Mainframe Relevance in an AI-First Era: How Db2 Fits

For decades, the IBM Z mainframe has been the backbone of mission-critical computing. Db2 for z/OS sits at the center of this story, reliably managing the world’s most sensitive and high-value data. Yet in today’s IT landscape, dominated by discussions of artificial intelligence (AI), machine learning, and data-driven transformation, the question inevitably arises: 

Where does Db2 fit in an AI-first world?

The answer is clear: Db2 remains central. In fact, it is uniquely positioned to power and support enterprise AI initiatives.

The Foundation of Trustworthy Data

AI is only as good as the data that feeds it. Models trained on incomplete, inconsistent, or inaccurate data produce unreliable outcomes. This is where Db2 shines. With its proven capabilities for data integrity, security, and availability, Db2 for z/OS provides the foundation of trustworthy, enterprise-grade data that AI depends upon.

Organizations already store their most critical operational data in Db2. Leveraging this data directly—without needing complex ETL processes that move it into less secure environments—offers a significant advantage. AI workloads can run against reliable, current data with governance and compliance controls already in place.

Db2 and Embedded AI Capabilities

IBM has not stood still in bringing AI to Db2 for z/OS. For example, Db2 AI for z/OS (Db2ZAI) uses machine learning models to improve database performance. By analyzing workload patterns, Db2ZAI can recommend optimal buffer pool configurations, predict query performance, and even assist the optimizer in choosing the best access paths. This closes the loop: AI is being applied inside Db2 itself to make database management more intelligent and efficient.

Similarly, SQL Data Insights brings AI-powered analytics directly into Db2 for z/OS, enabling built--in SQL functions to use AI for anomaly detection and data pattern recognition without requiring external AI platforms. These capabilities allow organizations to unlock the hidden value in their Db2 data more quickly and intuitively.

Synergy with IBM Z and AI Acceleration

The hardware platform itself reinforces this story. The latest IBM z16 and z17 mainframes incorporate on-chip AI acceleration with the Telum processor and Spyre AI accelerator. This means that inferencing can be performed where the data resides, avoiding latency and risk associated with data movement. For financial institutions detecting fraud, retailers optimizing transactions, or insurers assessing claims, the ability to apply AI in real-time on operational data is transformative.

Db2, running on these systems, is directly positioned to take advantage of this capability—turning the mainframe into not just a system of record, but also a system of insight and decision.

The DBA’s Evolving Role in an AI-First Era

As AI integrates more deeply into Db2, the role of the DBA also evolves. No longer solely the guardian of performance tuning and availability, the modern DBA must understand how AI tools are being embedded in their environment. This includes evaluating AI-driven recommendations, integrating AI queries into business applications, and ensuring that AI workloads are governed and secure.

Rather than diminishing the DBA’s importance, AI amplifies it. Human expertise is needed to validate, interpret, and operationalize AI-driven insights in ways that align with business priorities and regulatory requirements.

Conclusion

The narrative that positions mainframes and Db2 as “legacy” is misguided. In reality, Db2 for z/OS sits at the heart of enterprise AI adoption. With its unmatched reliability, native AI capabilities, and synergy with IBM Z’s AI-accelerated hardware, Db2 is not only relevant but critical in an AI-first world.

For organizations pursuing AI, the best path forward often starts with the data they already trust most—residing in Db2. The mainframe is not being left behind by AI; it is, in fact, helping to lead the way.

Machine Learning and AI Integration in Db2 for z/OS

In today’s data-driven world, the ability to harness the power of machine learning (ML) and artificial intelligence (AI) is essential for organizations aiming to stay competitive. With the introduction of Db2 for z/OS Version 13 and subsequent function levels, IBM has made significant strides in integrating ML and AI capabilities directly into the Db2 ecosystem, transforming the way businesses leverage their data.

SQL Data Insights

Perhaps the single most important new AI capability added to Db2 13 for z/OS is SQL Data Insights (SDI). I have written about this before and if you are interested in a more thorough discussion of SDI, check out this article on elnion.

At a high level though, SDI enables data scientists and analysts to run advanced analytics directly on data residing in Db2 without the need for extensive data movement. By minimizing data transfer, organizations can reduce latency and improve the efficiency of their workflows.

The initial support for SDI in Db2 13 for z/OS FL600 included three AI functions: AI_SIMILARITY, AI_SEMANTIC_CLUSTER and AI_ANALOGY. Function level 504 added a fourth: AI_COMMONALITY.

Python Support

Python is the dominant programming language for AI and ML because of its simplicity, readability, and vast ecosystem of libraries. It offers clear syntax allowing data scientists and developers to focus on solving problems rather than wrestling with complex code structures. This makes it ideal for rapid prototyping of AI models. Rich frameworks such as TensorFlow, PyTorch, and others provide ready-to-use tools for data preparation, model training, and evaluation, significantly reducing development time. Moreover, Python’s large, active community continually contributes new algorithms, techniques, and integrations, ensuring that it stays at the forefront of AI and ML innovation. This combination of usability, flexibility, and ecosystem maturity has made Python the de facto standard for building, deploying, and operationalizing AI and ML solutions across industries.

With Python being so important to data scientists, it stands to reason that IBM should support it in Db2 for z/OS. And they do! Python support for Db2 for z/OS was delivered with the IBM Db2 AI for z/OS and the Db2 for z/OS Python driver as part of the IBM Db2 for z/OS “Data Server Driver for ODBC, CLI, and .NET” family.

