Tag Archives: Mainframe

Mainframe Meets Machine Learning and Artificial Intelligence at SHARE Sacramento

Winter SHARE 2018 was held in Sacramento, California the week of March 12th. Throughout the years the scope and tone of the SHARE conference has changed based upon the technologies everyone is discussing. In the past, it was focused on the mainframe and how to better manage your environment. This year, SHARE was focused on emerging technologies that can be used to manage and monitor your environment. The most talked about next-generation tech being Machine Learning and Artificial Intelligence. As I listened to the sessions, I it became clear that Machine Learning is where many of the attendees were particularly focused.

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A Common Thread between SHARE and Computer Measurement Group

This is the fourth SHARE conference I have presented at with different organizations. For years, I have presented at a number of different conferences, both national and regional. Each conference has its own flavor and target audience. Many of the individuals that go to SHARE would not go to the Computer Measurement Group (CMG) event and vice versa. That said, this year, I came to present a topic that would be of interest at either event… the Changing Landscape of Capacity Management for the Mainframe. The basis of the topic is how Mainframe capacity managers need to ensure they are looking at the process from a business standpoint rather than just as a technical application.

Capacity Management’s Role in Machine Learning

So where does Capacity Management fit into the white hot new trend of Machine Learning? By definition, Machine Learning is “a field of computer science that gives computer systems the ability to “learn” with data, without being explicitly programmed.” Therefore, the key is to provide enough meaningful data for Machine Learning capabilities to automate into analytics. Capacity Management delivers a vast amount of information about IT resources and their utilization, including enabling machine learning programs to perform analytics in the background for the reporting of “Time to Live” until a resource is exhausted. The key to the performance of this analysis is the setting of thresholds, whether those thresholds are static or self-learned.

Self-Learning thresholds is where Capacity Managers want to get to within their environments. One of the discussions that was held at SHARE was focused on whether, with machine learning, we are eliminating the human factor. My answer to that statement is that we can never eliminate the human factor. There are dynamics within the environment that a machine cannot account for in its processing and learning. As we say many times, humans can do things we never have planned for with the software. There will continue to be analysis that must be performed on the reports to ensure a variable is not missed. Syncsort, with software products like Athene and Ironstream with Splunk is using this type of technology to enable this type of machine learning. Over the next twelve months I think this area will be one with large scale growth. The key to making this work is to ensure the quality of the data that is gathered, and having it correlated with the technical and business data. The business and application view is what organizations are looking to display on dashboards for all levels within the enterprise.

One of the benefits of going to a conference is seeing what the vendors are presenting in the exhibition hall along with meeting up with friends and former colleagues from the past. At each conference, you have the stalwarts including Syncsort, BMC, ASG, IntelliMagic, Velocity and IBM. Every year there are some new companies that show up at the shows. Throughout my long career, I have either worked with many people in the exhibition hall or know them from the industry. The nice feature about the technical aspect in the relationships is that we talk about the how our jobs are changing within the industry and the new technologies affecting us.

Conferences such as SHARE continue to provide a great venue for all attendees to share thoughts and insights about what’s changing and what technologies can help address the challenges and opportunities that come with that change.

Download our free eBook, “Mainframe Meets Machine Learning“, to learn about the most difficult challenges and issues facing mainframes today, and how the benefits of machine learning could help alleviate some of these issues.

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New eBook! 50 Years of Mainframe Innovations: Observations From a Long-Time Mainframer

Over the past five decades, the focus for the mainframe has been on bigger, faster and cheaper processing power. This is no surprise, considering the technology advancements that have occurred. In Syncsort’s new eBook, “50 Years of Mainframe Innovations: Observations From a Long-Time Mainframer“, Ed Hallock talks about how amazing the past 50 years has been for the mainframe, with unbelievable advances in technology and business practices.

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Not only have mainframes evolved, but organizations have evolved as well. That said, organizations struggle today with supporting growth, controlling IT budgets and costs, and ensuring the security of their IT infrastructure against potential threats and attacks.

Download the eBook today to learn more about what was observed.

