Monday, December 11, 2017

IBM POWER9 breaks barriers that hamper AI solutions

By Bill Moran and Rich Ptak

On December 5, IBM announced POWER9, its newest Power System. The POWER9 title might be taken to imply it is just another POWER8 iteration with a performance boost and a few new features thrown in. Not so. POWER9 is a significant generational advance, providing much more than a minor turn-of-the-crank. These next-generation Power Systems embed leading edge new technologies, such as PCI-Express 4.0, next-gen NVIDIA NVLink 2.0 and OpenCAPI more about these later. The new server, AC922 is the base platform for the CORAL collaboration, the world’s most powerful supercomputer. 
With this announcement, IBM marks a major change-of-direction as it targets compute intensive the super-computing and AI workloads used for modeling, research, credit risk analysis, etc.  Workloads requiring LOTs of memory, extremely high processing speeds and analyze vast amounts of data. We comment on this and its implications.

POWER9 enhancements

First, a description of the improvements over prior iterations. Skipping the “speeds and feeds”, here are a few important points.
·         POWER9 chips are 14nm technology; a significant advance over last generation’s 22nm. IBM no longer controls a chip foundry having sold it to Global Foundry. However, the Global Foundry – IBM alliance is clearly working effectively and delivering products in a timely manner
·         POWER9 architectural changes yield many improvements. These include a new implementation of OpenCAPI 2.0, that delivers a major improvement in I/O capacity as it speeds bandwidth by a factor of 4 over CAPI[1] in POWER8. Implementation of PCI-Express 4.0 and next-gen NVIDIA NVLink 2.0 means that data flows in and out of the system more quickly. Complex data analysis, simulations and model building/evaluations complete faster. Programming is simplified.
·         POWER9 enhances links between system CPUs and the GPUs. Experience has proven that pairing GPU devices with the CPU can yield dramatic operational improvements. POWER9’s new links increase bandwidth speeds by a factor of 7 - 10 times to benefit data manipulation and analysis.
Connections between the GPUs and system memory is simplified and improved. Thus, AI models run faster, programming is simpler, and this permits quicker creation and evaluation of more complex and larger models for AI, data analytics, research etc. Learning times are also dramatically reduced.
These features and new architecture mean the POWER9 is a strong competitor as it delivers performance improvements that are much needed in AI and supercomputing market segments.

A new Server

But, chip level and design specification improvement tend to be of limited interest to many potential customers. They tend to evaluate a new chip or processor in the context of the product they will purchase. They want to know how they or their projects benefit from the AC922 POWER9 processor-based server.
Detailed specs for the AC922 server appear in IBM’s material.  But, IBM also provided some benchmark runs comparing AC922 to an Intel X86 server. Two AI workloads, Caffe and Chainer[2]  were run. For both workloads, AC922 out-performed the X86 system by approximately 3.7 times. The X86 system is a standard environment. We expect Intel will be enhancing x86 with AI capabilities at some point.
We like the benchmarks that IBM ran. They effectively demonstrate the impact of system improvements in actual application. Paper and pencil comparisons are fine; but nothing equals the actual performance a system delivers with a real workload. The initial air-cooled server will be followed in 2018 by a faster, water-cooled version. The air-cooled servers have a maximum of 4 GPUs; the follow-on water versions allow up to 6 GPUs.

Supercomputer Heaven

CORAL is a supercomputer that is being built for the US DOE with various Oak Ridge, Argonne and Livermore labs. CORAL will be the most powerful supercomputer in the world when deployed in 2018. It is expected to deliver 10X the power of Titan, today’s supercomputer leader. Very impressively, the building block for Coral is a standard AC922, now available for purchase. This provides normal customers the ability (if not the resources) to build their own version of a CORAL-type supercomputer around multiple AC922s. We believe many customers, e.g. weather bureaus, modeling researchers, etc., will be interested in constructing such systems. These deployments will verify AC922’s increased operational and programming simplicity, versatility, robustness and scalability.