• IBM Db2 AI for z/OS (Db2ZAI) is an advanced solution designed to enhance the operational performance, reliability, and efficiency of Db2 for z/OS systems. By leveraging machine learning (ML) and artificial intelligence (AI), it improves many aspects of Db2 management. We will discuss it in a little more detail in the next section.
• The Python driver is IBM's official database connectivity driver that allows Python applications to connect to and interact with IBM DB2 databases. It delivers connectivity not just for Db2 for z/OS, but also for other IBM database products including DB2 for Linux/Unix/Windows, DB2 for i (AS/400), and IBM Informix.

So, Python support became generally available via IBM Db2 for z/OS Distributed Data Facility (DDF) using the IBM Data Server Driver for Python, which is the same Python driver used for Db2 LUW, but configured to connect over DRDA to Db2 for z/OS.

This wasn’t tied to a specific Db2 function level—rather, it was an enhancement to the client connectivity stack and supported back to Db2 11 for z/OS with the right PTFs. Of course, as of this December (2025) Version 13 will be the only supported version of Db2 for z/OS.

Machine Learning Enhanced Optimization

The Db2 optimizer can also benefit from an infusion of AI. Optimization improvement is a benefit of IBM’s Db2 AI for z/OS, an add-on solution that uses AI/ML to elevate system operations and performance.

IBM Db2 AI for z/OS continuously analyzes workload patterns, system metrics, and SQL execution behavior to recommend or automatically apply optimizations—such as selecting better access paths, tuning buffer pools, or adjusting configuration settings to reduce CPU usage. By learning from an organization’s actual Db2 workload over time, it adapts its recommendations to evolving data and usage patterns, helping maintain consistent performance without constant manual tuning.

In addition, Db2 AI for z/OS can assist in workload management, anomaly detection, and operational decision-making, giving DBAs intelligent, data-driven insights to run large-scale mainframe database systems more efficiently. By incorporating machine learning into key processes it can help to reduce CPU usage, optimize SQL query plans and concurrency, and detect and resolve anomalies and root causes.

Indeed, the AI-driven operational support of Db2 AI for z/OS goes beyond using AI in SQL queries. It is focused on keeping Db2 for z/OS environments running optimally and proactively, enhancing system resiliency and availability.

Summing Things Up

IBM continues to integrate machine learning and AI capabilities into Db2 for z/OS. By empowering organizations to leverage their data for predictive analytics and advanced machine learning, IBM is helping businesses unlock new opportunities and drive smarter decision-making. As these technologies continue to advance, the potential for innovation and growth in the data landscape is limitless. Embrace the future of data with Db2 for z/OS and unleash the power of AI and machine learning in your organization today!

5 Big Concerns of Modern IT When Using Db2 for z/OS

Db2 for z/OS is an entrenched solution for managing data at the world's largest organizations. It is a strong, reliable DBMS and I wrote about its strength recently on the blog (here). You really cannot go wrong using Db2 for z/OS for mission-critical workloads.

That said, there are concerns and issues facing organizations using Db2 for z/OS. One of the biggest concerns with Db2 for z/OS today is managing the cost and complexity of maintaining mainframe environments while still delivering high availability and performance. 

As such, here are 5 specific concerns facing large organizations using Db2 for z/OS today:

1. Skill Shortages: Many mainframe experts, especially those with deep Db2 for z/OS knowledge, are approaching retirement, creating a significant skills gap. The lack of trained professionals has made it challenging to manage and maintain Db2 for z/OS systems effectively.

2. Cost of Licensing and Maintenance: Mainframe systems come with substantial licensing costs. Many organizations are looking for ways to optimize usage or even repatriate workloads to more cost-effective platforms, where feasible, to reduce operational expenses. Whether or not such changes result in "actual" cost reductions is unfortunately irrelevant as many executives believe it will regardless of reality and studies to the contrary.

3. Integration with Modern Architectures: As companies adopt cloud, big data, and other modern architectures, integrating Db2 for z/OS with these systems can be complex and costly. Many seek seamless data integration between Db2 on mainframes and newer platforms like data lakehouses, which involves architectural and technological challenges.

4. Automation and DevOps Compatibility: Modern IT environments emphasize agility, continuous integration, and deployment, but the mainframe environment traditionally doesn’t integrate well with DevOps practices. Nevertheless, many companies are pushing for Db2 automation tools and integration with DevOps workflows to streamline operations and reduce manual workloads... and DevOps is being successfully deployed by mainframe organizations today using Zowe and other traditional DevOps tooling.

5. Performance and Availability: High performance and availability are always top concerns, especially as organizations process more data and need to meet stringent SLAs. Handling lock contention, optimizing query performance, and scaling resources efficiently continue to be challenges. But, to be fair, these are challenges with many DBMS implementations, not just Db2 for z/OS.

Organizations are adopting several strategies to address the challenges with Db2 for z/OS and ensure their mainframe environments remain relevant and efficient:

1. Workforce Development and Knowledge Transfer: To counter skill shortages, organizations are investing in training and upskilling initiatives for new IT staff, partnering with universities, or using mentoring programs to transfer knowledge from retiring mainframe experts to newer employees. Additionally, some companies are leveraging consulting firms or managed services providers with mainframe expertise to fill gaps temporarily.

2. Cost Optimization with Usage Analytics: Companies are using detailed workload and resource monitoring tools to optimize Db2 for z/OS usage, identify inefficient processes, and reduce costs. This includes tuning queries, scheduling batch jobs during off-peak hours, and leveraging IBM’s Workload Manager (WLM) to prioritize workloads based on business needs.

