Posts Tagged ‘zEnterprise’

z Systems and Cloud Lead IBM 2Q Results

July 24, 2015

DancingDinosaur generally steers clear of writing about reported quarterly revenue. Given the general focus of this blog on enterprise and cloud computing, however, IBM’s recent 2Q15 report can’t be ignored. Although it continued IBM’s recent string of negative quarterly results, the z and cloud proved to be bright spots.

Infographic - IBM Q2 2015 Earnings - Cloud - July 20 2015 - Final

Strong IBM cloud performance, Q2 2015 (click to enlarge)

As IBM reported on Monday: Revenues from z Systems mainframe server products increased 9 percent compared with the year-ago period (up 15 percent adjusting for currency).  Total delivery of z Systems computing power, as measured in MIPS, increased 24 percent.  Revenues from Power Systems were down 1 percent compared with the 2014 period (up 5 percent adjusting for currency).

It’s not clear when and how Power Systems will come back. IBM has opened up the Power platform through the Open Power Foundation. A good move in theory, which DancingDinosaur applauds. Still, much depends on the Foundation gaining increased momentum and individual members rolling out successful Power-based products. The roadmap for POWER8, POWER9, and beyond looks promising but how fast products will arrive is unclear. There also is potential for the commoditization of the Power platform, a welcome development in many quarters, but commoditization’s impact on future revenue also is not clear.

Cloud revenue was up more than 70 percent, adjusting for currency and divested businesses; up more than 50 percent as reported, according to IBM. Given that cloud, along with mobile and analytics, has been designated strategic by IBM this is an encouraging development. The company’s cloud strategy is starting to bear fruit.

The big question hanging over every vendor’s cloud strategy is how to make money at it. One of the appealing aspects of the cloud in terms of cost and pricing for IT-using organizations is what amounts to a race to the bottom. With pricing immediately apparent and lower pricing just a click away it has become a feast for the bottom grazers to whom the lowest price is all that matters. For companies like IBM and Oracle, which also has declared cloud a strategic initiative, and other large legacy enterprise platform providers the challenge is to be competitive on price while differentiating their offerings in other ways. Clearly IBM has some unique cloud offerings in Watson and Bluemix and others but can they deliver enough revenue fast enough to offset the reduction in legacy platform revenue. Remember, x86 is off IBM’s menu.

Timothy Prickett Morgan, who writes frequently about IBM technology, also had plenty to say about IBM’s 2Q15 announcement, as did a zillion other financial and industry analyst. To begin he noted the irony of IBM promoting cloud computing, primarily an x86 phenomenon while trying to convince people that Power-based systems are cost competitive—which they can be—and will do a better job for many of those workloads, correct again.

Morgan also makes an interesting point in regard to the z: “IBM doesn’t have to push the System z mainframe so much as keep it on a Moore’s Law curve of its own and keep the price/performance improving to keep those customers in the mainframe fold.” That’s harder than it may seem; DancingDinosaur addressed the Moore’ Law issue last week here. As Morgan notes, with well over $1 trillion in software assets running on the mainframe, the 6,000 or so enterprises that use mainframes are unlikely to move off the platform because of the cost, disruption, and risk such a move would entail. Just ask Union-Pacific Railroad, which seems to be doing a slow-motion platform migration off the mainframe that seemingly may never actually end. Morgan concludes: “IBM can count on a certain level of money from the System z line that it just cannot with the Power Systems line.”

As noted above, how much revenue Power can generate for IBM depends on how fast the Open Power Foundation members introduce products that expand the market and how many Power processors SoftLayer can absorb as the business unit expands its global footprint.  There also is the question of how many POWER8 servers Rackspace, a much larger cloud provider than SoftLayer, will take and whether the Rackspace initiative will catch on elsewhere.

In any event, IBM’s 2Q15 report showed enough positive momentum to encourage IT platform enthusiasts. For its part, DancingDinosaur is expecting a business class z13 in the coming months and more.

DancingDinosaur is Alan Radding, a veteran IT analyst and writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at technologywriter.com and here.

IBM Extends Moore’s Law with First 7nm Test Chip

July 17, 2015

In an announcement last week, IBM effectively extended Moore’s Law for at least another generation of chips, maybe two.  This contradicts what leading vendors, including IBM, have been saying for years about the imminent diminishing returns of Moore’s Law, which postulated that chips would double in capacity every 18-24 months. Moore’s Law drove the price/performance curve the industry has been experiencing for the past several decades.