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Maximizing Mainframe Visibility

Do you have a mainframe visibility problem? If so, you probably also have mainframe security and performance problems. Here’s how to improve visibility for your mainframe.

In IT, visibility means an understanding of what is happening in your systems and infrastructure.

Visibility is important because it provides the foundation for making informed decisions about security, performance optimization and the expansion of your infrastructure. If you lack visibility, you’re shooting in the dark when it comes to managing your hardware and software.

Ideally, visibility will be continuous, meaning it is ongoing and there are no gaps in your ability to work with your systems.

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Overcoming Mainframe Visibility Hurdles

The tricky thing about visibility is that there is no one-stop solution for achieving it. An effective visibility strategy requires a mix of tools and processes. And it must be tailored to your organization, of course.

Visibility is also challenging to achieve because having visibility into one part of your infrastructure does not necessarily mean the rest of it is visible, too. You may do a great job of maintaining visibility into your storage systems but have much less visibility into front-end software, for example. Or you may have maximum visibility into commodity servers but none for your mainframes.

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How do you address these challenges, particularly when you are working with a mainframe? The following tools and strategies can help you to overcome common mainframe visibility challenges:

  • Real-time system monitoring

Monitoring tools alert you to performance and availability issues as they occur, so that you have a decent shot of addressing them before they impact operations. Mainframe monitoring tools like Syncsort Ironstream Dataset Analyzer can be integrated with Splunk to provide easy visualization and interpretation of monitoring information.

  • Security monitoring

General-purpose mainframe monitoring tools may provide some security insights, but to maximize security visibility for the mainframe you should use a dedicated security monitoring solution. Syncsort’s ZEN Suite provides mainframe security monitoring.

  • Network monitoring

Optimizing mainframe performance requires you to keep tabs on your network, too. Mainframe network monitoring is another feature of Syncsort’s ZEN Suite.

  • Log analysis

Logs can enable both real-time and historical visibility into your systems. They can help you detect problems as they occur, as well as investigate issues after the fact. Because mainframe log data is so vast, analyzing mainframe logs manually is usually not feasible. Instead, log aggregation and analytics tools provide the insight you need. For guidance on leveraging mainframe logs, check out Syncsort’s whitepaper on the topic.

  • Organizational visibility

In addition to monitoring and analyzing your mainframe itself, full visibility requires taking into account the organizational context of the mainframe. Understand who is responsible for maintaining the mainframe, who is on-call when something goes wrong and who has access to it. Having this information on hand ensures that you can troubleshoot issues as quickly as they arise.

Again, your mainframe visibility strategy should be tailored to your infrastructure and organization. In general, however, the tips above should help you achieve the continuous visibility that you need to keep your mainframe lean, mean and running well.

For more on the mainframe, download our 2018 State of the State of the Mainframe report and learn what every business needs to know about Big Iron in a Big Data world

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Webcast: Key Mainframe Trends for 2018

The results from Syncsort’s annual State of the Mainframe survey are in! Professionals from Financial Services, Health Care, IT, Government and more have weighed in on which key mainframe trends are most important to them.

Our latest webcast, “Key Mainframe Trends for 2018” takes an in-depth look at the survey results and speaks about five mainframe trends to watch for in 2018.

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In addition to those trends, you’ll also learn the importance of:

  • Investmenting in the mainframe
  • Modernizing mainframe environments
  • Meeting security and compliance requirements
  • Using mainframe data from Big Data analytics

Check out the on-demand webcast now and see what this year’s results have brought in.

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Capacity Management: How to Keep Your Mainframe Cruising

Businesses and IT organizations are changing, but the mainframe continues to be an important hub of business activity. Mainframe capacity management can ensure effective and efficient operation to help you maximize your return on investment and keep customers happy well into the future.

Meeting Enterprise Operational Needs

A friend of mine bought a 20-foot boat last summer so he could take his family tubing, water skiing, and fishing.  It’s fast, fairly easy to operate, and relatively inexpensive to fix and maintain.  One person can do most of the tasks required to get the boat in and out of the water and it doesn’t take long to learn how to do most tasks involving a small craft like his.