3. Hybrid Cloud and Data Lakehouse Integrations: To manage integration with modern architectures, organizations are implementing hybrid cloud strategies and data lakehouses that can interface with Db2 for z/OS. Tools such as IBM Db2 Analytics Accelerator allow data stored on Db2 for z/OS to be offloaded to faster, scalable platforms, enabling integration with big data and analytics environments without entirely migrating off the mainframe.

4. Automation and DevOps Integrations: Organizations are investing in DevOps and automation tools compatible with Db2 for z/OS, such as IBM UrbanCode and mainframe DevOps solutions from other ISVs such as Broadcom and BMC Software. By automating routine tasks like provisioning, patching, and deploying schema changes, organizations can adopt more agile, efficient processes. Integrating Db2 for z/OS with CI/CD pipelines helps streamline development workflows, bridging mainframe operations with modern DevOps practices. For more details on integrating Db2 for z/OS into DevOps, consult this blog post that highlights several posts I wrote on the topic!

5. Mainframe Modernization with AI and Machine Learning: Using AI and machine learning to optimize Db2 for z/OS operations is becoming common. AI-based monitoring tools, such as IBM’s Watson AIOps, can predict system issues and detect anomalies to prevent downtime. Machine learning algorithms can also be used for capacity planning, workload optimization, and tuning Db2 performance parameters, helping reduce manual intervention.

6. Resilience and High Availability Improvements: For performance and availability, companies are implementing high-availability solutions like IBM Geographically Dispersed Parallel Sysplex (GDPS) to ensure continuous uptime. They’re also using backup automation and disaster recovery solutions tailored for Db2 to meet stringent SLAs and minimize downtime in case of failures.

By combining these strategies, organizations are better equipped to manage the costs, complexity, and skills required to maintain and modernize Db2 for z/OS environments in today’s rapidly evolving IT landscape.

Db2 for z/OS: The Performance and Management Champion!

Usually, posts I write for this blog focus on technical details, tips, and techniques for better using and optimizing your experience with Db2. Today, I want to do something a little different. You see, I am a big fan of Db2 for z/OS, and I do not see it getting the press, or the accolades that I think it is due. So I am going to use my platform to shout out the performance benefits of Db2 for z/OS.

When it comes to performance, nothing beats Db2 for z/OS. This mainframe database has been setting the standard for decades, delivering unmatched speed and efficiency for mission-critical applications. Let's explore some of the reasons why Db2 for z/OS is the performance champion.

Hardware Acceleration

• z/Architecture: Db2 for z/OS takes full advantage of the powerful z/Architecture, which includes specialized hardware for database operations. This hardware acceleration provides a significant performance boost for tasks like query processing and data loading.
• Storage Subsystem: The mainframe's storage subsystem is designed for high performance and reliability. With features like z/Hyperlink, data compression, and flash storage, Db2 for z/OS can access data quickly and efficiently.
• IDAA: IBM Db2 Analytics Accelerator is a high-performance, in-memory database appliance designed to accelerate analytic workloads. It's optimized for large-scale data analysis tasks, providing significant speedups compared to traditional disk-based databases. By leveraging solid-state drives (SSDs) and advanced hardware architecture, IDAA can handle complex queries and data manipulations with exceptional efficiency. This makes it ideal for applications requiring real-time analytics, data warehousing, and big data processing.

Database Optimization

• Query Optimization: Db2 for z/OS has a sophisticated query optimizer that can automatically select the most efficient execution plan for your queries. This ensures that your applications run as fast as possible.
• Data Compression: Db2 for z/OS supports data compression, which can reduce storage requirements and improve performance. By compressing data, Db2 can reduce the amount of data that needs to be read and processed.
• Parallel Processing: Db2 for z/OS can take advantage of multiple processors to perform tasks in parallel. This can significantly improve performance for large workloads.
• AI: IBM Db2 AI for z/OS integrates autonomics to simplify database management efforts. Using machine learning and AI, it can help improve operational performance and maintain Db2 for z/OS efficiency and health while enhancing Db2 for z/OS performance, reliability and cost effectiveness–even under the most demanding circumstances.

Workload Management

• Resource Allocation: Db2 for z/OS provides powerful tools for managing resources and ensuring that your database applications get the resources they need to perform optimally.
• Workload Balancing: Db2 can automatically balance workloads across multiple systems to ensure that resources are used efficiently.
• WLM: Workload Manager is an integrated, critical component of z/OS that is used for optimizing the performance and resource utilization of Db2 for z/OS. It provides a comprehensive framework for managing workloads across the mainframe environment, ensuring that Db2 applications receive the resources they need to perform optimally.

Data Sharing and Parallel Sysplex

Finally, Data Sharing using IBM Z Parallel Sysplex confers a significant advantage onto Db2 for z/OS in that it can enhanced availability by providing inherent redundancy, as multiple subsystems can access the same data. This helps to mitigate the impact of hardware failures or system outages. And in case of a disaster, data sharing can facilitate rapid recovery by allowing applications to access data from a different subsystem.

Furthermore, Data Sharing enhances scalability by enabling workloads to be distributed across multiple subsystems, improving scalability and preventing bottlenecks. It facilitates simpler growth: as data volumes and application demands increase, data sharing can help to accommodate growth without requiring significant hardware investments.