Post-Silicon-R&D_Infographic_070715_Final

Click to enlarge, courtesy of IBM

The announcement, ironically, coincides with IBM’s completion of the sale of its semi-conductor fabrication business to GLOBALFOUNDRIES, which IBM paid to take the costly facilities off its hands. To pull off the 7nm achievement IBM ended up partnering with a handful of players including public-private partnership with New York State and joint development alliance with GLOBALFOUNDRIES, Samsung, and equipment suppliers. The team is based at SUNY Poly’s NanoTech Complex in Albany.

To achieve the higher performance, lower power, and scaling benefits promised by 7nm technology, the IBM researchers turned to two main innovations, the use Silicon Germanium (SiGe) channel transistors and Extreme Ultraviolet (EUV) lithography integration at multiple levels, in effect bypassing conventional semiconductor manufacturing approaches.

Don’t expect to see new systems featuring these 7nm chips very soon. The announcement made no mention of any timetable for producing commercial products based on this technology. As Timothy Prickett Morgan, who writes extensively on IBM POWER Systems technology observed: the use of silicon germanium for portions of the transistors cuts back on power consumption for the very fast switching necessary for improving circuit performance, and the circuits are etched using extreme ultraviolet (EUV) lithography. These technologies may be difficult and expensive to put into production.

In the meantime, IBM notes that microprocessors utilizing 22nm and 14nm technology run today’s servers, cloud data centers, and mobile devices; and already 10nm technology is well on the way to becoming a mature technology. The 7nm chips promise even more: at least a 50% power/performance improvement for next mainframe and POWER systems that will fuel the Big Data, cloud and mobile era, and soon you can add the Internet of Things too.

The z13 delivers unbeatable performance today. With the zEC12 IBM boasted of the fastest commercial chip in the industry, 5.5 GHz on a 32 nm wafer. It did not make that boast with the z13. Instead the z13 runs on a 22 nm core at 5 GHz but still delivers a 40% total capacity improvement over the zEC12.

It does this by optimizing the stack top to bottom with 600 processors and 320 separate channels dedicated just to drive I/O throughput. The reason for not cranking up the clock speed on the z13, according to IBM, was the plateauing of Moore’s Law. The company couldn’t get enough boost for the tradeoffs it would have had to make. Nobody seems to be complaining about giving up that one-half GHz. Today the machine can process 2.5 billion transactions a day.

The ride up the Moore’s Law curve has been very enjoyable for all. Companies took the additional processing power to build onto the chip more capabilities that otherwise would have required additional processors.  The result: more performance and more capabilities at lower cost. But all good things come to an end.

This 7nm  breakthrough doesn’t necessarily restore Moore’s Law. At this point, the best we can guess is that it temporarily moves the price/performance curve to a new plane. Until we know the economics of mass fabrication in the 7nm silicon germanium world we can’t tell whether we’ll see a doubling as before or maybe just a half or quarter or maybe it could triple. We just don’t now.

For the past decade, Morgan reports, depending on the architecture, the thermal limits of systems imposed a clock speed limit on processors, and aside from some nominal instruction per clock (IPC) improvements with each  recent microarchitecture change, clock speeds and performance for a processor stayed more or less flat. This is why vendors went parallel with their CPU architectures, in effect adding cores to expand throughput rather than increasing clock speed to boost performance on a lower number of cores. Some, like IBM, also learned to optimize at every level of the stack. As the z13 demonstrates, lots of little improvements do add up.

Things won’t stop here. As Morgan observes, IBM Research and the Microelectronics Division were working with GLOBALFOUNDRIES and Samsung and chip-making equipment suppliers who collaborate through the SUNY Polytechnic Institute’s Colleges of Nanoscale Science and Engineering in nearby Albany to get a path to 10 nm and then 7 nm processes even as the sale of GLOBALFOUNDRIES was being finalized.

The next step, he suggests, could possibly be at 4 nm but no one is sure if this can be done in a way that is economically feasible. If it can’t, IBM already has previewed the possibility of other materials that show promise.

Moore’s Law has been a wonderful ride for the entire industry. Let’s wish them the best as they aim for ever more powerful processors.

DancingDinosaur is Alan Radding, a veteran IT analyst and writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at technologywriter.com and here.