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This summer, my family is planning on spending a week’s vacation on a cruise liner. In doing some research, I found that the boat, at top speed, is only half as fast as my friend’s 20-foot boat and common sense (and a very long 1996 movie) tells me that the ship can’t turn nearly as quickly in the water. And it takes thousands of people to make a cruise ship do what it does, from deck hands and entertainment staff all the way up through the ship’s captain.

In other words, a novice may be able to keep a speedboat running, but that doesn’t mean he knows how to handle a cruise liner. But when managed well, a cruise liner is a smoothly operated vessel that will make thousands of people satisfied customers.

A mistake in the operation of that speedboat will make a few people unhappy or put a few people at risk, while a mistake in the operation of the cruise liner could affect thousands of people and risk the health and future of the operating company.

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Changing Course with Mainframe Capacity Management

Think of the mainframe as that cruise liner.  Many organizations have invested a lot of time and money into making sure that the mainframes are operating at peak efficiency – much of that knowledge, however, is held within long-tenured, very experienced employees who may be thinking about buying their own fishing boats and heading into retirement.

More specifically, does the end of working life for the baby boomer generation mean problems for the many businesses for which the mainframe is still the most mission-critical server?

Like the cruise ship, changing course with a mainframe requires planning, expertise, and resolve. Organizations have been talking about replacing the mainframe for decades, but find it is still the most efficient and most secure data processor around. Today, without customers even knowing, it is the backbone for customer-facing, web-enabled applications and services. The mainframe isn’t going anywhere. But those mainframe experts might be, and organizations have to plan for that possibility.

The story sounds dire, but it doesn’t have to be. athene®, Syncsort’s capacity management software, provides automation around key processes and requires little-to-no mainframe expertise to operate in a cost-effective manner.

As a cross-platform solution, athene allows organizations to bring data into a centralized Capacity Management Information System (CMIS) from all components that comprise a service and provides a 360° view of those services in a single dashboard. It also has predictive analytics that give organizations insight into how the mainframe is performing today and will perform in the future, even with changes in the hardware or the workload.

Evaluate your mainframe capacity management process and keep it sailing smoothly – take our Maturity Survey today! Answer 20 quick questions about your organization and its processes, and you’ll immediately receive an initial maturity level as well as a comprehensive report with suggestions on how to improve your maturity.

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New eBook! State of Mainframe Operational Intelligence for 2018

We’ve recently completed our annual mainframe operational intelligence surveys of IT and data analytics professionals to identify trends, challenges and opportunities faced by enterprises investing in mainframe and Big Data technologies going into 2018. Respondents represented a wide range of IT disciplines and spanned vertical industries including financial services, insurance, health care, IT and government agencies.

Our latest eBook, State of Mainframe Operational Intelligence for 2018, takes a look at the current state of the mainframe within organizations and what professionals are looking to do moving forward.

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While organizations are looking for ways to optimize mainframe resources, reduce costs and re-invest the savings in newer technologies and use cases, they still rely on these systems for their most critical applications.

Download the eBook now and see the top objectives respondents identify for their mainframe environments.

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How to Make Everyone Love the Mainframe

Many people inside your company may never think about your mainframe. But they should if you want to put your mainframe computers to the best use. Here’s how to help your employees understand and appreciate your mainframe.

To most people at your company, your mainframe is an obscure, enigmatic machine. Few employees ever see it or interact with it. Many probably don’t even realize it is there.

Those who do might mistakenly assume that it is a “supercomputer” that they’ll never understand – even though, in reality, there is a big difference between mainframes and supercomputers.

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Why Your Employees Should Love Your Mainframe

It may not seem to matter much whether your employees understand your mainframe or not. If they don’t work directly with it, who cares what they know about it – right?

Wrong. In reality, getting your employees to understand your mainframe matters just as much as having them understand any other part of your business.

Mainframes remain central to business operations in many industries, from banking and insurance to transportation. If your employees don’t understand what your mainframe does and why it matters, they won’t be able to help your business derive maximum value from it.

The importance of having everyone understand and appreciate the mainframe is analogous to ensuring that all employees in a trucking company have a basic understanding of the logistics challenges that the business faces every day, or of making sure that everyone who works for a bakery understands which products it offers.

