Can Flash Replace Hard Disk for Enterprise Storage?

Earlier this month IBM announced a strategic initiative, the IBM FlashSystem, to drive Flash technology deeper into the enterprise. The IBM FlashSystem is a line of all-Flash storage appliances based on technology IBM acquired from Texas Memory Systems.

IBM’s intent over time is to replace hard disk drive (HDD) for enterprise storage with flash. Flash can speed the response of servers and storage systems to data requests from milliseconds to microseconds – an order of magnitude improvement. And because it is all electronic—nothing mechanical involved—and being delivered cost-efficiently at even petabyte scale, it can remake data center economics, especially for transaction-intensive and IOPS-intensive situations.

For example, the IBM FlashSystem 820 is the size of a pizza box but 20x faster than spinning hard drives and can store up to 24 TB of data. The entry-level IBM FlashSystem, with an approximate street price for an entry 820 (10 TB usable RAID 5) runs about $150K (or $15 per gigabyte).  At the high end, you can assemble a 1 PB FlashSystem that fits in one rack and delivers 22 million IOs per second (IOPS). You would need 630 racks of high capacity hard disk drives or 315 racks of performance optimized disk to generate an equal amount of IOPS.

For decades storage economics has been driven by the falling cost per unit of storage, and storage users have benefited from a remarkable ride down the cost curve thanks to Moore’s law. The cost per gigabyte for hard disk drive (HDD) has dropped steadily, year after year. You now can buy a slow, USB-connected 1TB consumer-grade disk drive for under $89!

With low cost per gigabyte storage, storage managers could buy cheap gigabytes, which enabled backup to disk and long-term disk archiving. Yes, tape is even cheaper on a cost per gigabyte basis but it is slow and cumbersome and prone to failure. Today HDD rules.

Silicon-based memory, however, has been riding the Moore’s Law cost slope too. In the last decade memory has emerged as a new storage media through memory-based storage in the form of RAM, DRAM, cache, flash, and solid state disk (SSD) technology. Prohibitively expensive to use for mass storage initially, the magic of Moore’s law combined with other technical advances and mass market efficiencies have made flash something to think about seriously for enterprise production storage.

The IBM FlashSystem changes data center economics. One cloud provider reported deploying 5TB in 3.5 inches of rack space compared to deploying 1300 hard disks to achieve 400k IOPS and it did so at one-tenth the cost.  Overall, Wikibon reports an all Flash approach will lower total system costs by 30%; that’s $4.9m for all flash compared to $7.1m for hard disk.  Specifically, it reduced software license costs 38%, required 17% few servers, and lowered environmental costs by 74% and operational support costs by 35%.  At the same time it boosted storage utilization by 50% while reducing maintenance and simplifying management with corresponding labor savings. Combine flash with compression, deduplication, and thin provisioning and the economics look even better.

For data center managers, this runs counter to everything they learned about the cost of storage. Traditional storage economics starts with the cost of hard disk storage being substantially less than the cost of SSD or Flash on a $/GB basis. Organizations could justify SSD, only by using it in small amounts to tap its sizeable cost/IOPS advantage for IOPS-intensive workloads.

Any HDD price/performance advantage is coming to an end. As reported in PC World, Steve Mills, IBM Senior Vice President noted:  Right now, generic hard drives cost about $2 per gigabyte. An enterprise hard drive will cost about $4 per gigabyte, and a high-performance hard drive will run about $6 per gigabyte. If an organization stripes its data across more disks for better performance, the cost goes up to about $10 per gigabyte. In some cases, where performance is critical, hard-drive costs can skyrocket to $30 or $50 per gigabyte.

From a full systems perspective (TCO for storage) Flash looks increasingly competitive. Said Ambuj Goyal, General Manager, Systems Storage, IBM Systems & Technology Group: “The economics and performance of Flash are at a point where the technology can have a revolutionary impact on enterprises, especially for transaction-intensive applications.” But this actually goes beyond just transactions. Also look at big data analytics workloads, technical computing, and any other IOPS-intensive work.

Almost every major enterprise storage vendor—EMC, NetApp, HP, Dell, Oracle/Sun—is adding SSD to their storage offerings. It is time to start rethinking your view of storage economics when flash can replace HDD and deliver better performance, utilization, and reliability even while reducing server software licensing costs and energy bills.

Lessons from IBM Eagle TCO Analyses

A company running an obsolete z890 mainframe with what amounted to 0.88 processors (332 MIPS) planned a migration to a distributed system consisted of 36 distributed UNIX servers. The production workload consisted of applications, database, testing, development, security, and more.  Five years later, the company was running the same in the 36-server, multi-core (41x more cores than the z890) distributed environment except that its 4-year TCO went from $4.9 million to $17.9 million based on an IBM Eagle study.  The lesson, the Eagle team notes: cores drive platform costs in distributed systems.