IBM’s new direction 

IBM has changed the direction of its Power System marketing. In the past, Power Systems were promoted as a general-purpose Linux server in direct competition with Intel servers. Intel dominated the distributed server market (albeit with Windows) for decades. Windows-based systems would have to convert from Windows to Linux to use Power. As such conversions are generally viewed as risky, customers were far more likely to just continue to upgrade to the latest version of Intel. Even customers installing Linux were more likely to do so on an Intel platform, supplied by HP or Dell. Thus, IBM Power Systems, despite significant advantages in processing performance, capacity and I/O handling faced powerful resistance to change which worked against achieving significant market penetration.
Now, with Power9, IBM sees in the new area of AI an opportunity that plays directly to their architectural and performance advantages. Power9 systems were designed to deliver maximum performance with AI workloads and models. They will still compete with Intel, but on a more level playing field in a rapidly growing and diverse market. Both companies will have to compete with very attractive Cloud offerings. IBM believes there exists sufficient demand for on-premise computing to support a profitable business.  Although many, if not most, Cloud servers are x86 based, IBM believes they can deliver a sufficient performance edge to justify keeping AI projects on-premise.  Initial benchmarks suggest that they may be right, although maintaining that edge will remain a challenge.


We think that IBM has delivered a powerful new answer for anyone searching for a production AI platform. It has the right combination of hardware and software technology to succeed. It has other strengths including Open Power foundation support, enhanced CAPI and GPU interfaces. This support has been critical in the creation of CORAL, as IBM acknowledges. IBM is covering key basics very well.
Finally, a significant messaging advantage they have neglected to mention is the powerful boost that this new architecture and system provides to Watson.  The Watson Marketing group is rightly and understandably focused on marketing segment specific benefits and features.
IBM Watson lays claim to having the best AI solution system in the marketplace. Today, competition in the AI platform space is rapidly growing. Vendors large and small, much x86-based, are effectively competing against IBM. It appears to us that there exists a powerful message in how POWER9 System’s bespoke (for AI) IBM infrastructure meshes with, enables and drives IBM’s showcase AI application. 
The POWER9 architecture represents a significant advance in its offering of AI-specific features, capabilities and performance enhancements. Combined with a solid existing ecosystem, it should increase the market penetration of Power Systems.

[1] CAPI itself was a very significant improvement, see With Redis Labs, CAPI goes Mainstream, Big Time! at
[2] Caffe and Chainer are both open source frameworks. See and for more information.

Wednesday, November 22, 2017

IBM Spectrum with Cluster Virtualization accelerates Cloud & Cognitive Computing

By Rich Ptak

(Image courtesy of IBM, Inc.) 
IBM made a big impact with announcements of pervasive encryption earlier this year. Now, with its most recent announcement, we predict they will do so again as they tackle one of the biggest frustrations and ongoing challenges to IT.

IT innovators and creators have struggled for decades trying to identify how to get the maximum utilization and optimal performance from an evolving, disparate, complex, heterogeneous IT infrastructure. Complicating the challenge is a user base demanding simple access to the latest technological innovations. The upending of market and usage models, only adds to the problem.

IBM’s latest announcement tackles the challenge head-on with an architecture and solution suite that applies cognitive computing and sophisticated software that delivers consistent, simplified access to automatically managed (and optimized) infrastructure. In their announcement, IBM provides the details of exactly how and what they deliver. We aren’t here to rehash that. We provide a selected product overview with comments on why we think this is a major advance for cloud and cognitive computing users and developers.

What’s the issue?

A perennial goal of IT operations has been to provide the best user experience possible in a cost-effective manner. Typically, operational metrics focused on the simplicity of the user interface, reliability, response times, etc. For infrastructure, the goal was optimal utilization, high performance, and reliable operations. Pursuing these goals has driven IT innovation and product development for decades. IT staff tried a variety of ways to resolve the issues, e.g. languages (Fortran, Cobol, Java), operating systems (z/OS, Unix, Linux, etc.), platforms, dedicated systems, GUIs, APIs, containers, server clusters, open systems, and clouds with limited success.

Today, despite the effort, the goal remains the same. The compute environment is more complex than ever. Users are still frustrated. IT administrators, developers, and operations staff spend too much time configuring infrastructure and juggling complex, dynamic workloads trying to meet SLAs and satisfy users. IBM Systems turned to Cognitive computing and Software Defined infrastructure to address the issues.

IBM Software Defined Infrastructure & Software

In a nutshell, IBM’s Software Defined Computing solution suite addresses the user interface, workload management, infrastructure management and solution development challenges. At the heart of the solution is Cluster Virtualization software which virtualizes access to and exploitation of servers, storage, clusters, clouds, etc., or whatever constitutes the defined available infrastructure. IBM’s innovation is to buffer the user, whether apps developer or user, from having to learn about the intricacies of the supporting computing infrastructure. It offers the prospect of automatic infrastructure configuration and management optimized to provide maximum infrastructure utilization and workload performance.

