/PTF UO02579 APAR PH65690/PTF UO02577 APAR PH65691/PTF UO02578 APAR PH65790/PTF UO02580 APAR PH65791/PTF UO02581 2024 Dec APAR PH61600/PTF UI99433 APAR PH64473/PTF UI99434 APAR PH64474/PTF UI99435 APAR PH64475/PTF UI99436 |
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Document Information
Modified date:
26 June 2026
UID
ibm17003489