Then there is the case of a 3500 MIPS mainframe shop that budgeted $10 million for a 1-year migration to a distributed environment. Eighteen months into the project, now six months behind schedule, the company had spent $25 million and only managed to offload 350 MIPS. In addition, it had to increase staff to cover the  over-run, implement steps to replace mainframe automation, had to acquire additional distributed capacity over the initial prediction (to support only 10% of total MIPS offloaded), and had to extend the period of running the old and the new systems in parallel at even more cost due to the schedule overrun. Not surprisingly, the executive sponsor is gone.

If the goal of a migration to the distributed environment is cost savings, the IBM Eagle team has concluded after 3 years of doing such analyses, most migrations are a failure. Read the Eagle FAQ here.

The Eagle TCO team was formed in 2007 and since then reports completing over 300 user studies.  Often its studies are used to determine the best platform among IBM’s various choices for a given set of workloads, usually as part of a Fit for Purpose. In other cases, the Eagle analysis is aimed at enabling a System z shop to avoid a migration to a distributed platform. The Eagle team, in fact, is platform agnostic until it completes its quantitative analysis, when the resulting numbers generally make the decisions clear.

Along the way, the Eagle team has learned a few lessons.  For example:  re-hosting projects tend to be larger than anticipated. The typical one-year projection will likely turn into a two- or three-year project.

The Eagle team also offers the following tips, which can help existing shops that aren’t necessarily looking to migrate but just want to minimize costs:

• Update hardware and software; new systems generally are more cost-efficient. For example one bank upgraded from z/OS 1.6 to 1.8 and reduced each LPAR’s MIPS by 5% (monthly software cost savings paid for the upgrade almost immediately)
• Schedule workloads to take advantage of sub-capacity software pricing for platforms that offer it, which may produce free workloads
• Consolidate workloads on Linux, which invariably saves money, especially when consolidating many Linux virtual servers on a mainframe IFL. (A recent debate raged on LinkedIn focused on how many virtual instances can run on an IFL with some suggesting a max of 20. The official IBM figure:  you can consolidate up to 60 distributed cores or more on a single System z core; a single System z core = an IFL.)
• Changing the database can impact capacity requirements and therefore costs, resulting in lower hardware and software costs
• Consider the  IBM mainframe Solution Edition program, which is the best mainframe deal going, enabling you to acquire a new mainframe for workloads you’ve never run on a mainframe for a deeply discounted package price including hardware, software, middleware, and 3 years of maintenance.

 BottomlineIT generally is skeptical of TCO analyses from vendors. To be useful the analysis needs to include full context, technical details (components, release levels, and prices), and specific quantified benchmark results.  In addition, there are soft costs that must be considered.  Eagle analyses generally do that.

In the end, the lowest acquisition cost or even the lowest TCO isn’t necessarily the best platform choice for a given situation or workload. Determining the right platform requires both quantifiable analysis and judgment.

Mainframe Workload Economics

IBM never claims that every workload is suitable for the zEnterprise. The company prefers to talk about platform issues in terms of fit-for-purpose or tuned-to-the-task. With the advent of hybrid computing, the low cost z114, and now the expected low cost version of the zEC12 later this year, however, you could make a case for any workload that benefits from the reliability, security, and efficiency of the zEnterprise mainframe is fair game.

John Shedletsky, VP, IBM Competitive Project Office, did not try to make that case. To the contrary, earlier this week he presented the business case for five workloads that are optimum economically and technically on the zEnterprise.  They are:  transaction processing, critical data workloads, batch processing, co-located business analytics, and consolidation-on-one-platform. None of these should be a surprise; possibly with the exception of analytics and consolidated platform they represent traditional mainframe workloads.  BottomlineIT covered Shedletsky’s mainframe cost/workload analysis last year here.

This comes at a time when IBM has started making a lot of noise about new and different workloads on the zEnterprise. Doug Balog, head of IBM System z mainframe group, for example, was quoted widely in the press earlier this month talking about bringing mobile computing workloads to the z. Says Balog in Midsize Insider: “I see there’s a trend in the market we haven’t directly connected to z yet, and that’s this mobile-social platform.”

Actually, this isn’t even all that new either. BottomlineIT’s sister blog, DancingDinosaur, was writing about organizations using SOA to connect CICS apps running on the z to users with mobile devices a few years ago here.