A virtualization software interface buffers the user and IT operations from the complexity of the underlying infrastructure more effectively than past attempts. Users provide app requirements and parameters. Operations staff identify performance metrics, constraints, and requirements. The solution suites for workload types (discussed below) manage and optimize infrastructure operations using cognitive computing solutions. These dynamically learn app and workload behaviors, infrastructure availability and performance, etc. measured against up to 20 different parameters to manage workloads and configurations. 

Figure 1 IBM Cluster Virtualization    (Courtesy of IBM, Inc.)

Cluster Virtualization Software allows users to transparently share clusters of computing resources. Specialized software suites operating through IBM Spectrum Computing and IBM Spectrum Storage underpin the specialized suites.  Figure 1 represents how all the pieces fit together to provide end-to-end management of user activities across multiple platforms, architectures and data center environments. 

Cluster Virtualization

Cluster Virtualization allows many independent applications and workloads to make use of disparate resources residing in multiple, different clusters. The workloads can be a mixture of traditional apps, such as high-performance computing or compute-intensive analytics, or next-generation workloads leveraging Hadoop, Spark, and containers, etc. A consistent interface provides users simplified access to and utilization of the total cluster infrastructure. The arrangement is highly scalable; apps and users can both run into the thousands. IBM reports the potential of running millions of jobs per day. IT operations staff benefit with cognitive computing services that automatically manage up to 20 different operational parameters to configure, provide workload management (e.g. scheduling, assignment), infrastructure scaling (up and down), etc., to optimize resource utilization and performance.

The beauty of this design lies in the extremely flexible definition of clusters. It supports a broad range of complex, mixed and heterogeneous environments encompassing from several to 1000s of systems, or VMs. Supported system types include OpenPOWER, x86, ARM, SPARC, as well as multiple operating systems and environments, including LinuxONE, Docker, containers, etc. The defined cluster can be on-premise systems or extend into public, private or hybrid clouds. Cluster virtualization can function across heterogeneous cloud environments that include IBM Cloud, IBM Cloud Private, AWS, etc.

Next Gen IBM Spectrum LSF Suites

IBM also announced significant enhancements to their IBM Spectrum LSF suites. These offer workload management options specifically targeted at the Enterprise, HPC and Workgroup segments with increasing functionality at each level. Figure 2 shows how the functionality and capability varies at each level. 
Figure 2 New IBM Spectrum LSF suites  (Courtesy of IBM, Inc.)

Each level is designed to simplify user access and management with automated reconfigurations of access to resources, rapid, flexible scalability and resource utilization. All adjustments are controlled through defined policies, automatically managed and administered.

IBM has introduced new pricing terms and models which appear very attractive. Your IBM rep can provide details.

IBM Spectrum Conductor

There is much more to IBM’s announcement, including updates and additions to IBM Spectrum Conductor, such as the Deep Learning Impact module. An extensive list of enhancements was announced to speed processing, including hyper-parameter search and optimization techniques, elastic resource allocation, and Spark-specific data management. Cluster virtualization and multitenancy for deep learning are only two techniques that are included to increase resource utilization.

This module is designed to more dynamically, efficiently and rapidly extract useable business insights and value from data even as it also simplifies installation, configuration, implementation, model building and analysis with pre-built frameworks. It provides shared multi-tenant and multi-service functionality that will speed up processing and increase infrastructure utilization. IBM Services and Support is available for the entire software stack available on both IBM Power System for HPC with IBM PowerAI framework and x86 systems with Open Source frameworks. The software distribution packages contain all needed components, including all Open Source components. End-to-end workflow management operates automatically to improve operations over multiple cycles. Feedback is that the results are very effective in reaching the efficiency, acceleration and savings goals. 

Enhancements were also made to IBM Spectrum Scale to improve storage performance and operational efficiency. These include accelerated I/O performance, reduced latency between nodes, and better performance of metadata operations. From what we can tell, these all benefit from the cluster virtualization and contribute significantly to the overall performance improvements.


This announcement appears to provide significant evidence to justify a more detailed follow-up for any IT operation responsible for the economic support of a complex data center in a compute intensive environment. To us, the effective implementation of Cluster Virtualization with its potential to simply and economically leverage, exploit and scale heterogeneous compute clusters alone is a compelling reason for further exploration. We intend to follow developments in this area. We look forward to hearing more from users. In the meantime, we highly recommend calling your IBM rep for additional information. 