And Data Sharing can improve performance. By allowing multiple Db2 subsystems to access the same data without requiring individual copies, data sharing significantly reduces I/O operations, leading to improved performance. And with data readily available to multiple subsystems, queries can be executed more quickly, resulting in faster response times for applications.

So, IBM Z data sharing on Db2 offers a range of benefits, including improved performance, enhanced availability, increased scalability, reduced costs, and simplified management. These benefits make it a valuable feature for organizations that require high-performance, reliable, and scalable database solutions.

Real-World Results

Organizations around the world rely on Db2 for z/OS to power their most critical applications. From financial services to healthcare, Db2 has proven its ability to deliver the performance and reliability that businesses need to succeed.

So, if you're looking for a database that can handle your most demanding workloads and deliver exceptional performance, Db2 for z/OS is the way to go.

Asking ChatGPT About the Advantages of Db2 for z/OS over Oracle

If you read my blog post from yesterday, you know that I have been playing around with ChatGPT, the latest AI technology that is sweeping the headlines.

Yesterday I was asking it about the mainframe, but today I thought I'd ask ChatGPT about Db2 and Oracle, specifically:

In what ways is IBM Db2 for z/OS better than Oracle?

Yes, I know that is a loaded question and that the results would likely be different if I swapped the order of Db2 for z/OS and Oracle. Nevertheless, I liked the results that ChatGPT generated, so I figured I'd share them with everybody here!

So here is ChatGPT's reply:

"Both IBM Db2 for z/OS and Oracle are mature and widely used relational database management systems, and each has its strengths and weaknesses. However, here are some ways that IBM Db2 for z/OS might be considered better than Oracle:

Transaction Processing: Db2 for z/OS is known for its high performance and ability to handle large transaction processing workloads. It is optimized for OLTP (Online Transaction Processing) applications and can handle high concurrency and high throughput.

Security: IBM has a long-standing reputation for security, and Db2 for z/OS is no exception. It has a robust set of security features, including encryption, role-based access control, and auditing capabilities that help ensure that sensitive data is protected.

Cost: Db2 for z/OS can be less expensive to operate than Oracle for some use cases. It is designed to run on IBM mainframes, which are known for their scalability and efficiency, allowing organizations to reduce hardware and software costs. Additionally, because IBM mainframes are known for their reliability, uptime, and availability, they can help reduce costs associated with system downtime or data loss.

Integration: Db2 for z/OS can integrate with other IBM products and services, such as CICS (Customer Information Control System) and IMS (Information Management System). This can be particularly beneficial for organizations that already have an IBM infrastructure in place.

Built-in Analytics: Db2 for z/OS includes built-in analytics features, such as IBM Db2 Analytics Accelerator, which can help organizations to run complex analytics queries on large datasets. This can be particularly useful for organizations that need to process large amounts of data quickly and efficiently. 

It is worth noting that Oracle also has its own strengths and advantages, such as its support for a wide range of platforms and its focus on database consolidation. Ultimately, the choice between Db2 for z/OS and Oracle will depend on the specific needs and requirements of an organization."

Again, a quite reasonable response! I think the thing that jumped out at me the most here is the "Cost" section. As a grizzeled, old mainframer I am always ready to fight back against unfounded claims that the mainframe option is always the more espensive one. But ChatGPT didn't make that mistake! Maybe because Oracle has a reputation of being expensive, too?

At any rate, I look forward to asking ChatGPT for help in my future endeavors. 

AI and ChatGPT Tell You Why You Should Use a Mainframe

ChatGPT has been getting a lot of attention for its ability to formulate reasonable responses to questions and inquiries. There have even been examples of ChatGPT being able to pass college exams and write up readable articles.

ChatGPT is a chatbot developed by OpenAI. It was launched in November pf 2022. It is built on top of OpenAI's GPT-3 family of large language models and it has been fine-tuned using both supervised and reinforcement learning techniques. 

So it is a somewhat practical example of AI being applied to a common proglem... communication.

Being the mainframe zealot that I am, I decided to ask ChatGPT why I should use a mainframe. I wasn't sure what to expect, but I am delighted with the response that I got. 

Me: Why should I still use a mainframe?

ChatGPT: There are several reasons why you might still want to use a mainframe for certain applications:

1. High Reliability: Mainframes are designed to handle massive workloads and to provide high levels of reliability and availability. They are built with redundant components and features that allow them to recover quickly from failures, making them ideal for mission-critical applications.
2. Security: Mainframes are known for their robust security features. They have been used in industries such as finance, healthcare, and government for decades because they offer features such as hardware encryption, advanced access controls, and secure connectivity options.
3. Scalability: Mainframes can scale vertically to handle large amounts of data and processing power. They can also scale horizontally by adding more processors or servers to a mainframe cluster, making them a good fit for organizations with rapidly growing or fluctuating workloads.
4. Cost-Effective: While mainframes are expensive to purchase, they can provide a cost-effective solution for certain applications. Mainframes are designed to handle large workloads with high efficiency, and they can consolidate multiple applications onto a single platform, reducing the need for additional hardware and software.
5. Legacy Systems: Many organizations have critical legacy applications that were designed to run on mainframes. Replacing these systems can be expensive and time-consuming, and in some cases, it may not be feasible to migrate these applications to modern platforms.
6. Integration with Modern Technologies: Many mainframe systems now offer modern connectivity options, such as APIs and web services, which make it easier to integrate them with newer technologies and applications.