What Shedletsky really demonstrated this week was the cost-efficiency of the zEC12.  In one example he compared a single workload, app production/dev/test running on a 16x, 32-way HP Superdome and an 8x, 48-way Superdome with a zEC12 41-way. The zEC12 delivered the best price/performance by far, $111 million (5yr TCA) for the zEC12 vs. $176 million (5yr TCA) for the two Superdomes.

When running Linux on z workloads with the zEC12 compared to 3 Oracle database workloads (Oracle Enterprise Edition, Oracle RAC, 4 server nodes per cluster) supporting 18K transactions/sec.  running on 12 HP DL580 servers (192 cores) the HP system priced out at $13.2 million (3yr TCA) compared to a zEC12 running 3 Oracle RAC clusters (4 nodes per cluster, each as a Linux guest) with 27 IFLs that priced out at $5.7 million (3yr TCA). The zEC12 came in at less than half the cost.

With analytics such a hot topic these days Shedletsky also presented a comparison of the zEnterprise Analytics System 9700 (zEC12, DB2 v10, z/OS, 1 general processor, 1 zIIP) and an IDAA with a current Teradata machine. The result: the Teradata cost $330K/queries per hour compared to $10K/queries per hour.  Workload time for the Teradata was 1,591 seconds for 9.05 queries per hour compared to 60.98 seconds and 236 queries per hour on the zEC12. The Teradata total cost was $2.9 million compared to $2.3 million for the zEC12.

None of these are what you would consider new workloads, and Shedletsky has yet to apply his cost analysis to mobile or social business workloads. However, the results shouldn’t be much different. Mobile applications, particularly mobile banking and other mobile transaction-oriented applications, will play right into the zEC12 strengths, especially when they are accessing CICS on the back end.

While transaction processing, critical data workloads, batch processing, co-located business analytics, and consolidation-on-one-platform remain the sweet spot for the zEC12, Balog can continue to make his case for mobile and social business on the z. Maybe in the next set of Shedletsky comparative analyses we’ll see some of those workloads come up.

For social business the use cases aren’t quite clear yet. One use case that is emerging, however, is social business big data analytics. Now you can apply the zEC12 to the analytics processing part at least and the efficiencies should be similar.

Winning the Coming Talent War Mainframe Style

The next frontier in the ongoing talent war, according to McKinsey, will be deep analytics, a critical weapon required to probe big data in the competition underpinning new waves of productivity, growth, and innovation. Are you ready to compete and win in this technical talent war?

Similarly, Information Week contends that data expertise is called for to take advantage of data mining, text mining, forecasting, and machine learning techniques. As it turns out the mainframe is ideally is ideally positioned to win if you can attract the right talent.

Finding, hiring, and keeping good talent within the technology realm is the number one concern cited by 41% of senior executives, hiring managers, and team leaders responding to the latest Harris Allied Tech Hiring and Retention Survey. Retention of existing talent was the next biggest concern, cited by 19.1%.

This past fall, CA published the results of its latest mainframe survey that came to similar conclusions. It found three major trends on the current and future role of the mainframe:

1. The mainframe is playing an increasingly strategic role in managing the evolving needs of the enterprise
2. The mainframe as an enabler of innovation as big data and cloud computing transform the face of enterprise IT
3. Demand for tech talent with cross-disciplinary skills to fill critical mainframe workforce needs in this new view of enterprise IT

Among the respondents to the CA survey, 76% of global respondents believe their organizations will face a shortage of mainframe skills in the future, yet almost all respondents, 98%, felt their organizations were moderately or highly prepared to ensure the continuity of their mainframe workforce. In contrast, only 8% indicated having great difficulty finding qualified mainframe talent while 61% reported having some difficulty in doing so.

The Harris survey was conducted in September and October 2012. Its message is clear: Don’t be fooled by the national unemployment figures, currently hovering above 8%.  “In the technology space in particular, concerns over the ability to attract game-changing talent has become institutional and are keeping all levels of management awake at night,” notes Harris Allied Managing Director Kathy Harris.

The reason, as suggested in recent IBM studies, is that success with critical new technologies around big data, analytics, cloud computing, social business, virtualization, and mobile increasingly are giving top performing organizations their competitive advantage. The lingering recession, however, has taken its toll; unless your data center has been charged to proactively keep up, it probably is saddled with 5-year old skills at best; 10-year old skills more likely.

The Harris study picked up on this. When asking respondents the primary reason they thought people left their organization, 20% said people left for more exciting job opportunities or the chance to get their hands on some hot new technology.

Some companies recognize the problem and belatedly are trying to get back into the tech talent race. As Harris found when asking about what companies are doing to attract this kind of top talent 38% said they now were offering great opportunities for career growth. Others, 28%, were offering opportunities for professional development to recruit top tech pros. A fewer number, 24.5%, were offering competitive compensation packages while fewer still, 9%, offering competitive benefits packages.