This may not seem like crucial information for employees who work in, say, accounting, or who run a cash register. But it is important for these people and everyone else to understand the core parts of the business. It will help them to feel more attached to the company, and it will ensure that they understand the rest of the business in case they ever have to step outside of their usual job duties.

Teaching Employees about the Mainframe

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So, how do you actually ensure that employees understand and appreciate the mainframe? Communicating the following information to them is key:

Which types of data the mainframe stores

You need not be a data scientist to understand basic information about the types of data – like credit card transactions or vehicle routing data – that are stored on the mainframe. When employees have a concrete sense of what the mainframe actually does, they’ll appreciate it much more.

What modern mainframe computers look like

Dispel the myth that all mainframe computers are decades-old computers stored in dark rooms lit only by green screens. Explain to your employees what your mainframe or mainframes actually look like, and how many commodity servers it would take to equal the mainframe’s computing power.

The challenges your mainframe operators face

Explain in non-technical terms the types of challenges that your technical team faces in working with mainframe commputers. For example, help employees understand that not all data is stored in the same format, and that converting data from one format to another is often a challenge when working with mainframe data.

Mainframe’s role in real-time analytics

Communicate the importance of real-time data analytics and the role that mainframes play in providing that insight for your company. It’s pretty easy to understand why real-time data analytics are so much more useful than historical data.

How much mainframes cost, and how much they save your business

Your employees might assume that maintaining mainframes is cost-inefficient. Help them to understand the business value of mainframes by explaining how much one costs to acquire, how long it can be expected to last and how its acquisition and operating costs compare to those of commodity servers (which in many cases are more expensive in the long run).

The differences between mainframes and the cloud

Some employees might think that mainframe computers are just a legacy version of the cloud. After all, both mainframes and the cloud are used to store large amounts of data in places that few people ever see. But on-premise mainframes are different from the public cloud, of course. They provide performance, scalability and compliance advantages that your employees should understand.

Mainframe security challenges

Mainframes present unique security challenges. Ensuring that your employees have a basic understanding of what those challenges are and strategies for mitigating them will help to improve your company’s overall security.

For more tips on how companies today are using mainframes and the type of information employees should understand about them, download Syncsort’s State of Mainframe for 2018 report.

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Building a Mainframe Disaster Recovery Strategy

Your mainframe may not be at the forefront of your mind when you’re planning for disaster recovery. But it should be because getting your mainframe back up and running quickly is essential for maintaining business continuity following a disaster.

When it comes to disaster recovery preparation, mainframes present some unique challenges. For one, it’s not usually practical to set up a secondary mainframe in a remote location to serve as a backup system, as you would do with commodity servers. That would be too expensive.

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It is also difficult to back up mainframe data to the cloud or remote servers in a straightforward way. Unlike commodity servers, mainframes run operating systems and applications that often cannot be easily moved to non-mainframe systems.

At the same time, of course, you can’t simply leave your mainframe out of disaster recovery planning. Doing so will deprive you of the essential services that your mainframe hosts, leaving you poorly equipped to recover quickly following a disaster.

This is why, if you have a mainframe, you need to spend time developing specific plans for mainframe disaster recovery. Don’t wait until you’re in the midst of a crisis to start figuring out how to get your mainframe up and running again.

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Mainframe Disaster Recovery Preparation

The following tips and strategies will help ensure that your mainframe is as well prepared for recovery from a disaster as the rest of your infrastructure:

Offload data routinely

Because you likely can’t set up a backup mainframe system, it’s important to make sure that you offload data routinely from your mainframe to other servers. Routine, ongoing offloading will provide backups of your mainframe data.

Back up tapes offsite

Depending on how you offload your mainframe data and where the offloaded data is stored, you may also want to make copies of your tape drives and move the copies to an offsite location. The tape backups will provide a secondary set of data – and a set that is easy to load into any mainframe – that can be used for recovery if necessary. See also: 3 Tips for Leveraging Existing Infrastructure for Backup

Be able to transform data

Backing up mainframe data is not enough to ensure that you can recover quickly from a disaster. You also need to ensure that you can transform data quickly in order to make it usable in whichever tools or environments you use to analyze it.