In summary, while mainframes are no longer the primary platform for many organizations, they still offer unique benefits and advantages for certain applications. Mainframes provide high levels of reliability, security, scalability, and cost-effectiveness, making them an attractive option for organizations with specific needs and requirements.

This seems like a  reasonable response to me. What do you think? With technology this good, I can only imagine how much better it will get as the models are honed over time.

Time to Download the Db2 13 for z/OS Manuals!

Yesterday I posted a brief piece about the new version of Db2 for z/OS that is now generally available: Db2 13 for z/OS is Here! It is always an exciting time when a new version of Db2 for z/OS is unleashed on the world and one of the first things I recommend is to start reading the manuals to see what all is there!

I like having the PDF versions of the manuals on my hard drive, so with each new version, I start by downloading them! With that in mind, here is the link to the IBM page that hosts the PDF manuals for Db2 13 for z/OS. 

Of course, over time, this documentation will be modified. Therefore, it is a good idea to be aware that subsequent modifications may render the versions on your hard drive inaccurate. You can always replace them periodically if you wish... perhaps when you adopt a new function level make plans to downloads the latest iterations of the manuals. 

There is also a great, new redbook on Db2 13 for z/OS that you should download and read. It is titled IBM Db2 13 for z/OS and More, and it, along with the What's New manual, can serve as a nice introduction to this new version.

A new manual that I need to mention is the SQL Data Insights Users Guide. If you read my earlier post (Db2 13 for z/OS is Here!) then you know that SQL Data Insights is a new Db2 13 capability that combines AI/deep learning with Db2 for z/OS and IBM Z technologies to deliver SQL-based semantic queries on tables and views. It is probably one of the most exciting new things in this new version...

So if you work with Db2 for z/OS don't delay... download those new manuals and start learning what new wonders Db2 13 will offer up!

Db2 13 for z/OS is Here!

Here we are, in June 2022, about 5 years or so since Db2 12 for z/OS was released. And lo' and behold, IBM has given us a new version of Db2 for z/OS to learn and adopt: Db2 13 for z/OS. 

The new version is generally available (as of May 31, 2022). If you were not paying close attention though, you may have missed it. Db2 13 was announced at the same time as the new mainframe (IBM z16), so it didn't get quite the same level of attention. But those of us who use Db2 for z/OS day in and day out will find a lot of great new stuff in this latest and greatest version of Db2.

I'm not going to go into great detail about the new features and functionality of Db2 13 for z/OS today, but I will offer a high-level overview. Look for future blog posts to dig into more of the nitty gritty tech details and capabilities.

The first thing to mention is that you will need to activate the last Db2 12 function level 510 (FL510) before you can migrate to Db2 13. As many organizations are lagging behind in terms of function level activation, it will be interesting to see how this requirement impacts migration to Db2 13.

AI

So what can users expect from this new version? Well, it seems that the most talked-about features are related to adopting AI. Functions that deliver AI capabilities into Db2 will make it easier for organizations on the AI journey to integrate Db2 into their processes.

Perhaps the most significant AI addition to Db2 13 is the SQL Data Insights feature. Provided as an extension to Db2, SQL Data Insights is delivered using built-in functions to deliver AI capabilities like uncovering heretofore unknown relationships in your data. Since it uses built-in functions you can use it anywhere that you use SQL!

Db2 13 offers additional AI help delivering the ability to simplify building models, Natural Language Processing (NLP), and exploiting the speed of the IBM z16 for training and querying data.

IBM z16 Synergy

The next thing that has been highly-touted is that Db2 13 takes advantage of new capabilities delivered in the IBM z16 hardware.  The new Telum chip used by the z16 mainframe provides powerful AI capabilities that Db2 uses to bolster its AI capabilities (such as SQL Data Insights). And we have already touched on that in terms of speeding up training and querying data for AI.

Db2 for z/OS is unique in that it is the only major DBMS that is designed specifically for a single operating system (z/OS) and hardware platform (IBM Z). This enables IBM (the provider of the DBMS, O/S, and hardware) to take advantage of capabilities unique to the platform, because there is no worry about supporting other platforms.

One example of this unique synergy is the ability to improve sort performance using the SORTL instruction of the IBM Z15 and z16. Additionally, the IBM z16 System Recovery Boost can minimize downtime by speeding up the performance of Db2 for z/OS restart. 

But What About BAU?

OK, so there is new AI stuff and great synergy with the IBM Z, but what about the features and functionality that make it easier to keep up with Business As Usual (BUA)? You know, things like easier administration, better performance, and so on?

Good news! There are a plethora of great new capabilities and improvements in Db2 13 for z/OS. While I cannot adequately cover them in detail today, some examples include:

• The ability to convert back-and-forth between partition-by-growth and partition-by-range Db2 table spaces. 
• Support for more concurrent threads and open data sets, as well as improved storage conditions. 
• DDF storage relief.
• Real Time Statistics (RTS) improvements.
• Many improvements to IBM Db2 utility functionality.
• Security and compliance improvements, including integration to the IBM Z Security and Compliance Center.

Summary

The bottom line is that there is a new version of Db2 for z/OS that mainframe shops will need to learn and prepare for. As with any new Db2 version, it will be exciting to dig in and discover all of the new stuff that can help us do our jobs better... and improve our organization's efforts to use its data to improve business.

Keep checking back here as I will blog in more detail about the new capabilities of Db2 13 for z/OS over time... 

