IDUG NA 2025

In today's data–driven world, the integration of robust database management systems with advanced machine learning platforms is crucial for deriving actionable insights and driving innovation. This presentation explores the synergy between IBM DB2 and AWS SageMaker, highlighting how this powerful combination can enhance data analytics and machine learning workflows.
IBM DB2, a highly scalable and reliable relational database management system, offers comprehensive data management capabilities. When integrated with AWS SageMaker, a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly, the potential for data–driven decision–making is significantly amplified.
This session will cover:
The architecture and key features of IBM DB2 and AWS SageMaker.
Best practices for integrating DB2 with SageMaker to streamline data preprocessing, model training, and deployment.
Real–world use cases demonstrating the benefits of this integration in various industries.
Attendees will gain a comprehensive understanding of how to leverage the strengths of both DB2 and SageMaker to enhance their data analytics and machine learning capabilities, ultimately driving more informed and strategic business decisions.

IBM provides us number of solution to achieve multisite HA/DR for PureScale clusters. Those include technologies like HADR Replication for PureScale Clusters, Geographically Dispersed PureScale Clusters, GPFS replication for PureScale Clusters, Q Replication for PureScale Clusters.
 In the presentation we will describe alternative approach, where replication across 2 sites is provided by Storage Array Layer, which allows us to achieve additional benefits like consistency groups going beyond single GPFS filesystem used by the PureScale, optimized network utilization where Storage Array replication happens on SAN Fiber, additional HA layer where filesystem can be cross mounted across sites which gives additional redundancy layer for storage availability.
  
 We implement solution by deploying Synchronic Storage Replication across 2 sites, where SAN fabric provides us NSD multi path connections from each side. This way on each side we have collection of NSD disks that are local to given side, and also connection to remote NSD disks from DR side. On both sites we install standalone PureScale clusters, independent from each, therefore failure of any of those clusters does not impact other side counterpart. Having 2 clusters we designate one as primary by creating PureScale managed GPFS on top of Storage Array Layer, and on top of that create Database with its' associated paths. Next we use gpfssync capabilities to export primary GPFS filesystem , and next mount the same on DR site. This allows us to mimic primary cluster on DR site, and next attach those synchronized mount points to TSAMP cluster on secondary site. Later on, we just move application connection to DR site, which can handle further ongoing workloads.
  
 Proposed solution is active–passive deployment, when at any given time only one cluster has connection to synchronized storage array. We achieve this by protections on each layer (NSD disks active on one site only, GPFS mounts online on one site only, database cataloging on one site only). This is crucial to ensure only one side has active writes to the cluster, so that we prevent any corruption of the data. In the presentation we provide procedures to setup such deployment, along with failover procedures where we move storage attachment from primary to secondary, and reverse. We also provide testing results where we verify solution, by forcing failover and more failure scenarios while processing application workload.

In these days of heightened security, it is likely that you will be asked about Db2’s audit facility, db2audit. This tool has the ability to collect a number of types of security information and this presentation will show how to configure and use db2audit. dbaudit can collect massive amounts of data but there are ways to limit the data and those techniques will be shown in the presentation.

Db2 13 introduced the ability to track execution of IBM Db2 utilities allowing users to gain insight into the performance of the utilities. In this session you will hear how it has been implemented, what information is recorded and when, and some ideas of how the feature can be used to improve your utility processing.

Join me on a journey through our first year of deploying SQL Data Insights (SDI) into production. Discover how SDI impacted our business processes, changed stakeholder perceptions of the mainframe, and enhanced our approach to data analysis.
We will start with a review of our first use case and discuss the resources consumed for training and scoring, as well as the impact SDI had on our business processes. 
SDI's most evident benefit is its ability to analyze data where it sits without having to export, transfer and reload it, and with minimal data science dependency. But how does it compare to more traditional approaches? To answer that, we'll compare SDI with other machine learning algorithms by applying them to a frequently used dataset for predicting diamond prices. We'll delve into the accuracy of the algorithms and see how SDI stacks up against data scientists' most loved algorithms.
Following that, we'll explore a brand–new use case that applies the new commonality–function in Db2 FL504. We'll discuss its usefulness, resource requirements, and potential impact on business processes, providing more practical insights into the power of SDI.
And finally, I'll share a use case that demonstrates how to identify outliers using SDI with Db2 monitoring data, ready to be applied in your own shop. 
Don't miss this opportunity to gain practical insights into the power of SDI and how it can transform your data analysis!

When we talk about Mainframe Modernization, we usually discuss DevOps, Zowe, APIs, Java, Python, etc, but how often does anyone talk about how your security posture needs to be modernized?  Many of these systems were built 30–40 years ago when it was just batch, IMS and CICS.  Now we have traffic coming in from everywhere, whether it is via APIs, distributed Db2, or other means, you need to make sure you are prepared to monitor that traffic to prevent DDoS attacks, and make sure nobody is getting at your most sensitive data.  I will discuss some of the core Db2 Security features that companies should consider using along with Data Access Monitors like Guardium.