Wednesday, November 15, 2017

Wednesday, November 1, 2017

Busting Mainframe Myths - BMC’s 12th Annual Survey

By Bill Moran and Rich Ptak

BMC surprised us during the review of the results of their annual mainframe survey. Frankly, we were concerned it would be somewhat boring. After all, after 12 years of surveys, expectations were low for something new, much less exciting. The results, when presented, changed all that.

BMC began by listing 5 popular mainframe myths. For this paper, we ‘ve reordered and reworded the list slightly, to make them more forceful. Here they are with our comments in italics:

1)    The mainframe is in maintenance mode (i.e. an old, dead platform) that no one invests in anymore. Many in the industry believe this.
2)    Executives are planning to replace their mainframes. As the trade press (and some analysts) have been saying for years.
3)    Organizations have already fully optimized the mainframes for maximum availability. No surprise here. They have had a lifetime to do so.
4)    Only elderly, ready-to-retire Cobol types work on the mainframe today. Sun Micro at one point had a video that showed some of them.
5)    If any young professionals work on the mainframe, they cannot expect much of a career.
We admit that our list exaggerates a bit, but it does so to make a valid point. Many non-mainframe people believe item number 1 item is undeniably true. This is the root of remaining 4 points. Despite efforts by IBM, BMC, Compuware, and others working for years to update, improve and mainstream the mainframe, the perception persists. 

This BMC survey provides a giant step toward finally putting these myths to rest.

Before presenting our conclusions and comments, some background. Survey details and logistics are covered in the Results e-Book[1]. The survey captures input from over 1,000 executives and professionals, all working with the mainframe in enterprises down to mid-range shops. Now, for the survey results as they expose the myths.

For myth #1, a full 91% of the respondents view the mainframe as a long-term, viable platform. 75% of respondents are using Java on the mainframe indicating their companies have made the investment to hire or train people in Java usage. 42% identify application modernization as a priority. The specific reason (for modernizing) is to take advantage of new technology. These results provide convincing proof that customers are modernizing their mainframes. Also, far from being dead – mainframes are very active platforms. Myth #1 deposed.
On to myth #2. 47% of the executives interviewed state that the mainframe will grow and attract more workloads, 43 % see it stabilizing, and only 9% say their organizations will replace the platform.  Myth #2 destroyed.

On to myth #3. The claim is that mainframe users have already squeezed the last drop of availability out of the platform. Mainframes have always delivered very high levels of availability, yet a full 66% say business requirements continue to force a focus on further reducing maintenance windows. Simply said, they must increase platform availability. Myth #3 shattered.

Consider myth #4. Mainframe users are mainly elderly, ready-to-retire types. This year, BMC added demographic questions to the survey.  They found 53% of the respondents are under the age of 50 and only 4% over 65.  20% are female of whom the majority 55%, are between 30 and 49. (Interesting side-note, latest figures say only 11% women are in STEM positions worldwide.) Myth #4 deflated.

Finally, Myth#5. No career path for younger professionals. In actuality, a full 70% of the surveyed millennials (under age 30 with less than 10 years’ experience) are convinced that the mainframe will grow and attract new workloads industry-wide. 54% believe that the mainframe will grow within their organization, a sure indication they see career opportunities with the mainframe. Myth #5 is laid to rest.

Logically, this survey will help to kill off some of these common mainframe myths. People will believe what they want to believe. Others are vested in the maintaining the myths. Typically, neither of these will let the facts alter their beliefs. We, however, want as many as possible to be aware of these facts.

We encourage you to investigate BMC’s results for more information and insight. You will likely find the results to be interesting and, possibly, unexpected.

BMC announced these results on November first. For even more of the details and your own copy of the survey, go to BMC’s Mainframe Survey Resources web page here[2].   And, you can read more of our commentary on IT topics in our Tech Blogs[3]. We think you will find that the mainframe has a significant future!


ignio: Artificial Intelligence for IT Ops

By Bill Moran and Rich Ptak


Figure 1 Artificial Intelligence for IT Ops   Courtesy of Digitate
Indian multi-national Tata Consulting Services (TCS), created Digitate in 2015 to develop and deliver products based on the ignio™ Cognitive Automation platform. Today, (November 2017) these include ignio for IT Operations, ignio for Batch, and ignio for SAP ERP. We think these offer significant value and benefits to IT. Here’s why.