Thinking About the Mainframe, the Cloud, and IBM Think 2021

A Bit about Think

I am looking forward to attending the IBM Think 2021 conference, IBM's annual flagship technology event. I have attended several in-person Think events, as well as last year’s virtual conference, and I always come away with new knowledge and additional insight into technology and IBM’s vast portfolio of hardware, software, and solutions. The Think conference is always one of the tech highlights of the year for me!

This year’s event, IBM Think 2021, is again being held as a virtual conference, May 11 and 12, 2021. And it is free of charge, which means that you can experience all the great education, presentations, and networking opportunities without having to leave your desk.

My favorite aspect of the Think conference is the breadth and scope of pertinent technical content that it covers. Whether you are a developer, a DBA, a data scientist, a manager, an executive, or any flavor of IT or business specialist, there will be a wealth of useful information presented to educate you and make you “think.”  Be sure to register here.

My Think 2021 Agenda

There are multiple sessions to be delivered at this year’s IBM Think conference that intrigue me because they focus on areas where I specialize.  For example, Dr. Dario Gil, SVP and Director of IBM Research will be delivering a keynote session on IT infrastructure which is sure to be educational. This session, 2081, offers a deep dive into the IBM innovations powering the next generation of hardware, including IBM Z.

Another session I am looking forward to is session 2303 focusing on security “everywhere.” It features IBM luminaries like Tom Rosamilia, Senior Vice President, IBM Systems, and Mary O’Brien, General Manager IBM Security. And Forrester Research Director, Lauren Nelson, will also be lending her industry expertise to the session.

But I think the Think 2021 session I am most looking forward to is The IBM Z roadmap for hybrid cloud and AI (session 1605) featuring Ross Mauri General Manager for IBM Z. Mauri promises to offer a timely discussion on the business value of integrating the IBM Z platform as a full participant into your hybrid cloud. And he’ll speak with Russell Plew, Technology Senior Manager at M&T Bank who will discuss their real-life experiences in doing so!

Why is this session so interesting to me? Well, I’ve worked with the mainframe my entire career, and as anybody who works on the mainframe knows, the IBM Z platform is used to drive mission-critical workloads across all major industry sectors, worldwide. If your organization needs to perform large-scale transaction processing (thousands of transactions per second), support thousands of users and programs concurrently, manage terabytes of information, and handle large-bandwidth communication, chances are you rely on the mainframe to do that because the platform excels at all of those things.

If you’ve ever deposited a check into your bank account, booked a flight on an airline, or used a credit card to purchase something, it is probable that a mainframe was involved in completing that activity!

Ever since Stewart Alsop of InfoWorld predicted the last mainframe would be unplugged on March 15, 1996 there has been a lingering perception that the mainframe would go away at some point. But here we are, 25 years later, and the mainframe is still going strong! At last year’s IBM Think conference IBM presented the following statistics on the mainframe’s ubiquity and power:

●      70% of the Fortune 500 use mainframes and 72% of customer-facing applications are dependent on the mainframe for some or all data processing.

●      Mainframes are designed to be able to process a trillion web transactions a day with the capability to process 1.1 million transactions per second.

●      95% of transactions in the banking, insurance, airline and retail industries are handled by mainframes.

Indeed, the mainframe continues to offer a strong, unparalleled platform for performance, security, and reliability. Of course, the mainframe has changed and grown over its 50+ year lifespan. Today’s IBM z15 is light-years beyond the original IBM System/360 introduced in 1964. Some of the great newer capabilities of the IBM Z include encryptions everywhere with pervasive encryption and Data Privacy Passports, rack-mountable mainframes, Instant Recovery, and cloud-native development. I’m looking forward to hear how IBM’s customers have taken advantage of these, and other capabilities, to integrate the IBM Z into their hybrid cloud architecture.

It only makes sense that businesses relying on the mainframe will continue to do so, even as they embrace cloud computing. This is what the “hybrid” in the term hybrid cloud implies, an IT infrastructure that uses a mix of on-premises and private / public cloud from multiple providers. And this approach makes the most sense because everything can’t shift to the cloud immediately (perhaps ever) because most existing applications were not built with an understanding of the public cloud and it would take a lot of investment to re-engineer them to properly take advantage of a public cloud architecture. And even if you wanted to move everything, cloud service providers (CSPs) can’t build out their infrastructure fast enough to support all the existing data center capacity “out there” to immediately support everything.

So, it will be exciting to watch the IBM continue to innovate on the IBM Z platform as enterprise customers work to integrate Z as a vital component of their hybrid cloud infrastructure. With the large investment enterprises have in their working mainframe applications, large data sets and databases containing crucial data, and high-volume processing requirements they will continue to rely on the mainframe well into the future… and that makes it important to understand how IBM is enabling the IBM Z to participate in your hybrid cloud architecture.

So, join me at Think 2021 for session 1605 to learn how to use your investments in IBM Z and build and modernize applications into container-based workloads using a common DevOps experience. And stick around for other sessions to gain insights on harnessing the full value of IBM hardware, software and services in your organization as you continue to support, manage, and transform traditional business and IT operations.

Automation and the Future of Modern Db2 Data Management

Recently I was invited by BMC Software to participate in their AMI Z Talk podcast series to talk about modern data management for Db2... and I was happy to accept.

Anne Hoelscher, Director of R+D for BMC's Db2 solutions, and I spent about 30 minutes discussing modern data management, the need for intelligent automation, DevOps, the cloud, and how organizations can achieve greater availability, resiliency, and agility managing their mainframe Db2 environment.