IBM Continues Open Source Commitment with Apache Spark

June 18, 2015

If anyone believes IBM’s commitment to open source is a passing fad, forget it. IBM has invested billions in Linux, open Power through the Open Power Foundation, and more. Its latest is the announcement of a major commitment to Apache Spark, a fast open source and general cluster computing system for big data.

spark VGN8668

Courtesy of IBM: developers work with Spark at Galvanize Hackathon

As IBM sees it, Spark brings essential advances to large-scale data processing. Specifically, it dramatically improves the performance of data dependent-apps and is expected to play a big role in the Internet of Things (IoT). In addition, it radically simplifies the process of developing intelligent apps, which are fueled by data. It does so by providing high-level APIs in Scala, Java, and Python, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Spark Streaming for stream processing.

IBM is contributing its breakthrough IBM SystemML machine learning technology to the Spark open source ecosystem. Spark brings essential advances to large-scale data processing, such as improvements in the performance of data dependent apps. It also radically simplifies the process of developing intelligent apps, which are fueled by data. But maybe the biggest advantage is that it can handle data coming from multiple, disparate sources.

What IBM likes in Spark is that it’s agile, fast, and easy to use. It also likes it being open source, which ensures it is improved continuously by a worldwide community. That’s also some of the main reasons mainframe and Power Systems data centers should pay attention to Spark.  Spark will make it easier to connect applications to data residing in your data center. If you haven’t yet noticed an uptick in mobile transactions coming into your data center, they will be coming. These benefit from Spark. And if you look out just a year or two, expect to see IoT applications adding to and needing to combine all sorts of data, much of it ending up on the mainframe or Power System in one form or another. So make sure Spark is on your radar screen.

Over the course of the next few months, IBM scientists and engineers will work with the Apache Spark open community to accelerate access to advanced machine learning capabilities and help drive speed-to-innovation in the development of smart business apps. By contributing SystemML, IBM hopes data scientists iterate faster to address the changing needs of business and to enable a growing ecosystem of app developers who will apply deep intelligence to everything.

To ensure that happens, IBM will commit more than 3,500 researchers and developers to work on Spark-related projects at more than a dozen labs worldwide, and open a Spark Technology Center in San Francisco for the Data Science and Developer community to foster design-led innovation in intelligent applications. IBM also aims to educate more than 1 million data scientists and data engineers on Spark through extensive partnerships with AMPLab, DataCamp, MetiStream, Galvanize, and Big Data University MOOC (Massive Open Online Course).

Of course, Spark isn’t going to be the end of tools to expedite the latest app dev. With IoT just beginning to gain widespread interest expect a flood of tools to expedite developing IoT data-intensive applications and more tools to facilitate connecting all these coming connected devices, estimated to number in the tens of billions within a few years.

DancingDinosaur applauds IBM’s decade-plus commitment to open source and its willingness to put real money and real code behind it. That means the IBM z System mainframe, the POWER platform, Linux, and the rest will be around for some time. That’s good; DancingDinosaur is not quite ready to retire.

DancingDinosaur is Alan Radding, a veteran IT analyst and writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing on Technologywriter.com and here.

API Economy Comes to the IBM z System

June 11, 2015

What comes to mind when you hear (or read) about a RESTful IBM z System? Hint: it is not a mainframe that is loafing. To the contrary, a RESTful mainframe probably is busier than it has ever been, now running a slew of new apps, most likely mobile or social apps with REST APIs connecting to z/OS-based web services plus its usual workloads. Remember web services when SOA first came to the mainframe? They continue today behind the new mobile, cloud, social, and analytical workloads that are putting the spotlight on the mainframe.

Travel and Transportation - Passenger Care

Courtesy of IBM: travel fuels mobile activity (click to enlarge)

A variety of Edge2015 sessions, given by Asit Dan, chief architect, z Service API Management and Glenn Anderson, IBM Lab Services and Training, put what the industry refers to as the emerging API economy in perspective. The z, it should come as no surprise, lies at the heart of this burgeoning API economy, not only handling transactions but also providing governance and management to the API phenomenon that is exploding. Check out IBM’s APIs for Dummies.

The difference between first generation SOA and today’s API economy lies in the new workloads—especially mobile and cloud—fueling the surging interest. The mobile device certainly is the fastest growing platform and will likely become the largest platform soon if it is not already, surpassing desktop and laptop systems.

SOA efforts initially focused on the capabilities of the providers of services, noted Dan, particularly the development, run-time invocation, and management of services. The API economy, on the other hand, focuses on the consumption of these services. It really aims to facilitate the efforts of application developers (internal developers and external business partners) who must code their apps for access to existing and new API-enabled services.

One goal of an enterprise API effort is to access already deployed services, such z-based CICS services or those of a partner. Maybe a more important goal, especially where the z is involved, is to drive use of mainframe software assets by customers, particularly mobile customers.  The API effort not only improves customer service and satisfaction but could also drive added revenue. (Have you ever fantasized of the z as a direct revenue generator?)

