Colliding Worlds

IBM Z16 brings together the worlds of Enterprise-Scale Transaction Workloads, with Machine Learning and AI.

"Colliding Worlds" is a collection of practical examples of using a z/OS environment to deploy and use AI technologies with z/OS.

IBM Z16 Context

The IBM Z16 introduced the Telum processor, with the AIU processing unit to support AI workloads. z/OS has also provided a wide range of AI software support, both proprietary and open source, to enable AI workloads. A Z16-based infrastructure is required to realise the business benefits of AI at Scale.

... However, a low-cost emulated IBM Z environment is all you need to learn how to deploy and use AI on Z.

Colliding Worlds Environment

The Colliding Worlds workshop makes use of ZD&T ( Z Development and Test ) to provide a z/OS environment for gaining practical experiences of various AI on Z deployment scenarios. This github repository contains the hands-on learning guides for a student to perform the exercises. It also contains an audit trail of all the work that was done to prepare the lab environment.

Hands-On Learning exercises are provided for two categories of experience.

• Using AI on Z - aimed at the IT and Data Science users. (ie after the software environment has been built)
• Deploying AI software on Z - aimed at the IT specialists who will have to deploy all the software.

You will need to request the correct ZVA Image for the exercises you wish to do.

The links below will take you to the exercise notebooks for the experiences you wish to make use of.

Deployment Exercises ( using ZVA Image "Colliding Worlds Deployment Exercises" )

1. Deploy SQL Data Insights V12 Technology Preview against Db2 z/OS V12
2. Deploy SQL Data Insights feature of Db2 z/OS V13
3. Deploy Open Source Data Science Tools and Libraries in z/OS Container Extensions
4. Deploy Watson Machine Learning for z/OS Community Edition in z/OS Container Extensions
5. Deploy Watson Machine Learning for z/OS

Usage Exercises ( using ZVA Image "Colliding Worlds Usage Exercises" )

1. Using SQL Data Insights V12 Technology Preview against Db2 z/OS V12
2. Using SQL Data Insights feature of Db2 z/OS V13
3. Using Open Source Data Science Tools and Libraries in z/OS Container Extensions
4. Using Watson Machine Learning for z/OS Community Edition in z/OS Container Extensions
5. Using Watson Machine Learning for z/OS
6. Using CDC Solutions to replicate IMS, VSAM and Db2 data from z/OS to Kafka or Postgres
7. Using SQL and REST APIs to Access Data in-situ on z/OS from Anywhere

Workplan

HoLs	Work to do	Effort Estimate
SQLDI V12 * 2	Re-work 2022 Labs	1 day
SQLDI V13 * 2	Adapt 2022 Labs	1 day
ZCX Open Source AI Tools * 2	New Work	4 days
WMLZ-CE * 2	New Work	2 days
WMLZ * 2	New Work	4 days
CDC * 1	Repeat 2022 work	2 days
DaaZ * 1	New Work	4 days