z/OS AI Framework components

The AI Framework for IBM® z/OS® consists of 5 major component areas that, together, enable AI-enhanced capabilities within the z/OS system.

Figure 1 shows the major components that form the AI Framework for IBM z/OS.

Figure 1. AI Framework for IBM z/OS components
The AI framework components are described in the text that follows the figure.

The following component descriptions correspond to the numbered components shown in Figure 1:

 1  — Data collection

Data collection provides a common way to collect IT data for use in AI model training.

The data collection engine performs the following functions:
  • Collects and parses the raw IT data.
  • Streams the data to the data store.

AI Framework for IBM z/OS uses IBM Z® Common Data Provider (ZCDP) as the data collection engine.

EzNoSQL for z/OS, a component of DFSMS, serves as the data store to hold data for training the AI models.
  • Implemented using VSAM data sets.
  • Accessed by the model training pipeline and, optionally, by the deployed model.
  • Can be used both for training and for the deployed model to store its own data.

 2  — AI model server

The AI model server hosts and manages the AI models.
  • Manages model training, versioning, deploying, and monitoring.
  • Supports failover for high availability.
  • Accessed by the system via REST APIs.

AI Framework for IBM z/OS uses Machine Learning for IBM z/OS Core Edition (MLz Core) as the AI model server.

 3  — AI Base Component

AI Base Component for IBM z/OS (z/OS AI Base), a new component of the BCP element, assists use-case providers in communicating with the AI model server. This support enables traditional z/OS components to use AI models without the need for frequent updates to the latest technologies.
  • Access is via traditional z/OS assembler services (macros).
  • Handles connection to REST APIs.

 4  — User interface (z/OSMF)

The user interface is the primary means by which end users work with the z/OS AI Framework and manage models, and is provided through IBM z/OS Management Facility (z/OSMF).
  • A z/OSMF workflow, known as the AI Framework for IBM z/OS Configuration Workflow, guides you through the installation process with detailed configuration steps for each of the framework components.
  • The AI Control Interface for IBM z/OS, a new task on the z/OSMF desktop, provides AI model management. You use the z/OS AI Interface to initiate training of a model for a use case and to enable or disable the AI mode for that use case or place it into simulation mode.

 5  — AI providers and use cases

Providers can plug into the AI framework to perform the following functions for simpler deployment of AI-driven use cases:
  • Define data collection.
  • Create the model training pipeline.
  • Call the z/OS AI Base component.
  • Extend the user interface.

Workload management (WLM) is the first provider of an AI use case, AI-powered WLM batch initiator management, that uses the z/OS AI Framework. The use case proactively starts WLM-managed initiators based on predictive insights on upcoming batch workloads.

The framework is designed to be expandable to include additional providers and use cases.