This calls, however, for a new set of interfaces. As Dan notes in a recent piece, APIs for accessing these assets, defined using well known standards such as web services and Representational State Transfer (REST) with JSON (JavaScript Object Notation), and published via an easily accessible catalog, make it efficient to subscribe to APIs for obtaining permissions and building new applications. Access to the APIs now can be controlled and tracked during run-time invocations (and even metered where revenue generation is the goal).

Now the API economy can morph into a commercial exchange of business functions, capabilities, and competencies as services using web APIs, noted Glenn Anderson at Edge2015. In-house business functions running on the z can evolve into an API as-a-service delivery vehicle, which amounts to another revenue stream for the mainframe data center.

The API economy often is associated with the concept of containers. Container technology provides a simplified way to make applications more mobile in a hybrid cloud, Anderson explained, and brings some distinct advantages. Specifically, containers are much smaller in size than virtual machines and provide more freedom in the placement of workloads in a cloud (private, public, hybrid) environment. Container technology is being integrated into OpenStack, which is supported on the z through IBM Cloud Manager. Docker is the best known container technology and it works with Linux on z.

With the combination of SOA, web services, REST, JSON, OpenStack, and Docker all z capable, a mainframe data center can fully participate in the mobile, apps, cloud API economy. BTW, POWER servers also can play the API, OpenStack, Docker game too. Even Watson can participate in the API economy through IBM’s early March acquisition of AlchemyAPI, a provider of scalable cognitive computing API services. The acquisition will drive the API economy into cognitive computing too. Welcome to the mainframe API economy.

DancingDinosaur is Alan Radding, a veteran IT analyst and writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing on Technologywriter.com and here.

Real Time Analytics on the IBM z13

June 4, 2015

For years organizations have been putting their analytics on distributed platforms thinking that was the only way to get fast, real-time and predictive analytics. Maybe once but not anymore. Turns out the IBM z System, especially the z13 not only is ideal for real time, predictive analytics but preferable.

IBM today is so bullish on analytics, especially predictive analytics, that last month it introduced 20 pre-built industry-specific predictive analytics solutions. To build these solutions IBM tapped its own experience working on 50,000 engagements but also an array of outside organizations with success in predictive analytics, including Urban Outfitters, National Grid, Deloitte, Bolsa de Santiago, Interactive Data Managed Solutions, and Bendigo and Adelaide Bank, among others.

Web

Courtesy of IBM (click to enlarge)

The truth of the matter is that without efficient real time, predictive analytics managers get it wrong most of the time when it comes to making operational decisions, said Paul DiMarzio, IBM z Systems Big Data and Analytics Worldwide Portfolio Marketing Manager. He spoke at IBM Edge2015 in a session titled When Milliseconds Matter: Architecting Real-Time Analytics into Operational Systems. His key point: you can do this completely within the IBM z System.

The old notion of sending data to distributed systems someplace else for analytics now appears ridiculous, especially with the introduction of systems like the z13 that can handle operations and perform real time analytics concurrently. It performs analytics fast enough that you can make decisions when the action is still going on. Now the only question is whether we have the right business rules and scoring models. The data already are there and the tools are ready and waiting on the z13.

You start with the IBM SPSS Modeler with Scoring Adapter for zEnterprise. The real time predictive analytics capability delivers better, more profitable decisions at the point of customer impact. For business rules just turn to the IBM Operational Decision Manager for z/OS, which codifies business policies, practices, and regulations.

IBM SPSS improves accuracy by scoring directly within the transactional application against the latest committed data. As such it delivers the performance needed to meet operations SLAs and avoid data governance and security issues, effectively saving network bandwidth, data copying latency, and disk storage.

In addition to SPSS and the Operational Decision Manager the z13 brings many capabilities, some new for the z13 at this point. For starters, the z13 excels as a custodian of the data model, providing an accurate, secure, single copy of information that, according to IBM, ensures veracity of the data necessary for reliable analytics and provides centralized control over decision information.

Specifically, the machine brings SIMD (single instruction multiple data) and the MASS (mathematical acceleration subsystem) and ATLAS (automatically tuned linear algebra software) libraries for z/OS and Linux on z. SIMD enables the same operation to be performed on several data elements at the same time rather than sequentially. MASS and ATLAS help programmers create better and more complex analytic models.