Here's a link to the podcast that you can play right here in the blog!

BMC AMI Z Talk · Episode 7: Automation and the Future of Modern Db2 Data Management

Modern data management, to me, means flexibility, adaptability, and working in an integrated way with a team. Today’s data professionals have to move faster and more nimbly than ever before. This has given rise to agile development and DevOps - and, as such, modern DBAs participate in development teams. And DBA tasks and procedures are integrated into the DevOps pipeline. 

And as all of this DevOps adoption is happening, the amount of data we store, and have to manage, continues to grow faster than ever before.

These are just some of the challenges that Anne and I discuss in this podcast... and at the end, Anne even asks me to predict the future... 

I hope you'll take the time to listen to our discussion and sharing your thoughts and issues regarding the resiliency and agility required to succeed with modern data management and Db2 for z/OS.

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I’d also like to extend an offer to all the listeners of this BMC podcast (and readers of this blog post) to get a discount on my latest book, A Guide to Db2 Performance for Application Developers. The link is https://tinyurl.com/craigdb2

There’s also a link to the book publisher on home page of my website. Once you are there, click on the link/banner for the book and when you order from the publisher you can use the discount code 10percent to get 10% off your order of the print or ebook.

 

IBM Think 2020: Virtual, On Demand, Hybrid Cloud and Z

This year’s IBM Think event was quite different than in past years. Usually, Think is an in-person event and attracts a lot of people, typically more than ten thousand IT executives and practitioners. But as we all know, this year with the global COVID-19 pandemic an in-person event was not practical, so IBM held it on-line. And I have to say, they did a fantastic job of managing multiple threads of content without experiencing bandwidth or access issues – at least none that I encountered.

The theme and focus of the content for the event was different, too. Instead of the usual conference focus on products, announcements, and customer stories, this year’s event was more philanthropic. Oh, sure, you could still hear about IBM’s products and customer successes, but the keynote and featured sessions were at a higher level this year.

In the kickoff session, new IBM CEO Arvind Krishna spoke about the driving forces in IT as being hybrid cloud and AI. And he spoke about these things in the context of moving IBM forward, but also how they can be used to help healthcare workers combat pandemics like we are currently experiencing.

In another keynote, IBM Executive Chairman Ginni Rometty spoke with Will.i.am (of the Black-Eyed Peas) about making the digital era inclusive through education, skills development, and the digital workforce.

And then there was Mayim Bialik’s session on women and STEM, which was sincere, heartfelt, and entertaining. 

For those who don’t know who she is, she is the actress who played Blossom (on Blossom) and Amy Farrah Fowler (on The Big Bang Theory)… but she is also a scientist with a doctorate in neuroscience. Bialik’s session focused on putting a positive female face on STEM, something that is definitely needed!

So, what about the technology side of things? Well, you can take a clue from Krishna’s assertion that IBM as a company has to have a “maniacal” focus on hybrid cloud and AI in order to compete. But the company has a rich and deep heritage across the computing spectrum that gives it a key advantage even as it adjusts to embracing hybrid cloud and AI.

The first thing to remember is that IBM uses the term “hybrid multicloud[RB1] ” very specifically and deliberately. Everything is not going to be in the cloud[RB2] . Large enterprises continue to rely on the infrastructure and applications they have built over many years, many of them on z Systems mainframes. The key to the future is both on-premises and cloud, and IBM understands this with its hybrid cloud approach… as they clearly demonstrated at Think 2020.

My specific area of focus and expertise is the mainframe and Db2 for z/OS, so I sought out some sessions at Think in those areas. Let me tell you a bit about two of them.

First let’s take a quick look at how IBM Cloud Pak for Data can work with data on the Z platform. This information was drawn from IBM Distinguished Engineer Gary Crupi’s session, titled "Drive Actionable, Real-Time Insight from Your High-Value IBM Z Data Using IBM Cloud Pak for Data."

What is Cloud Pak for Data? Well, it is an IBM platform for unifying and simplifying the collection, organization, and analysis of data. Heretofore, it was mostly focused on non-mainframe platforms, but the latest release, version 3.0, is a major upgrade with an enhanced unified experience, expanded ecosystem, and optimized Red Hat integration. And it enables several ways for you to turn your enterprise data on IBM Z into actionable, real-time insight through the integrated cloud-native architecture of IBM Cloud Pak for Data.

Crupi’s session started out with the now familiar (at least to IBM customers and Think attendees) Ladder to AI and how Cloud Pak for Data helps to enable customer’s journey up the ladder. Data is the foundation for smart business decisions and AI can unlock the value of this data.

He went on to discuss the continuing importance of the mainframe providing facts including:

•  70% of Fortune 500 companies use mainframe for their most critical business functions
•  72% of customer-facing applications are completely or very dependent on mainframe processing
•  The mainframe handles 1.1 million transactions per second (as compared to Google experiences of 60,000 searches per second)
•  95% of transactions in the banking, insurance, airline and retail industries run on the mainframe

These are all good points; and things that mainframe users like to hear. It is good to see IBM promoting the ubiquity and capabilities of the mainframe.

Now, what about IBM Cloud Pak for Data better-exploiting mainframe data? Crupi goes back to the AI Ladder to talk about z/OS capabilities for analyzing and collecting data for AI.

Solutions such as Watson Machine Learing for z/OS, Db2 AI for z/OS, and QMF can be used for analyzing data; while Db2 for z/OS and Tools, IDAA, and Data Virtualization Manager can be used for data collection. These things already exist, but using them effectively with distributed platform capabilities will be crucial to be able to climb the ladder to AI.