An IT dilemma

IT departments face a dilemma. Their budgets are under severe pressure to deliver more with fewer resources.  Yet, they must also manage and undergo a costly digital transformation that CEOs are relying on to deliver new business opportunities. This dilemma is sharpened, and risk is increased as many of IT’s best people are unavailable because they are focused on firefighting to maintain the SLAs that keep existing customers happy. 

IT benefits greatly when such resources and people can focus on these challenges. This is where Digitate’s ignio products offer substantive assistance[1]. Over time, they “learn”[2] IT operations to allow automation of routine tasks and thus speed and facilitate problem detection and solution. As its knowledge builds, ignio more fully automates problem “find and fix” activities. Meanwhile, it greatly assists with problem resolution.

Determining problems in a complex environment is difficult and time-consuming. ignio can help but most IT shops will wisely choose to selectively implement the more advanced ignio capabilities. A careful plan, as we discuss later, will deliver many advantages by reducing risks and speeding the process.

ignio products

ignio for Batch and ignio for SAP identify their application targets. ignio for IT Operations is designed to deliver value across the whole range of data center operations. Each product can integrate with other installed monitors. Data sheets for each product are available on the Digitate web site[3]. Figure 2 shows the ignio platform architecture.

Figure 2 ignio Platform Architecture        Courtesy of Digitate    

Key to ignio’s value is the amount of out-of-the-box knowledge it has about the data center. It knows what a server is, what storage is, and has considerable knowledge about commonly installed operating systems. Inherent in ignio is >30 years of IT infrastructure technology that includes common knowledge about data center operations and IT infrastructures.

The process on how ignio addresses IT challenges has been carefully designed. Through Blueprinting, ignio first learns the environment to identify what is there and determine “normal” behavior. Once ignio identifies “normal,” it can identify deviations. Then, it moves to analysis determining probable causes of the deviant behavior. Finally, ignio recommends or in some cases executes fixes which can be applied automatically. Such repair depends on the installation parameters.

During operation, ignio products follow a continuous cycle of Learn, Resolve, Prevent. The result is that operational models and the knowledge base are continually updated to reflect changes in the environment and operations of the data center.

In addition to being able to “Resolve” issues in the data center, ignio can automate routine tasks that used to take a significant amount of time. IT resources are stretched in most companies, ignio can help address typical employees requests quickly while allowing IT to tackle other more critical challenges.

In its “Prevent” phase, ignio will use the knowledge acquired of system operations to predict likely problems before they happen as well as model the effect of proposed system changes. Very significantly and attractively, we note that ignio does not use scripts. Therefore, staff do not have to deal with brittle scripts that are a nightmare to manage

Suggested Action Plan

We recommend beginning with a study and evaluation of ignio. We found a wealth of helpful material on Digitate’s web site[4] from which to understand Digitate’s product offerings, their potential application in the enterprise, and decide on further investigation of ignio products.

After deciding to move forward with ignio, the next step requires creation of a business case and plan. Senior management judge will judge success by the amount of business value that a technology delivers. You can expect to deliver value in a reasonably short timeline. What is “reasonable” depends on the organization.

The planner needs to understand the organization’s significant problems. They must identify where and what the possibilities are for tangible organizational benefit. Too often, new technology projects fail due to lack of a properly documented business case with a well-defined use case that includes specific benefits enumerated and quantified. Review potential targets to identify which will benefit most from ignio. Avoid a project with a high risk of visible, disruptive failure. Effective application of AI is leading edge so set modest goals to start. Establish readily identifiable payback and quantifiable benefits.

Finally, identify potential pitfalls, setbacks, and difficulties. Then, determine how to address these. How will you recover if the original objective cannot be achieved?  This is a possibility, especially with new technology. Should you consider having Digitate Consulting work with existing staff on the initial deployment and training? Where are problems most likely to crop up? Who is affected by this? Where will objections/blockages occur? How can these be avoided/minimized? 

How long will the install take?