In addition, increases in memory to as much as 10 TB, faster I/O, and simultaneous multi-threading (SMT) generally boost overall throughput of the z13, which will surely benefit any analytics being run on the machine, especially real time, predictive analytics.  In addition, analytics on the z13 gains from deep integration with core systems, the integrated architecture, and its single pane management view.

The latest IBM Red Book on analytics on the z13 sums it up as such: z Systems analytics enables organizations to improve performance and lower cost by bringing the analytic processing to where the data resides. Organizations can therefore maximize their current IT investments while adding functionality and improved price and performance with the z13. And with the new z13 features, applications can gain increased throughput for operational business intelligence (operational BI) and DB2 query workloads, which saves money (hardware, software, labor).

The Red Book suggests the following example: a user with a mobile application signs on and initiates a transaction flow through an IBM MobileFirst Platform Server running on Linux on z. The event goes to an LDAP server on z/OS to validate the user’s sign-on credentials. After successful validation, the transaction then proceeds through the z/OS transaction environment where all of the data resides in DB2 z/OS. IBM CICS transactions also are processed in the same z environment and all of the analysis is performed without moving any data, resulting in extremely fast performance. Sweet.

DancingDinosaur is Alan Radding, a veteran IT analyst and writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing on Technologywriter.com and here.

IBM zSystem for Social—Far From Forgotten at Edge2015

May 28, 2015

Dexter Doyle and Chris Gamin (z System Middleware) titled their session at Edge2015 IBM z Systems: The Forgotten Platform in Your Social Business. They were only half joking. As systems of engagement play bigger roles in the enterprise the z is not quite as forgotten as it may once have been.  In fact, at IBM the z runs the company’s own deployment of IBM Connections, the company’s flagship social business product.

Doyle used the graphic below (copyright John Atkinson, Wrong Hands) to make the point that new tools replace familiar conventional tools in a social business world.

 social desktop

 (copyright John Atkinson, Wrong Hands, click to enlarge)

Looks almost familiar, huh? Social business is not so radical. The elements of social business have been with us all along. It’s not exactly a one-to-one mapping, but Twitter and Pinterest instead of post-it notes, LinkedIn replaces the rolodex, Instagram instead of photos on your desk, and more.  Social business done right with the appropriate tools enables efficiency, Doyle observed. You don’t see the z in this picture, but it is there connecting all the dots in the social sphere

Many traditional mainframe data centers are struggling to come to grips with social business even as mobile and social workloads increasingly flow through the z. “The biggest thing with social is the change in culture,” said Doyle in his Forgotten Platform session. You end up using different tools to do business in a more social way. Even email appears antiquated in social business.

For data centers still balking at the notion of social business, Doyle noted that by 2016, 50% of large organizations will have internal Facebook-like social networks, a widely reported Gartner finding, and 30% of these will be considered as essential as email and telephones are today. The message: social business is real and z data centers should be a big part of it.

So what parts of social business will engage with the z? Doyle suggested five to start:

  1. Social media analytics
  2. Customer sentiment
  3. Customer and new market opportunity identification
  4. Identification of illegal or suspicious activities
  5. Employee and customer experiences

And the z System’s role? Same as it has always been:

  • Build an agile approach to deliver applications
  • Make every transaction secure
  • Use analytics to improve outcomes at every moment

These are things every z data center should be good at. To get started with social business on z visit the IBM Connections webpage here. There happens to be an offer for the 60-day free trail (it’s a cloud app) here. Easy and free, at least should be worth a try.

IBM Connections delivers a handful of social business capabilities. The main components are home, profiles, communities, and social analytics. Other capabilities include blogs, wikis, bookmarks, and forums for idea generation and sharing. You can use the activities capability to organize your work and that of a team, and another lets you vote on ideas. Finally, it brings a media library, content management capabilities, and file management.

Along with Connections you also might want to deploy WebSphere and Java, if you haven’t already. Then, if you are serious about building out a social business around the z you’ll want to check out Bluemix and MobileFirst. Already there is an IBM Red Book out for mobile app dev on the z13. The idea, of course, is to create engaging mobile and social business apps with the z as the back end.

The biggest payoff from social business on the z comes when you add analytics, especially real-time analytics. DancingDinosaur attended a session on that topic at Edge2015 and will be taking it up in a coming post.

DancingDinosaur is Alan Radding, a veteran IT analyst and writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing on Technologywriter.com and here.

Legacy Storage vs. Software Defined Storage at IBM Edge2015

May 21, 2015

At Edge2015 software defined storage (SDS) primarily meant IBM Spectrum Storage, the new storage software portfolio designed to address data storage inefficiencies by separating storage functionality from the underlying hardware through an intelligent software layer. To see what DancingDinosaur posted on Spectrum Storage in February when it was unveiled click here. Spectrum became the subject of dozens of sessions at the conference. Check out a general sampling of Edge2015 sessions here.