IBM Cloud Pak for Data will leverage IBM Z technology to bring valuable IBM Z data into a modern analytics/AI platform. It can now exploit IBM Z data and resources where appropriate enabling you to further benefit from IBM Z technology and data.

A key new component of making the data on IBM Z accessible is IBM Db2 for z/OS Data Gate, a new product announced during Think 2020. Db2 Data Gate can help you reduce the cost and complexity of your data delivery with a simple, easy-to-deploy mechanism to deliver read-only access to Db2 for z/OS data. Instead of building and maintaining costly custom code, Db2 Data Gate do the work. Data can be synchronized between Db2 for z/OS data sources and target databases on IBM Cloud Pak for Data.

Instead of accessing data in the IBM Z data source directly, an application accesses a synchronized copy of the Db2 for z/OS data, hosted by a separate system. This target system can be established anywhere Cloud Pak for Data is supported, thus enabling a wide range of target platforms that include public cloud, on-premises, and private cloud deployments.

So IBM is helping you to expand the accessibility of your Z data.

And that brings me to the second session I’d like to briefly mention, Automate Your Mainframe z/OS Processes with Ansible [Session 6760]. 

Although Ansible is not a replacement for your operational mainframe automation tools, it can be used to communicate with and automate z/OS using the out-of-the-box SSH into z/OS Unix Systems Services to execute commands and scripts, submit JCL, and copy data. And Ansible has existing modules that can be used to make calls to RESTful/SOAP APIs that are available in many z/OS products.

Ansible can be beneficial to orchestrate cross-platform, including Z systems, and to simplify configuration and deployment management. But keep in mind that Ansible is a proactive framework for automation and is not intended to replace automation solutions that monitor and react.

Here is a nice, but by no means exhaustive, list of examples showing how Ansible can be used to interact with popular z/OS products.

The Bottom Line

The IBM Think 2020 conference was a great success considering how rapidly IBM had to move to convert it from an in-person event, to an online, virtual one. And the content was informative, entertaining, and had something for everybody. I hope you enjoyed my take on the event… feel free to share your comments below on anything I’ve written here, or on your experiences at the event.

My Thoughts on Think

Last week I had the great pleasure of attending the IBM Think 2019 conference in San Francisco. There were many great sessions and content covering my interest areas, including AI, machine learning, analytics, data governance, Db2, digital transformation, and more. 

Part of the difficulty of attending such an event is deciding what to attend from a list of competing, interesting topics. And another is trying to piece together everything you hear into a cogent, comprehensive message. 

Instead of writing down all of my thoughts I decided to make a quick video on YouTube summarizing my takeaways from the conference. Let me know what you think...

Making Plans for IBM Think 2019

I'm looking forward to once again attend IBM Think, IBM's flagship technology conference. I attended the inaugural Think conference and it was one of the highlights of the year (2017). This year IBM Think is being held in San Francisco February 12 thru 15 at the Moscone Center and surrounding hotels. San Francisco is a wonderful location because it will give the conference more room to accommodate the large crowds more comfortably than the Las Vegas venue of 2017.

One of the great things about Think is the breadth and scope of pertinent technical content that it covers. So whether you are a developer, a DBA, a data scientist, a manager, or any flavor of IT specialist, there will be a plethora of useful sessions and activities to educate and make you “think.”

Now you all know that my primary background is database administration and Db2, but I also work with and have interest in many other technologies, including data governance, security and data protection, DevOps, machine learning, AI, blockchain, quantum computing, and cloud computing. And the great thing about the IBM Think conference is that it provides in-depth coverage of all of these areas, and more.

A big struggle for such a large event (expected attendance in excess of 30,000) is finding what you need. Well, IBM Think makes it a bit easier because it is broken down into campuses that focus on a specific areas. This year’s campuses include:

• ·         Smarter Business Showcase
• ·         Data & AI Campus
• ·         Cloud & Infrastructure Campus
• ·         Security & Resiliency Campus

There will be more than 2,000 business strategy sessions and technical deep dives over the course of the week, along with professional development opportunities from 100s of hands-on labs and certification exams.

One of the big highlights of IBM Think is always the great speakers, and this year is no exception. From IBM speakers like CEO Ginni Rometty and Sr. VP Hybrid Cloud Arvind Krishna, to industry speakers like Founder & CEO of Mogul Tiffany Pham and AT&T CEO John Donovan, to researchers like MIT Media Lab and Harvard research specialist Dr. Kate Darling, to entertainers like Super Bowl MVP Joe Montana and skateboarding legend Tony Hawk, there will be a lot of knowledge imparted. I’m particularly looking forward to hearing Paul Cormier, EVP and President of Products and Technologies at Red Hat to hear how the IBM / Red Hat combination is working.

Another advantage of attending IBM Think is the access to exclusive information about IBM products, technologies, strategies, and services that are sure to be shared during the event. IBM always unveils a ton of great stories and technologies at Think.

I’ll be live-tweeting at IBM Think 2019, so be sure to follow me at twitter.com/craigmullins so you can experience Think right along with me, as it happens. Some of the sessions I plan on attending include topics on governed data science, using machine learning to prioritize business issues, and Db2 on cloud... but those are just the tip of the tech iceberg.

And finally, it is not too late. Click here if you want to attend IBM Think 2019… If you do, maybe I’ll see you there amongst 30,000 of our IT friends!