We have been watching many variants on efficient packaging of servers for highly scalable workloads for years, including blades, modular servers, and dense HPC rack offerings from multiple vendors, most of the highly effective, and all highly proprietary. With the advent of Facebook’s Open Compute Project, the table was set for a wave of standardized rack servers and the prospect of very cost-effective rack-scale deployments of very standardized servers. But the IP for intelligently shared and managed power and cooling at a rack level needed a serious R&D effort that the OCP community, by and large, was unwilling to make. Into this opportunity stepped Intel, which has been quietly working on its internal Rack Scale Architecture (RSA) program for the last couple of years, and whose first product wave was officially outed recently as part of an announcement by Intel and Ericsson.
While not officially announcing Intel’s product nomenclature, Ericsson announced their “HDS 8000” based on Intel’s RSA, and Intel representatives then went on to explain the fundamental of RSA, including a view of the enhancements coming this year.
RSA is a combination of very standardized x86 servers, a specialized rack enclosure with shared Ethernet switching and power/cooling, and layers of firmware to accomplish a set of tasks common to managing a rack of servers, including:
· Asset discovery
· Switch setup and management
· Power and cooling management across the servers with the rack
Last year I published a reasonably well-received research document on Hadoop infrastructure, “Building the Foundations for Customer Insight: Hadoop Infrastructure Architecture”. Now, less than a year later it’s looking obsolete, not so much because it was wrong for traditional (and yes, it does seem funny to use a word like “traditional” to describe a technology that itself is still rapidly evolving and only in mainstream use for a handful of years) Hadoop, but because the universe of analytics technology and tools has been evolving at light-speed.
If your analytics are anchored by Hadoop and its underlying map reduce processing, then the mainstream architecture described in the document, that of clusters of servers each with their own compute and storage, may still be appropriate. On the other hand, if, like many enterprises, you are adding additional analysis tools such as NoSQL databases, SQL on Hadoop (Impala, Stinger, Vertica) and particularly Spark, an in-memory-based analytics technology that is well suited for real-time and streaming data, it may be necessary to begin reassessing the supporting infrastructure in order to build something that can continue to support Hadoop as well as cater to the differing access patterns of other tools sets. This need to rethink the underlying analytics plumbing was brought home by a recent demonstration by HP of a reference architecture for analytics, publicly referred to as the HP Big Data Reference Architecture.
On one level, IBM’s new z13, announced last Wednesday in New York, is exactly what the mainframe world has been expecting for the last two and a half years – more capacity (a big boost this time around – triple the main memory, more and faster cores, more I/O ports, etc.), a modest boost in price performance, and a very sexy cabinet design (I know it’s not really a major evaluation factor, but I think IBM’s industrial design for its system enclosures for Flex System, Power and the z System is absolutely gorgeous, should be in the MOMA*). IBM indeed delivered against these expectations, plus more. In this case a lot more.
In addition to the required upgrades to fuel the normal mainframe upgrade cycle and its reasonably predictable revenue, IBM has made a bold but rational repositioning of the mainframe as a core platform for the workloads generated by mobile transactions, the most rapidly growing workload across all sectors of the global economy. What makes this positioning rational as opposed to a pipe-dream for IBM is an underlying pattern common to many of these transactions – at some point they access data generated by and stored on a mainframe. By enhancing the economics of the increasingly Linux-centric processing chain that occurs before the call for the mainframe data, IBM hopes to foster the migration of these workloads to the mainframe where its access to the resident data will be more efficient, benefitting from inherently lower latency for data access as well as from access to embedded high-value functions such as accelerators for inline analytics. In essence, IBM hopes to shift the center of gravity for mobile processing toward the mainframe and away from distributed x86 Linux systems that they no longer manufacture.
I’ve been getting a steady trickle of inquires this year about the future of the mainframe from our enterprise clients. Most of them are more or less in the form of “I have a lot of stuff running on mainframes. Is this a viable platform for the next decade or is IBM going to abandon them.” I think the answer is that the platform is secure, and in the majority of cases the large business-critical workloads that are currently on the mainframe probably should remain on the mainframes. In the interests of transparency I’ve tried to lay out my reasoning below so that you can see if it applies to your own situation.
How Big is the Mainframe LOB?
It's hard to get exact figures for the mainframe contributions to IBM's STG (System & Technology Group) total revenues, but the data they have shared shows that their mainframe revenues seem to have recovered from the declines of previous quarters and at worst flattened. Because the business is inherently somewhat cyclical, I would expect that the next cycle of mainframes, rumored to be arriving next year, should give them a boost similar to the last major cycle, allowing them to show positive revenues next year.
I’ve been talking to a number of users and providers of bare-metal cloud services, and am finding the common threads among the high-profile use cases both interesting individually and starting to connect some dots in terms of common use cases for these service providers who provide the ability to provision and use dedicated physical servers with very similar semantics to the common VM IaaS cloud – servers that can be instantiated at will in the cloud, provisioned with a variety of OS images, be connected to storage and run applications. The differentiation for the customers is in behavior of the resulting images:
Deterministic performance – Your workload is running on a dedicated resource, so there is no question of any “noisy neighbor” problem, or even of sharing resources with otherwise well-behaved neighbors.
Extreme low latency – Like it or not, VMs, even lightweight ones, impose some level of additional latency compared to bare-metal OS images. Where this latency is a factor, bare-metal clouds offer a differentiated alternative.