To retain the top tech talent they already had 33.6% were offering opportunities for professional development, the single most important strategy they leveraged to retain employees. Others, 24.5%, offered opportunities for career advancement while 23.6% offered competitive salaries. Still a few hoped a telecommuting option or competitive bonuses would do the trick.

Clearly mainframe shops, like IT in general, are facing a transition as Linux, Java, SOA, cloud computing, analytics, big data, mobile, and social play increasing roles in the organization and the mainframe gains the capabilities to play in all these arenas. Advanced mainframe skills like CICS are great but it’s just a start. You also need Rest, Hadoop, and a slew of mobile, cloud, and data management skill sets.  At the same time, hybrid systems and expert integrated systems like IBM PureSystems and zEnterprise/zBX give shops the ability to tap a broader array of tech talent while baking in much of the expertise required.

The Use Case and Business Case for SSD

PwC is bullish on mobile, projecting a 35% CAGR through 2015, driven in large part by solid state disk (SSD) technology.  The PwC researchers now see it extending beyond mobile to other types of computing.

Deloitte takes SSD enthusiasm even further: By the end of 2012, SSD will likely store data in 90% of mobile devices (smartphones, tablets, MP3 players), up from just 20% in 2006, the consulting firm predicts. More surprising, Deloitte expects up to 15% of laptops and netbooks to rely on SSDs, four times more than in 2010. Even in the data center, SSDs could rise to 10%.

The growing penetration of SSD into enterprise data centers presents a  challenge to enterprise data center trying to identify the best use cases figure out how it fits into their storage strategy. Even with the price-performance improvements, however, SSD remains significantly more expensive than hard disk drive (HDD) storage on a cost-per-gigabyte basis.  Any adoption of SSD will require building a compelling business case for SSD.

“The increasing use of flash in enterprise solutions, explosive growth of mobile client devices, and lower SSD pricing is creating a perfect storm for increased SSD shipments and revenue over our forecast,” according to IDC’s 2012 market report.  The researchers expect SSD shipments to increase at a compound annual growth rate (CAGR) of 51.5% from 2010 to 2015.

The initial enterprise use cases revolve around workloads that require extremely low latency and workloads that demand fast performance or high I/O throughput.  It also can be useful in data centers scrambling to reduce energy consumption or are cramped for rack space. A small amount of SSD can replace a large amount of HDD in a rack.

For example, Penn State turned to SSD to speed up nightly backup. Its solution: a flash array from Texas Memory Systems (acquired by IBM) instead of increasing the number of HDD spindles. It paid off in a 6x improvement in nightly backup performance with two 1U flash arrays replacing 200 15k disks and reducing power consumption by 90% in the process.

With SSD prices dropping below $1 per gigabyte that still leaves SSD considerably more expensive than HDD on a cost/gigabyte basis.  Cost/gigabyte, however, is not the only cost metric important to enterprise data centers.

SSD has at least two cost metrics it brings to the party that you can use to build the business case for SSD:  dramatically lower cost in terms of I/O performance. This is particularly apparent when you look the I/O cost per second (IOPS).  SSD also requires considerably less data center energy and space.

The way you boost IOPS performance with HDD is to aggregate hundreds, or more likely, thousands of the fastest spinning HDDs to boost IOPS performance. Even at the low HDD cost/gigabyte, the cost adds up.

Also, few data centers these days have cheap rack space to spare so more rack space will need to be found, adding to the data center real estate cost. Finally, all those spinning disks consume electricity, raising energy costs so add to the cost of HDD the cost of data center space and energy. On a cost/IOPS basis of a few thousand HDDs, which is what it would take to generate a comparable level of IOPS to a just a few SSDs, the HDD approach is no IOPS bargain. SSD storage, by the way, uses 90% or less energy than HDD. Figured on a cost/IOPS basis, SSD energy consumption is negligible. This is the foundation of your business case.

This is not to say that SSD has no drawbacks. SSD life expectancy can be a concern. In short, SSDs can wear out.

The SSD industry has come up with several solutions to the wear out problem. The most widely adopted is load-leveling. Through load-leveling, writes are distributed across the cells to minimize wear of any cell. Through load-leveling organizations can effectively stretch the useful life of SSD by years.

It is unlikely that enterprise data centers will completely replace HDD storage with SSD. In the meantime, polish your business case for SSD. You’ll want it sooner or later.

Achieving the Private Cloud Business Payoff Fast

Nationwide Insurance eliminated both capital and operational expenditures through a private cloud and expects to save about $15 million over three years. In addition, it expects the more compact and efficient private cloud landscape to mean lower costs in the future.