Digitate estimates that it generally takes 6 weeks for ignio to learn and become effective in
 normal operations. This can vary widely by customer[5]. Many installations operate a variety of “normal”. Day-time processing differs from nighttime. Weekdays differ from weekends. End-of-month, -quarter and -year have unique patterns. Some have periods when operations dramatically differ. For example, tax season stresses auditing firm IT systems; fourth quarter stresses retail IT. ignio continuously learns the business context during each period to build a complete model able to detect deviations. Select the initial project time-line accordingly as it may make sense to avoid a critical business period to avoid a catastrophic result.

ignio - Be aware

Currently, ignio does have some limitations. For instance, ignio has limited mainframe support. ignio for Batch will be able to analyze data from the mainframe, but it is not designed as a batch scheduler to execute mainframe’s batch jobs. That said, ignio for Batch can be very useful in certain environments. In our opinion, any shop running hundreds, or thousands of batch jobs would be well served to take a close look at ignio’s products.

Note that current operating system support includes: Windows, Linux, AIX, and Solaris. There is no support, currently or planned, for z/OS or any other mainframe OS.  We expect UNIX versions, like HP-UX, will be added over time.

The Final Word

ignio delivers a valuable, beneficial application of AI technology to IT data center operations. It will deliver worthwhile results to organizations that follow a careful plan for its implementation. Its products merit careful examination. It is new technology and should be handled as such, i.e. with careful management and planning.  

There will be many products using AI technology. Similar offerings are in the market that use AI, robotics, machine learning for cognitive automation in different ways. Offerings for process automation and optimization are available from companies such as Automation Anywhere, Blue Prism, IBM, UIPath, WorkFusion, etc. Business and industry press, consultants and analysts discussing applications of AI and cognitive technologies will only increase management pressure for in-house AI projects.

ignio appeals to us because it offers key advantages to IT. Among the most significant is that their current products can be used in projects totally contained within IT where risk can be best managed. This allows IT to build knowledge and experience to respond to management questions about AI. A project to investigate and apply ignio products to IT operations appears to us to be a very good move.

TCS has a worldwide presence, deep pockets and highly regarded expertise in IT consulting. Digitate benefits as they leverage these in development and delivery activities. Successful, continued innovation in leading-edge technologies requires substantial on-going investment. Stable technical and financial backing benefits both Digitate and its customers.

[1] There is an excellent video, an interview with Dr. Harrick Vin, the CEO of Digitate, on the design of ignio. See There are other videos as well.
[2] We realize that we are using words that imply that machine learning is identical to human learning. This can be debated but we will use these words without prejudging the results of the debate.
[3] Find these and many more informative resources at:
[5] External events may also have to be considered. A disaster, natural or otherwise, can dramatically affect data center operations. 

Tuesday, October 10, 2017

Compuware Delivers Topaz on AWS to Mainstream the Mainframe

By Rich Ptak

Figure 1 – Topaz on AWS      Image Courtesy of Compuware, Inc.
It’s time for Compuware’s quarterly mainframe product announcements. This time Compuware kicks off its 12th quarter (3 years) of new and enhanced product releases by partnering with Amazon. The duo upends mainframe DevOps and mainframe IT by combining efforts to deliver web access to the Topaz DevOps software suite on AWS. See Figure 1.

In an industry first, Compuware provides cloud access to modern mainframe development via Topaz. Developers can enjoy the same user experience on the cloud as if Topaz was locally installed while fully leveraging all the security, performance, flexibility, reliability, scalability and accessibility features of the AWS platform.

Topaz on AWS leverages Amazon AppStream[1] 2.0 technology, a fully managed, secure application streaming service that allows applications to be streamed from  AWS to devices running a web browser. Now, all of Topaz’s rich capabilities and more are accessible anywhere through the most popular web interfaces including IE/Edge, Chrome and Firefox. The power of Topaz is accessible regardless of the device used, be it a Windows, Mac or Chromebook desktop system.

Compuware’s patent-pending technology provides an intuitive, streamlined configuration menu that leverages AWS best practices, and makes it easy for systems administrators to quickly and easily configure their Topaz on AWS infrastructure, customized to their specific needs, in a few simple steps.

Enterprises can scale the number of development environments up or down depending on their needs. Developers have fast access to new features and functionality that Compuware makes available every 90 days without administrators having to distribute, load, recompile, modify and test multiple individual systems or installations. Efforts to modernize mainframe operations and capabilities happen faster with fewer delays and without requiring the involvement of critical IT staff.

Compuware and Amazon have created a highly performant, secure and fluid developer experience. Once developers launch Topaz on AWS, they can access datasets and data files, analyze applications, make code changes and manage other mainframe tasks using the Topaz suite of tools as if the user environment was locally installed.