Jon Toigo, a respected storage consultant and infuriating iconoclast to some, jumped into the discussion of legacy storage vs. SDS at a session provocatively titled 50 Shades of Grey. He started by declaring “true SANs never reached the market.” On the other hand, SDS promises the world—storage flexibility, efficiency, avoidance of vendor lock-in, and on and on.

 edge2015 toigo san

Courtesy Jon Toigo (click to enlarge)

What the industry actually did as far as storage sharing, Toigo explained, was provide serial SCSI over a physical layer fabric and the use of a physical layer switch to make and break server-storage connections at high speed. Although network-like there was no management layer (which should be part of any true network model, he believes). Furthermore, the result was limited by the Fibre Channel Protocol and standards designed so that “two vendors could implement switch products that conformed to the letter of the standard…with absolute certainty that they would NOT work together,” said Toigo. iSCSI later enabled storage fabrics using TCP/IP, which made it easier to deploy the fabric since organizations already were deploying TCP/IP networks for other purposes.

Toigo’s key requirement: unified storage management, which means managing the diversity and heterogeneity of the arrays comprising the SAN. The culprit preventing this, as he sees it, are so call value-add services on array controllers that create islands of storage. You know these services: thin provisioning, on-array tiering, mirroring, replication, dedupe, and more. The same value-add services are the culprits driving the high cost of storage. “Storage hardware components are commoditized, but value-add software sustains pricing.”

With Spectrum Storage IBM incorporates more than 700 patents and is designed to help organizations transform to a hybrid cloud business model by managing massive amounts of data where they want it, how they want it, in a fast and easy manner from a single dashboard.  The software helps clients move data to the right location, at the right time to flash storage for fast access or to tape and cloud for the lowest cost.

This apparently works for Toigo, with only a few quibbles: vendors make money by adding more software, and inefficiency is added when they implement non-standard commands. IBM, however, is mostly in agreement with Toigo. According to IBM, a new approach is needed to help organizations address [storage] cost and complexity driven by tremendous data growth.  Traditional storage is inefficient in today’s world. However, Spectrum Storage software, IBM continued, helps organizations to more efficiently leverage their hardware investments to extract the full business value of data. Listen closely and you might even hear Toigo mutter Amen.

SDS may or may not be the solution. Toigo titled this session fifty shades of grey because the vendors can’t even agree on a definition for what constitutes SDS.  Yet, it is being presented as a panacea for everything that is wrong with legacy storage.

The key differentiator for Toigo is where a vendor’s storage intelligence resides; on the array controller, in the server hypervisor, or part of the software stack. As it turns out, some solutions are hypervisor dedicated or hypervisor dependent.  VMware’s Virtual SAN, for instance, only works with its hypervisor.  Microsoft’s Clustered Storage Spaces is proprietary to Microsoft, though it promises to share its storage with VMware – simple as pie, just convert your VMware workload into Microsoft VHD format and import it into Hyper-V so you can share the Microsoft SDS infrastructure.

IBM Spectrum passes Toigo’s 50 Shades test. It promises simple, efficient storage without the cost or complexity of dedicated hardware. IBM managers at Edge2015 confirmed Spectrum could run on generic servers and with generic disk arrays. With SDS you want everything agnostic for maximum flexibility.

Toigo’s preferred approach: virtualized SDS with virtual storage pools and centralized select value-add services that can be readily allocated to any workload regardless of the hypervisor. DancingDinosaur will drill down into other interesting Edge2015 sessions in subsequent posts.

DancingDinosaur is Alan Radding, a veteran IT analyst and writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing on Technologywriter.com and here.

POWER Systems for Cloud & Linux at IBM Edge2015

April 23, 2015

In October, IBM introduced a new range of POWER systems capable of handling massive amounts of computational data faster at nearly 20 percent better price/performance than comparable Intel Xeon v3 processor-based systems, delivering to clients a superior alternative to closed, commodity-based data center servers. DancingDinosaur covered it last October here. Expect this theme to play out big at IBM

Edge2015 in Las Vegas, May 10-15. Just a sampling of a few of the many POWER sessions makes that clear:

IBM Power S824L

Courtesy of Studio Stence, Power S824L (click to enlarge)

(lCV1655) Linux on Power and Linux on Intel: Side By Side, IT Economics Positioning; presenter Susan Proietti Conti

Based on real cases studied by the IBM Eagle team for many customers in different industries and geographies, this session explains where and when Linux on Power provides a competitive alternative to Linux on Intel. The session also highlights the IT economic value of architecture choices provided by the Linux/KVM/Power stack, based on open technologies brought by POWER8 and managed through OpenStack. DancingDinosaur periodically covers studies like these here and here.