The City of Honolulu turned to a private cloud and reduced application deployment time from one week to only hours. It also reduced the licensing cost of one database by 68%. Better still; a new property tax appraisal system resulted in $1.4 million of increased tax revenue in just three months.

The private cloud market, especially among larger enterprises, is strong and is expected to show a CAGR of 21.5% through 2015, according to research distributed by ReportLinker.com. Another report from Renub Research quotes analysts saving security is a big concern for enterprises that may be considering the use of public cloud. For such organizations, the private cloud represents an alternative with a tighter security model that would enable their IT managers to control the building, deployment and management of those privately owned, internal clouds.

Nationwide and Honolulu each built their private clouds on the IBM mainframe. From its introduction last August, IBM has aimed the zEC12 at cloud use cases, especially private clouds. The zEC12’s massive virtualization capabilities make it possible to handle private cloud environments consisting of thousands of distributed systems running Linux on zEC12.

One zEC12, notes IBM, can encompass the capacity of an entire multi-platform data center in a single system. The newest z also enables organizations to run conventional IT workloads and private cloud applications on one system.  Furthermore, if you are looking at a zEC12 coupled with the zBX (extension cabinet) you can have a multi-platform private cloud running Linux, Windows, and AIX workloads.  On a somewhat smaller scale, you can build a multi-platform private cloud using the IBM PureSystems machines.

Organizations everywhere are adopting private clouds.  The Open Data Center Alliance reports faster private cloud adoption than originally predicted. Over half its survey respondents will be running more than 40% of their IT operations in private clouds by 2015.

Mainframes make a particularly good private clouds choice.  Nationwide, the insurance company, initially planned to consolidate 3000 distributed servers to Linux virtual servers running on several z mainframes, creating a multi-platform private mainframe cloud optimized for its different workloads. The goal was to improve efficiency.

The key benefit: higher utilization and better economies of scale, effectively making the mainframes into a unified private cloud—a single set of resources, managed with the same tools but optimized for a variety of workloads. This eliminated both capital and operational expenditures and is expected to save about $15 million over three years. The more compact and efficient zEnterprise landscape also means low costs in the future too. Specifically, Nationwide is realizing an 80% reduction in power, cooling and floor space despite an application workload that is growing 30% annually, and practically all of it handled through the provisioning of new virtual servers on the existing mainframe footprint.

The City and County of Honolulu needed to increase government transparency by providing useful, timely data to its citizens. The goal was to boost citizen involvement, improve delivery of services, and increase the efficiency of city operations.

Honolulu built its cloud using an IFL engine running Linux on the city’s z10 EC machine. Between Linux and IBM z/VM the city created a customized cloud environment. This provided a scalable self-service platform on which city employees could develop open source applications, and it empowered the general public to create and deploy citizen-centric applications.

The results: reduction in application deployment time from one week to only hours and 68% lower licensing costs for one database. The resulting new property tax appraisal system increased tax revenue by $1.4 million in just three months.

You can do a similar multi-platform private cloud with IBM PureSystems. In either case the machines arrive ready for private cloud computing. Or else you can piece together x86 servers and components and do it yourself, which entails a lot more work, time, and risk.

New Products Reduce Soaring Storage Costs

The latest EMC-sponsored IDC Digital Universe study projects that the digital universe will reach 40 zettabytes (ZB) by 2020, a 50-fold growth from the beginning of 2010!! Do you wonder why your storage budget keeps increasing? And the amount of data that requires protection—backup on some sort—is growing faster than the digital universe itself.  This clearly is not good for the organization’s storage budget.

Worse yet, from a budget standpoint, the investment on IT hardware, software, services, telecommunications and staff that could be considered the infrastructure of the digital universe will grow by 40% between 2012 and 2020. Investment in storage management, security, big data, and cloud computing will grow considerably faster.

Last July BottomlineIT partially addressed this issue with a piece of reducing your storage debt, here. Recent products from leading storage players promise to help you do it more easily.

Let’s start with EMC, whose most recent storage offering is the VMAX 40K Enterprise Storage System. Enterprise-class, it promises to deliver up to triple the performance and more than twice the usable capacity of any other offering in the Industry, at least that was the case seven months ago. But things change fast.

With the VMAX comes an enhanced storage tool that simplifies and streamlines storage management, enabling fewer administrators to handle more storage. EMC also brings a revamped storage tiering tool, making it easier to move data to less costly and lower performing storage when appropriate. This allows you to conserve your most costly storage for the data most urgently requiring it.