Some architectural benefits of AWS

An important feature is that this implementation fully leverages all of the unique enterprise product strengths of the AWS cloud architecture. These include:

  • ·         Security – individual secure deployment applied and management on a per account basis – with built-in automated security management services to review policies and monitor compliance with security best practices.
  • ·         Cost optimization – automated optimization assures least-cost-to-user and most cost-effective resource management. Periodic reviews and auto-scaling combine to optimize the operating environment as workload volumes and capacity requirements fluctuate.
  • ·         Reliability – AWS management services work to ensure systems are architected to meet operational thresholds to avoid when possible, and quickly recover from inevitable failures to meet business and customer service demands.
  • ·         Operational excellence – Amazon maintains cloud centers located around the world to assure service response and support.
  • ·         Performance efficiency – optimizes system services for maximum performance using available resources, enabling optimal utilization of IT staff and computing resources through automation, cloud-based services and management.

The pricing is right

All of this comes with no new charges from Compuware. The standard Compuware Topaz licensing charge covers the use of Topaz on-premise, in the cloud or in a mixed environment. If you already have a Topaz license, all you need to do is add an Amazon account with AWS cloud services designed to meet the requirements of your specific enterprise operating environment and workload. As mentioned earlier, Amazon AppStream 2.0 services include an automated function to help users find the right optimized pricing model and configuration for their workload and resource needs. These include highly flexible on-demand pricing, spot-discrete fixed price and reserved instances for dedicated predictable workloads, and combinations. We recommend you review the details with an AWS advisor or check here[2] for more information.

What else is new?

Compuware’s quarterly announcements are never about just one thing. This time is no exception. In addition to the major announcement, Compuware has additional improvements and new product enhancements and capabilities to deliver.  

First up is a collaboration with CloudBees Jenkins Enterprise. Leveraging Compuware ISPW and/or Compuware Topaz for Total Test in conjunction with CloudBees Jenkins Enterprise, large enterprises can streamline DevOps on their mainframes and orchestrate DevOps across all platforms. Compuware will co-host a webcast with CloudBees on October 25, which will identify opportunities and help educate users on the latest in mainframe DevOps processes.

Figure 2 Webhook Notifications  (Courtesy Compuware, Inc.)
Next is the addition that extends ISPW so that it can stream information and notifications to web apps through Webhook notifications. Webhooks were designed to allow third-parties, such as developers and apps, to make changes to web APIs using callbacks. See Figure 2. This is how ISPW can communicate with Jenkins and other CI services to trigger actions. In effect, it allows ISPW to integrate with other deployment tools and drive continuous integration processes. Activities can be communicated by DevOps teams as they happen in real time to such tools as Slack and Hipchat.

A bit of risk?

Choosing public cloud service delivery of the Topaz suite may appear to be risky or even premature to some potential users. Considerations that come to mind are those surrounding issues pertaining to security, reliability, privacy, infrastructure control and, unfortunately, more and more government imposed legal and legislative constraints and mandates. Most of these issues have been and will continue to be hashed over and argued about in the press. They remain and should remain issues of, at a minimum, keen awareness. Our conversation with Compuware has convinced us that they are working in lockstep with Amazon to reduce the risk and vulnerabilities as much as possible.

Potential customers should identify potential issues and resolve what needs to be done before making the move to the cloud. Others may find cloud-based but maintained and operated in-house on-premise to be the right solution.

The first step to be taken is to perform due diligence to identify and assess potential risks and vulnerabilities. Then, these can be balanced against the significant potential benefits in the form of client/customer satisfaction, staff satisfaction and cost savings that can result from improved operations, increased efficiencies and simplified infrastructure management. Examine what Compuware and Amazon have done to mitigate the risks. We believe that many will find the decision to move this development activity to the cloud makes sense.  

The Final Word

Compuware continues to deliver solutions aimed at “Mainstreaming the Mainframe.” Their strategy depends upon their ability to identify and overcome structural and operational issues that make mainframe utilization and COBOL code maintenance a complex, slow and intimidating task, especially for those new to the mainframe.

Compuware has delivered significant, game-changing products each quarter for the last 3-years. They have not only improved, simplified and sped up mainframe operations and management, but they have also introduced capabilities that were never thought possible or are radically changing mainframe operations. They appear to us to be on track to continue that success. Congratulations to them. Good luck as they move forward. We recommend examining their latest offering.