Take advantage of virtualization

Where possible, take advantage of mainframe virtualization features to run workloads in Linux environments rather than on native mainframe operating systems.

This may not be practical for all workloads, of course. But because Linux workloads are easier to port from a mainframe to a commodity server, using Linux on your mainframe where possible will help to ensure that you can get mainframe applications back up and running quickly in the event that your mainframe becomes unavailable.

Use data replication

Where possible, be sure to take advantage of automated data replication features on your mainframe. Data replication copies data to multiple disks so that if some disks fail, the data is not lost. Of course, data replication will not protect you from a disaster that totally destroys all of your disks. But it can provide assurance against small-scale disruptions that harm only part of your infrastructure.

Spread out your mainframe

Although we tend to talk about “the mainframe” as if every mainframe is a single, indissoluble machine, in reality, many mainframe infrastructures are composed of multiple pools of storage and compute resources.

Consider spreading these resources out across your campus, or even between multiple sites if possible. Doing so will help to ensure that a physical problem that disrupts part of your mainframe infrastructure will not destroy all of it.

When it comes to implementing these strategies, Syncsort can help. Syncsort provides the data cleansing, transformation and integration solutions for mainframes that organizations need to keep their mainframe data and applications safe from destruction during an unexpected event.

For a broader look at trends around disaster recovery, check out our new report – The 2018 State of Resilience – we review the results of an industry-wide report on how organizations are strategizing to sustain severe shocks, protect information, and enable the insight and intelligence required to stay competitive.

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Mainframe Cost Reduction Tips to Maximize Your Data Infrastructure ROI

Getting the most from your mainframe requires not just taking advantage of technologies like containers or integrating your mainframe into DevOps workflows. You also want to optimize around mainframe cost reduction. Keep reading for five tips for lowering your mainframe costs.

If you know anything about mainframes, you know they are a big investment. Prices for a new mainframe start in the tens of thousands of dollars, and can easily reach into six figures – for just a single computer.

Compare that to a commodity x86 server, which might cost you $ 2,000 at the high end, and it’s obvious that mainframes entail a pretty hefty monetary commitment.

5 Mainframe Cost Reduction Tips

With such a large commitment comes a need for cost optimization. If you want to maximize your mainframe ROI, you’ll be on the lookout for strategies that can help you reduce mainframe setup and operating costs, such as those detailed below.

mainframe Mainframe Cost Reduction Tips to Maximize Your Data Infrastructure ROI

1. Virtualize Your Mainframe Workloads

Although commodity servers have supported virtualization for a long time, mainframes continue to offer unparalleled support for virtualized workloads. IBM promises that a single mainframe can support as many as 8,000 virtual machines. You’d be lucky if you can run eighteen virtual machines on a commodity server.

When planning your mainframe architecture, strive to take full advantage of virtualization. Virtualization makes workloads more portable and scalable and helps ensure that your mainframe’s capacity is not under-utilized.

2. Consider Linux for Mainframe

One of the most powerful features of mainframes is their ability to run Linux-based software environments, as well as native mainframe environments.

Taking advantage of Linux as a host environment for some of your applications on your mainframe can significantly reduce your overall operating costs — especially because Linux on the mainframe makes it possible to move some of your applications from commodity servers onto your mainframe.

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3. zIIP and zAAP Your Mainframe Workloads

One of the most significant recent advances in mainframe hardware is IBM’s release of zIIP and zAAP processors for z Systems. These are special processors that are optimized for certain kinds of workloads, such as databases and encrypting network traffic.

Because zIIP and zAAP processors are less expensive, they can help to lower your mainframe hardware acquisition costs without compromising performance. By sending appropriate workloads to zIIP and zAAP processors, and saving your more expensive mainframe processors for other types of tasks, you get more bang for your mainframe buck.

4. Modernize Your Mainframe Applications

You may be running mainframe applications that were written decades ago. Their code can be modernized to run more efficiently by taking advantage of modern mainframe hardware, running more tasks in parallel and so on.