HP, which has been struggling in general through a number of self-inflicted wounds, continues to offer robust storage products. Recognizing that today’s storage challenges—vastly more data, different types of data, and more and different needs for the data—require new approaches HP revamped its Converged Storage architecture. According to an Evaluator Group study many organizations only use 30% of their physical disk capacity, effectively wasting the rest while forcing their admins to wrestle with multiple disparate storage products.

The newest HP storage products address this issue for midsize companies. They include the HP 3PAR StoreServ7000, which offers large enterprise-class storage availability and quality-of-service features at a midrange price point.  HP StoreAll, a scalable platform for object and file data access that provides a simplified environment for big data retention and cloud storage while reducing the need for additional administrators or hardware.  Finally, it introduced the HP StoreAll Express Query, a special data appliance that allows organizations to conduct search queries orders of magnitude faster than previous file system search methods. This expedites informed decision-making based on the most current data.

IBM revamped its storage line too for the same reasons.  Its sleekest offering, especially for midsize companies, is the Storwize V7000 Unified, which handles block and file storage.  It also comes as a blade for IBM’s hybrid (mixed platforms) PureSystems line, the Storwize Flex V7000. Either way it includes IBM’s Real-Time Compression (RtC).

RtC alone can save considerable money by reducing the amount of storage capacity an organization needs to buy, by delaying the need to acquire more storage as the business grows, and by speeding performance of storage-related functions. While other vendors offer compression, none can do what RtC does; it compresses active (production) data and with no impact on application performance. This is an unmatched and valuable achievement.

On top of that the V7000 applies built-in expertise to simplify storage management. It enables an administrator who is not skilled in storage to perform almost all storage tasks quickly, easily, and efficiently. Fewer lesser-skilled administrators can handle increasingly complex storage workloads and perform sophisticated storage tasks flawlessly.  This substantially reduces the large labor cost associated with storage.

NetApp also is addressing the same storage issues for midsize companies through its NetApp FAS3200 Series. With a new processor and memory architecture it promises up to 80% more performance, 100% more capacity, non-disruptive operations, and industry-leading storage efficiency.

Data keeps growing, and you can’t NOT store it. New storage products enable you to maximize storage utilization, optimize the business value from data, and minimize labor costs.

PaaS Gains Cloud Momentum

Guess you could say Gartner is bullish on Platform-as-a-Service (PaaS). The research firm declares: PaaS is a fast-growing core layer of the cloud computing architecture, but the market for PaaS offerings is changing rapidly.

The other layers include Software-as-a-Service (SaaS) and Infrastructure-as-a-Service (IaaS) but before the industry build-out of cloud computing is finished (if ever), expect to see many more X-as-a-Service offerings. Already you can find Backup-as-a-Service (BaaS). Symantec, for instance, offers BaaS to service providers, who will turn around and offer it to their clients.

But the big cloud action is around PaaS. Late in November Red Hat introduced OpenShift Enterprise, an enterprise-ready PaaS product designed to be run as a private, public or hybrid cloud. OpenShift, an open source product, enables organizations to streamline and standardize developer workflows, effectively speeding the delivery of new software to the business.

Previously cloud strategies focused on SaaS, in which organizations access and run software from the cloud. Salesforce.com is probably the most familiar SaaS provider. There also has been strong interest in IaaS, through which organizations augment or even replace their in-house server and storage infrastructure with compute and storage resources from a cloud provider. Here Amazon Web Services is the best known player although it faces considerable competition that is driving down IaaS resource costs to pennies per instance.

PaaS, essentially, is an app dev/deployment and middleware play. It provides a platform (hence the name) to be used by developers in building and deploying applications to the cloud. OpenShift Enterprise does exactly that by giving developers access to a cloud-based application platform on which they can build applications to run in a cloud environment. It automates much of the provisioning and systems management of the application platform stack in a way that frees the IT team to focus on building and deploying new application functionality and not on platform housekeeping and support services. Instead, the PaaS tool takes care of it.

OpenShift Enterprise, for instance, delivers a scalable and fully configured application development, testing and hosting environment. In addition, it uses Security-Enhanced Linux (SELinux) for reliable security and multi-tenancy. It also is built on the full Red Hat open source technology stack including Red Hat Enterprise Linux, JBoss Enterprise Application Platform, and OpenShift Origin, the initial free open source PaaS offering. JBoss Enterprise Application Platform 6, a middleware tool, gives OpenShift Enterprise a Java EE 6-certified on-premise PaaS capability.  As a multi-language PaaS product, OpenShift Enterprise supports Java, Ruby, Python, PHP, and Perl. It also includes what it calls a cartridge capability to enable organizations to include their own middleware service plug-ins as Red Hat cartridges.