(lCV1653) Power IT Economics Advantages for Cloud Service Providers and Private Cloud Deployment; presenter Susan Proietti Conti

Since the announcement of POWER8 and building momentum of the OpenPOWER consortium, there are new reasons for cloud service providers to look at Power technology to support their offerings. As an alternative open-based technology to traditional proprietary technologies, Power offers many competitive advantages that can be leveraged for cloud service providers to deliver IaaS services and other types of service delivery. This session illustrates what Power offers by highlighting client examples and the results of IT economics studies performed for different cloud service providers.

(lSY2653) Why POWER8 Is the Platform of Choice for Linux; presenter Gary Andrews

Linux is the platform of choice for running next generation workloads. With POWER8, IBM is investing heavily into Linux and is adding major enhancements to the Power platform to make it the server of choice for running Linux workloads. This session discusses the new features and how they can help run business faster and at lower costs on the Power platform. Andrews also points out many advanced features of Linux on Power that you can’t do with Linux on x86. He shows how competitive comparisons and performance tests demonstrate that POWER8 increases the lead over x86 latest processor family. In short, attend this session to understand the competitive advantages that POWER8 on Linux can deliver compared to Linux on x86.

(pBA1244) POWER8: Built for Big Data; presenter William Starke

Starke explains how IBM technologies from semiconductors through micro-architecture, system design, system software, and database and analytic software culminate in the POWER8 family of products optimized around big data analytics workloads. He shows how the optimization across these technologies delivers order-of-magnitude improvements via several example scenarios.

 (pPE1350) Best Practices Guide to Get Maximum Performance from IBM POWER8; presenter Archana Ravindar

This session presents a set of best practices that have been tried and tested in various application domains to get the maximum performance of an application on a POWER8 processor. Performance improvement can be gained at various levels: the system level, where system parameters can be tuned; the application level, where some parameters can be tuned as there is no one-size-fits-all scenario; and the compiler level, where options for every kind of application have shown to improve performance. Some options are unique to IBM and give an edge over competition in gaming applications. In cases where applications are still under development, Ravindar presents guidelines to ensure the code runs fastest on Power.

DancingDinosaur supports strategies that enable data centers to reuse existing resources like this one. (pCV2276) Developing a POWERful Cloud Strategy; presenter, Susan Schreitmueller

Here you get to examine decision points for how and when to use an existing Power infrastructure in a cloud environment. This session covers on-premises and off-premises, single vs. multi-tenant hosting, and security concerns. You also review IaaS, PaaS, and hybrid cloud solutions incorporating existing assets into a cloud infrastructure. Discover provisioning techniques to go from months to days and then to hours for new instances.

One session DancingDinosaur hasn’t found yet is whether it is less costly for an enterprise to virtualize a couple of thousand Linux virtual machines on one of the new IBM Power servers pictured above or on the z13 as an Enterprise Linux server purchased under the System z Solution Edition Program. Hmm, will have to ask around about that. But either way you’d end up with very low cost VMs compared to x86.

Of course, save time for the free evening entertainment. In addition to Penn & Teller, a pair of magicians, and rocker Grace Potter, here, there will be a weird but terrific group, 2Cellos as well.

DancingDinosaur is Alan Radding, a veteran IT analyst and writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing on Technologywriter.com and here. Please join DancingDinosaur at IBM Edge2015. You will find me hanging out wherever people gather around available power outlets to recharge mobile devices.

Storage Looms Large at IBMEdge 2015

April 17, 2015

Been a busy year in storage with software defined storage (SDS), real-time compression, flash, storage virtualization, OpenStack, and more all gaining traction. Similarly, big data, analytics, cloud, and mobile are impacting storage. You can expect to find them and more at IBM Edge2015, coming May 10-15 in Las Vegas.

 But storage continues to make news every week. Recently IBM scientists demonstrated an areal recording density triumph, hitting 123 billion bits of uncompressed data per square inch on low cost, particulate magnetic tape. That translates into the equivalent of a 220 terabyte tape cartridge that could fit in the palm of your hand, or comparable to 1.37 trillion mobile text messages or the text of 220 million books, which would require a 2,200 km bookshelf spanning from Las Vegas to Houston, Texas. (see graphic below)

Tape compression breakthrough

Courtesy of IBM (click to enlarge)

Let’s take a look at some sessions delving into the current hot storage topics at Edge2015, starting with tape, since we’ve been talking about it.