If you’re thinking that modernizing your mainframe applications requires an expensive and time-consuming overhaul of their codebases, think again. It’s possible to refactor your mainframe software without rewriting it. In fact, some vendors even offer automated refactoring solutions targeted at mainframes.

Investing in a little application modernization can do much to make your applications run more efficiently.

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5. Automate, Automate, Automate!

Any task – whether it involves a mainframe or a different part of your infrastructure – that is performed manually is bound to be time-consuming and costly. That’s why automation is king when it comes to optimizing costs.

On your mainframe, opportunities to automate center on areas like data offloading and transformation, or integrating data and applications with the rest of your infrastructure.

Next Steps: Learn More About Mainframe Optimization

For even more specific actions you can take toward mainframe cost reduction, watch this insightful webinar:

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The Future of Mainframe Optimization

In this IBM Systems Magazine webinar, you’ll learn about key mainframe optimization problems, opportunities, and use cases. Discover how the latest innovations for zIIP and sort will save you both time and money, game-changing features of workload-centric database optimization for DB2 and IDMS, and new solutions for long-standing network management issues.

Watch the IBM Systems Magazine webinar now >

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2017 Mainframe Trends that are Here to Stay for 2018: Docker, Blockchain, z14 and Beyond

Mainframes are still going strong as 2018 begins. Need proof? Keep reading for a look at the biggest innovations and developments to hit the mainframe world in the past year.  These five mainframe trends are expected to continue to impact the mainframe community in 2018.

Ask an everyman to tell you about mainframes, and you’ll likely hear that they went out of fashion decades ago.

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In fact, however, as these mainframe trends show, the ecosystem remains alive and well, and continues to see new ideas and trends on par with innovations that stretch across the IT world as a whole.

Docker Containers Come to Mainframes

Technically, it has been possible to run Docker on mainframes using a DIY approach since Docker debuted in 2013. Docker works on any Linux-based operating system, and Linux can run on mainframes.

In August 2017, however, Docker support for mainframes became official. Mainframes are now a bona fide part of the Docker ecosystem, benefitting from the agility and efficiency advantages that containers offer.

IBM z14 Announced

Mainframe hardware continues to evolve, as IBM showed when it announced the z14 system in July 2017.

Z14 is the latest, greatest version in IBM’s z family of mainframes. It expands upon the features of z13, which debuted in 2015.

Z14 offers a number of innovations in the security realm in particular.

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Z Systems Sales Decline

Notwithstanding the z14 announcement, sales of z Systems overall declined in 2017.

Is this a sign of the impending collapse of the mainframe industry and the irrelevance of mainframe skillsets? Hardly.

The z Systems sales decline was due in part to the fact that previous quarters saw high z Systems sales rates. Maintaining that pace indefinitely was not feasible.

Plus, even if mainframe sales were to decline, people with the skills to migrate mainframe workloads to other types of servers will be in high demand. Any company that chooses to divest itself from mainframes will need to embark on a complicated journey, which will only succeed with the help of seasoned mainframe admins.

Blockchain Comes to Mainframes

The world of blockchain technology evolved significantly in 2017, and mainframes have been a part of the picture. Over the course of the year, vendors like IBM have been increasingly active in promoting mainframes for hosting blockchain workloads.

Expect this trend to continue as blockchain technology — which includes but is certainly not limited to the Bitcoin cryptocurrency platform — continues to expand.

More Interest in Software-Defined Mainframe Environments

One of the biggest trends in the IT world over the past several years has been the shift toward software-defined everything.

Rather than running applications and storing data directly on hardware, organizations are increasingly using virtual environments that abstract the underlying hardware away. This provides more flexibility.

The software-defined everything trend is impacting mainframes, too, by enabling companies to move workloads from physical mainframes to software-defined mainframe environments — as Swisscom started doing in 2017, to cite one prominent example.

Such moves don’t mean the mainframes are going away. You still need to understand mainframe applications and architectures in order to administer these workloads. But the way that mainframe hardware and software interact is becoming more flexible.

Want to learn more about current mainframe trends? Check out our 2018 State of the Mainframe report to see key trends to watch for in 2018 as well as IT professionals’ top objectives for improving performance and saving money over the next 12 months.

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