Conventional physical app dev is a cumbersome process entailing as many as 20 steps from idea to deployment. Make it a virtual process and you can cut the number of steps down to 14; a small improvement. As Red Hat sees it, the combination of virtualization and PaaS can cut that number of steps to six; idea, budget, code, test, launch, and scale. PaaS, in effect, shifts app dev from a craft undertaking to an automated, cloud-ready assembly line. As such, it enables faster time to market and saves money.

Although Red Hat is well along in the PaaS market and the leader in open source PaaS other vendors already are jumping in and more will be joining them. IBM has SmartCloud Application Services as its PaaS offering.  Oracle offers a PaaS product as part of the Oracle Cloud Platform. EMC offers PaaS consulting and education but not a specific technology product.  When HP identifies PaaS solutions it directs you to its partners. A recent list of the top 20 PaaS vendors identifies mainly smaller players, CA, Google, Microsoft, and Salesforece.com being the exceptions.

A recent study by IDC projects the public cloud services market to hit $98 billion by 2016. The PaaS segment, the fastest growing part, will reach about $10 billion, up from barely $1 billion in 2009. There is a lot of action in the PaaS segment, but if you are looking for the winners, according to IDC, focus on PaaS vendors that provide a comprehensive, consistent, and cost effective platform across all cloud segments (public, private, hybrid). Red Hat OpenShift clearly is one; IBM SmartCloud Application Services and Microsoft Azure certainly will make the cut. Expect others.

Speed Time to Big Data with Appliances

Hadoop will be coming to enterprise data centers soon as the big data bandwagon picks up stream. Speed of deployment is crucial. How fast can you deploy Hadoop and deliver business value?

Big data refers to running analytics against large volumes of unstructured data of all sorts to get closer to the customer, combat fraud, mine new opportunities, and more. Published reports have companies spending $4.3 billion on big data technologies by the end of 2012. But big data begets more big data, triggering even more spending, estimated by Gartner to hit $34 billion for 2013 and over a 5-year period to reach as much as $232 billion.

Most enterprises deploy Hadoop on large farms of commodity Intel servers. But that doesn’t have to be the case. Any server capable of running Java and Linux can handle Hadoop. The mainframe, for instance, should make an ideal Hadoop host because of the sheer scalability of the machine. Same with IBM’s Power line or the big servers from Oracle/Sun and HP, including HP’s new top of the line Itanium server.

At its core, Hadoop is a Linux-based Java program and is usually deployed on x86-based systems. The Hadoop community has effectively disguised Hadoop to speed adoption by the mainstream IT community through tools like SQOOP, a tool for importing data from relational databases into Hadoop, and Hive, which enables you to query the data using a SQL-like language called HiveQL. Pig is a high-level platform for creating the MapReduce programs used with Hadoop. So any competent data center IT group could embark on Hadoop big data initiatives.

Big data analytics, however, doesn’t even require Hadoop.  Alternatives like Hortonworks Data Platform (HDP), MapR, IBM GPFS-SNC (Shared Nothing Cluster), Lustre, HPCC Systems, Backtype Storm (acquired by Twitter), and three from Microsoft (Azure Table, Project Daytona, LINQ) all promise big data analytics capabilities.

Appliances are shaping up as an increasingly popular way to get big data deployed fast. Appliances trade flexibility for speed and ease of deployment. By packaging hardware and software pre-configured and integrated they make it ready to run right out of the box. The appliance typically comes with built-in analytics software that effectively masks big data complexity.

For enterprise data centers, the three primary big data appliance players:

• IBM—PureData, the newest member of its PureSystems family of expert systems. PureData is delivered as an appliance that promises to let organizations quickly analyze petabytes of data and then intelligently apply those insights in addressing business issues across their organization. The machines come as three workload-specific models optimized either for transactional, operational, and big data analytics.

• Oracle—the Oracle Big Data Appliance is an engineered system optimized for acquiring, organizing, and loading unstructured data into Oracle Database 11g. It combines optimized hardware components with new software to deliver a big data solution. It incorporates Cloudera’s Apache Hadoop with Cloudera Manager. A set of connectors also are available to help with the integration of data.

• EMC—the Greenplum modular data computing appliance includes Greenplum Database for structured data, Greenplum HD for unstructured data, and DIA Modules for Greenplum partner applications such as business intelligence (BI) and extract, transform, and load (ETL) applications configured into one appliance cluster via a high-speed, high-performance, low-latency interconnect.

 And there are more. HP offers HP AppSystem for Apache Hadoop, an enterprise-ready appliance that simplifies and speeds deployment while optimizing performance and analysis of extreme scale-out Hadoop workloads. NetApp offers an enterprise-class Hadoop appliance that may be the best bargain given NetApp’s inclusive storage pricing approach.