(sSS1335) The Future of Tape; presenter Mark Lantz. He discusses current and future scaling trends of magnetic tape technology—see announcement above—from the perspective of IBM Research. He begins by first comparing recent scaling trends of both tape and hard disk drive technology. He then looks at future capacity scaling potential of tape and hard disks. In that context he offers an in-depth look at a new world record tape areal density demonstration of more than 100 Gb/in2, performed by IBM research in collaboration with Fujifilm, using low cost particulate tape media. He also discusses the new hardware and tape media technologies developed for this demonstration as well as key challenges for the continued scaling of tape.

If you are thinking future, check out this session too. (sBA2523) Part III: A Peek into the Future; presenter Bruce Hillsberg. This session looks at novel and innovate technologies to address clients’ most challenging technical and business problems across a wide range of technologies and disciplines. The presentation looks at everything from the most fundamental materials level all the way to working on the world’s largest big data problems. Many of the technologies developed by the Storage Systems research team lead to new IBM products or become new features in existing products. Topics covered in this lecture include atomic scale storage, research into new materials, advances in current storage media, advanced object stores, cloud storage, and more.

Combine big data, flash, and the z13 all here. (sBA1952) How System z13 and IBM DS8870 Flash Technology Enables Your Hadoop Environments; presenter Renan Ugalde.  Analyzing large amounts of data introduces challenges that can impact the goals of any organization. Companies require a reliable and high performing infrastructure to extract value from their structure and unstructured data. The unique features offered by the integration of IBM System z13 and DS8870 Flash technology enable a platform to support real-time decisions such as fraud detection. This session explains how integration among System z13, DS8870, and Hadoop maximizes performance by enabling the infrastructure’s unique big data capabilities.

Jon Toigo is an outstanding non-IBM presenter and somewhat of an iconoclast when it comes to storage. This year he is offering a 3-part session on Disaster Recovery Planning in an Era of Mobile Computing and Big Data:

  • (aBA2511) Part I: For all the hype around hypervisor-based computing and new software-defined infrastructure models, the ongoing need for disaster preparedness is often being buried in the discussion. High availability server clustering is increasingly believed to trump disaster recovery preparations, despite the fact that the transition to an agile data center is fraught with disaster potentials. In the first of three sessions, Toigo looks at the trends that are occurring in IT and the potential they present for disruption.
  • sBA2512) Part II: builds on the previous session by examining the technologies available for data protection and the trend away from backups in favor of real-time mirroring and replication. He notes promising approaches, including storage virtualization and object storage that can make a meaningful contribution.
  • (sBA2513) Part III: completes his disaster recovery planning series with the use of mobile computing technologies and public clouds as an adjunct to successful business recovery following an unplanned interruption event. Here he discusses techniques and technologies that either show promise as recovery expediters or may place businesses at risk of an epic fail.

Several SDS sessions follow: (sSS0884) Software Defined Storage — Why? What? How? Presenter: Tony Pearson. Here Pearson explains why companies are excited about SDS, what storage products and solutions IBM has to offer, and how they are deployed. This session provides an overview of the new IBM Spectrum Storage family of offerings.

 A second session by Pearson. (sCV3179): IBM Spectrum Storage Integration in IBM Cloud Manager with OpenStack: IBM’s Cloud Storage Options; presenter Tony Pearson. This session will look at the value of IBM storage products in the cloud with a focus on OpenStack. Specifically, it will look at how Spectrum Virtualize can be integrated and used in a complete 3-tier app with OpenStack.

Finally, (sSS2453) Myth Busting Software Defined Storage – Top 7 Misconceptions; presenter Jeffrey Barnett. This session looks at the top misconceptions to cut through the hype and understand the real value potential. DancingDinosaur could only come up with six misconceptions. Will have to check out this session for sure.

Of course, save time for the free evening entertainment. In addition to Penn & Teller, a pair of magicians, and rocker Grace Potter, here. There also will be a weird but terrific group, 2Cellos. Stick with it to the end (about 3 min.) for the kicker.

DancingDinosaur is Alan Radding, a veteran IT analyst and writer. Follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing on Technologywriter.com and here. And join DancingDinsosaur at IBM Edge2015. You will find me hanging out wherever people gather around available power outlets to recharge mobile devices.


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