Raw performance – Under the right conditions, a single bare-metal server can process more work than a collection of VMs, even when their nominal aggregate performance is similar. Benchmarking is always tricky, but several of the bare metal cloud vendors can show some impressive comparative benchmarks to prospective customers.
There is always a tendency to regard the major players in large markets as being a static background against which the froth of smaller companies and the rapid dance of customer innovation plays out. But if we turn our lens toward the major server vendors (who are now also storage and networking as well as software vendors), we see that the relatively flat industry revenues hide almost continuous churn. Turn back the clock slightly more than five years ago, and the market was dominated by three vendors, HP, Dell and IBM. In slightly more than five years, IBM has divested itself of highest velocity portion of its server business, Dell is no longer a public company, Lenovo is now a major player in servers, Cisco has come out of nowhere to mount a serious challenge in the x86 server segment, and HP has announced that it intends to split itself into two companies.
And it hasn’t stopped. Two recent events, the fracturing of the VCE consortium and the formerly unthinkable hook-up of IBM and Cisco illustrate the urgency with which existing players are seeking differential advantage, and reinforce our contention that the whole segment of converged and integrated infrastructure remains one of the active and profitable segments of the industry.
EMC’s recent acquisition of Cisco’s interest in VCE effectively acknowledged what most customers have been telling us for a long time – that VCE had become essentially an EMC-driven sales vehicle to sell storage, supported by VMware (owned by EMC) and Cisco as a systems platform. EMC’s purchase of Cisco’s interest also tacitly acknowledges two underlying tensions in the converged infrastructure space:
In this playbook, we do not predict the future of technology but we try to understand how, in the age of the customer, I&O must transform to support businesses by accelerating the speed of service delivery, enabling capacity when and where needed and improving customers and employee experience.
All industries mature towards commoditization and abstraction of the underlying technology because knowledge and expertise are cumulative. Our industry will follow an identical trajectory that will result in ubiquitous and easier to implement, manage and change technology.
Dell today announced its new FX system architecture, and I am decidedly impressed.
Dell FX is a 2U flexible infrastructure building block that allows infrastructure architects to compose an application-appropriate server and storage infrastructure out of the following set of resources:
Multiple choices of server nodes, ranging from multi-core Atom to new Xeon E5 V3 servers. With configurations ranging from 2 to 16 server nodes per enclosure, there is pretty much a configuration point for most mainstream applications.
A novel flexible method of mapping disks from up to three optional disk modules, each with 16 drives - the mapping, controlled by the onboard management, allows each server to appear as if the disk is locally attached DASD, so no changes are needed in any software that thinks it is accessing local storage. A very slick evolution in storage provisioning.
A set of I/O aggregators for consolidating Ethernet and FC I/O from the enclosure.
All in all, an attractive and flexible packaging scheme for infrastructure that needs to be tailored to specific combinations of server, storage and network configurations. Probably an ideal platform to support the Nutanix software suite that Dell is reselling as well. My guess is that other system design groups are thinking along these lines, but this is now a pretty unique package, and merits attention from infrastructure architects.
One of the developing trends in computing, relevant to both enterprise and service providers alike, is the notion of workload-specific or application-centric computing architectures. These architectures, optimized for specific workloads, promise improved efficiencies for running their targeted workloads, and by extension the services that they support. Earlier this year we covered the basics of this concept in “Optimize Scalable Workload-Specific Infrastructure for Customer Experiences”, and this week HP has announced a pair of server cartridges for their Moonshot system that exemplify this concept, as well as being representative of the next wave of ARM products that will emerge during the remainder of 2014 and into 2015 to tilt once more at the x86 windmill that currently dominates the computing landscape.
Specifically, HP has announced the ProLiant m400 Server Cartridge (m400) and the ProLiant m800 Server Cartridge (m800), both ARM-based servers packaged as cartridges for the HP Moonshot system, which can hold up to 45 of these cartridges in its approximately 4U enclosure. These servers are interesting from two perspectives – that they are both ARM-based products, one being the first tier-1 vendor offering of a 64-bit ARM CPU and that they are both being introduced with a specific workload target in mind for which they have been specifically optimized.
Very much in the shadows of all the press coverage and hysteria attendant on emerging cloud architectures and customer-facing systems of engagement are the nitty-gritty operational details that lurk like monsters in the swamp of legacy infrastructure, and some of them have teeth. And sometimes these teeth can really take a bite out of the posterior of an unprepared organization.
One of those toothy animals that I&O groups are increasingly encountering in their landscapes is the problem of what to do with Windows Server 2003 (WS2003). It turns out there are still approximately 11 million WS2003 systems running today, with another 10+ million instances running as VM guests. Overall, possibly more than 22 million OS images and a ton of hardware that will need replacing and upgrading. And increasing numbers of organizations have finally begun to take seriously the fact that Microsoft is really going to end support and updates as of July 2015.
Based on the conversations I have been having with our clients, the typical I&O group that is now scrambling to come up with a plan has not been willfully negligent, nor are they stupid. Usually WS2003 servers are legacy servers, quietly running some mature piece of code, often in satellite locations or in the shops of acquired companies. The workloads are a mix of ISV and bespoke code, but it is often a LOB-specific application, with the run-of-the-mill collaboration, infrastructure servers and, etc. having long since migrated to newer platforms. A surprising number of clients have told me that they have identified the servers, but not always the applications or the business owners – often a complex task for an old resource in a large company.