As much as enterprise data centers loathe deploying appliances, if you are under pressure to get on the big data bandwagon fast and start showing business value almost immediately appliances will be your best bet. And there are plenty to choose from.

IBM Brings MEAP to All its Platforms

Mobile Enterprise Application Platforms (MEAP) are increasingly popular. With mobile as a strategic initiative IBM  is making its Mobile Development Lifecycle Solution v4.0 available on each of its platforms, from A (AIX) to Z (z/OS) and everything in-between (mainly Power and System x), including non-IBM platforms like HP, Mac, and Oracle (Sun/Solaris)

And IBM isn’t the only vendor to try to capture the mobile platform wave. The HP Enterprise Mobility Platform is intended to communication service providers. Of course, Oracle is there with its Mobile Rapid Application Development Platform that works on every platform by using HTML5, CSS3 and JavaScript for a true device agnostic solution. A smaller, lower cost player is Vervivo. An early, open standards-based player is KonyOne.

The IBM Mobile Development Lifecycle product, however, enables collaborative, mobile lifecycle management capabilities integrated with an enterprise-grade, standards-based, mobile application platform that is based on IBM Worklight for effective team development of mobile applications.

As mobile usage continues to grow worldwide—by the end of this year mobile transactions will have increased 50%–developing for mobile usage becomes an increasingly important consideration for organizations. Companies need to move beyond the initial one-off mobile projects that started them down the mobile path. Going forward they require a strategic approach that encompasses more than mobile device application coding and testing, just two aspects of the overall mobile app dev lifecycle.

Now the challenge is to ensure mobile apps are delivered on-time, with high quality, and meet business objectives. For this organizations need an approach that goes beyond the device SDKs. They need a comprehensive, team-based mobile app dev approach that provides not just a runtime infrastructure for deploying and running mobile applications for myriad devices but also an infrastructure to support rapid change, development, and delivery of quickly evolving mobile applications for business-critical data and transactions.

The mainframe, for its massive scalability and extreme high availability, can play a particularly important role in an organization’s mobile initiative, especially as the volume and value of mobile transactions increase. Already the System z mainframe is a leading platform for secure data serving and, according to IBM, the only commercial server to achieve Common Criteria Evaluation Assurance Level 5+ security classification, providing the confidence to run many different applications containing confidential data on the mainframe. And the mainframe is where much of the data users want to access from mobile devices will reside.

In particular, the newest mainframe, the new zEC12 builds on this with innovative security and privacy features to help protect data .Specifically, the zEC12 includes a state-of-the-art, tamper-resistant cryptographic co-processor, the Crypto Express4S, which provides privacy for transactions and sensitive data. It also incorporates transactional memory technology that IBM adapted to better support concurrent operations among a shared set of data, such as financial institutions processing transactions against the same set of accounts.

Making this all the more important is the anticipated growth of mobile transactions. According to Juniper Research, the value of remote transactions conducted via mobile devices is expected to exceed $730 billion annually by 2017. While Juniper sees major brands and retailers driving mobile transaction activity, IBM sees other types of transactions, such as flight check-in, client loyalty programs, employee self-service, the signing of legal documents, and other kinds of transactions that will drive the demand for mobile transaction security. Transactions, mobile and otherwise, are where the z excels.

IBM has pulled together a diverse set of capabilities to support the entire mobile lifecycle. The main pieces include IBM Worklight, IBM Endpoint Manager for Mobile Devices, and IBM WebSphere Cast Iron (Hypervisor edition). It is supplementing the core with tools like Tealeaf CXMobile, support for mobile app testing, support for mobile agile methodologies, and more.

Worldwide smartphone sales grew by 47% last year to 147 million units during the final quarter of 2011, according to Gartner. IDC estimates global downloads of mobile apps will reach 76.9 billion by 2014. It’s apparent the mobile wave is not diminishing anytime soon.

Enterprise data centers should expect to support an increasing amount of mobile traffic from new and different devices. This will present, at the least, significant new security and capacity challenges.  The z, and especially the zEC12with its recently updated software, previously covered by DancingDinosaur here, and enhancements like the Crypto Express4S, should be able to handle the challenges in stride, maybe with nothing more than some rethinking of MIPS consumption and assist processor usage.

Finally, one favor: Please take a moment to fill out this short survey. It is from Waterstone Management Group, a tech-focused management consulting firm that is attempting to gather a unique set of benchmarks and insights from a broad group of software industry professionals with the goal of sharing the summary with everyone who participates.  The scope of the survey is enterprise-wide but the respondent self-selects the areas they have responsibility for (one or more) and only answers questions specific to their area.  Each section contains 15-16 questions and should take no more than 10 min. Again, please click here for the survey.