Cisco Press
2003 | 2002 | 2001 | 2000 | 1999 | |
Storage Software | $6621 | $5730 | $6157 | $6113 | $4640 |
Storage Services | $23,360 | $21,171 | $20,552 | $19,501 | $17,250 |
Note – In addition to the “lumpiness” of the software revenues, it is also critical to note the steady increase in storage services revenue. These figures indicate strong growth in the use of professional services staff to install, configure, and manage storage hardware and software.
In the long run, software revenue figures are augmented by the eventual maturation of storage management products, a process that is still, at least in part, dependant on consolidation in the storage software market itself.
BMC Software’s exit from the SRM market (and subsequent sale of Patrol Storage Manager to EMC), StorageNetworks’ flameout, and EMC’s purchase of Legato, Documentum, and Astrum increase the chances that products on the market eventually meet customer requirements.
These developments also indicate that additional consolidation is still on the horizon. As is typical of the churn around the chasm, product adoption rates and product innovation rates are “lumpy,” showing spikes and valleys until the cycle rounds off with the early and late majority adopters.
A primary factor of the recovery of the enterprise storage software market is the demand for SRM software. SRM software is a fundamental component of any storage management initiative and eventually the one tool most capable of maximizing storage investments.
Storage Resource Management
Storage consumers have undoubtedly waited a long time for SRM tools to make their lives easier. Until SRM products mature completely, which depends in part on the ongoing development of standards for storage hardware products, storage managers and storage decision-makers remain dependant on a combination of home-grown tools and reports for capacity planning and provisioning. The tools available on the market today play only a small role in the day-to-day tasks required for the management of enterprise storage. Many customers who have already purchased and implemented SRM solutions are still reliant on traditional spreadsheet solutions for making critical decisions regarding the purchase, allocation, and de-allocation of storage. For SRM software vendors, the major competition is not other vendors, but their customer’s own spreadsheets and processes.
SRM tools have high price tags, are notoriously difficult to implement, and in many cases, they have not delivered the critical reporting functionality needed to replace home-grown solutions at the heart of IT storage departments. Integrating SRM solutions with these tools presents a significant challenge to customers who cannot deploy labor-intensive software agents on a wider scale until the replacement solutions match basic functional reporting requirements. After these requirements are met, customers still face scalability issues with products designed to gather enterprise storage data from each of possibly thousands of hosts. Consulting and professional services in the SRM space are currently poised to see increased revenue because many SRM installations either fail or they require significant customization to show value.
In the not-so-distant future, the enterprise storage software market will bear little resemblance to the entity we are familiar with today. Marked by intense competition, rapid consolidation, and significant advances in technology, the enterprise storage software market will become an oligopoly, with a handful of major players commanding the majority of the revenue. Over time, smaller companies, such as Boston-based Onaro and Silicon Valley-based MonoSphere, that focus on what are now seen as niche markets (for instance, predictive change management and virtualization) will gain momentum and market share by supplying unique features and functionality that lessen the burden of storage management.
Currently the SRM market is, with a few exceptions, marked by a handful of immature products that show significant promise.
Reliance on storage management tool suites, when they finally mature, will simplify every aspect of the storage yield, purchase, and deployment cycles. Capacity planning will finally move away from spreadsheets and utilization, at the disk level and application level (the allocation and utilization efficiencies) will be tracked in real-time through a GUI. Performance, service level management, workflow, and information lifecycle management functionality will also be built into future storage management software packages. Until that day, however, many customers are in a wait-and-see position with regard to installing the current releases of SRM solutions. Consequently, they must rely on de facto standards, homogeneous environments, and home-grown solutions to make their storage management and operational lives simpler.
Most capacity planning and disk procurement processes are based on a combination of historical trending, usage models, and guesswork. These inefficiencies, coupled with the immaturity of storage management software, irrational exuberance, and Y2K-related spending, are all responsible for much of the overcapacity and build out of disk capacity in the years previous to the most recent recession.
It is important to put the current state of affairs into perspective, however. If you concede that Fibre Channel solutions have recently crossed the chasm, and that IP-based storage networks have yet to do so, it is safe to assume that the storage world we live in today will be significantly different in a brief period of time.
Historically, storage management has been a host-based process. Truly scalable, truly sustainable storage management processes, those required for the creation of a storage vision, however, can be achieved only with a centralized management strategy. One of the companies currently working to change the storage management paradigm is CreekPath.
Storage Operations Management
Scott Hansbury, Chief Marketing Officer for CreekPath, agrees that a sustainable storage management process is achieved through a centralized management strategy. CreekPath, an independent software vendor founded in 1999, has been delivering storage and SAN management software solutions since January, 2001. CreekPath currently offers an array of products designed to facilitate optimal storage operations management.
Hansbury believes that a holistic view of the IT organization and its infrastructure will prevail as the market for storage software management products matures. Products that can map critical processes and application functions to the infrastructure provide required services at every level of the storage value chain, anticipate customer demand, and will be successful in the long term.
Hansbury likens the current market for storage management software products to the market for office productivity software in the mid-to-late 1980s. Microsoft’s capability to consolidate a disparate set of point products into a modular suite of solutions essentially disrupted an entire market.
Hansbury is also quick to point out that the original market predictions for office productivity software grossly underestimated the potential.
SRM is only one functional piece of storage infrastructure management, the first to see significant investment from storage software vendors. The remaining issues—policy, workflow, and automation—are currently being addressed. In addition, products that can map those functions from the application to the spindle, and are easy to install and use, will no doubt be the most successful.
Tools that provide the passive knowledge of storage resource data will eventually give way to software products that actively manage those resources. “Seeing the storage is not enough,” Hansbury says. “Now it boils down to proactive management of performance and data (or information) archiving.”
Point solutions on the market today address the passive and proactive pieces separately; in the near future, these products will be integrated to provide an enterprise view.
Mike Koclanes, CreekPath’s Chief Technology Officer, views the evolution of storage management software as ever-expanding levels of abstraction layered on top of a guaranteed level of service, much like networking QoS (quality of service).
Koclanes believes that as IP-based storage solutions widen the choices for product deployment, the goal should be to limit the unpredictability of that service (with management techniques such as QoS). IO performance should be guaranteed to meet service levels as required, regardless of the dynamic nature of the choices available to the customer or client, and regardless of how the service levels are scoped (whether they are time-sliced, application-centric, or market-centric).
Koclanes’s view eventually leads us to the need for an operations management system capable of matching available resources to required services. From a historical standpoint, the adoption rate of new, disruptive technologies is often underestimated. Koclanes believes that the adoption of centralized network storage management and the integration of Fibre Channel and IP storage network is no different. He believes that a single, integrated network that provides data services to both internal operations and external customers, and one that is capable of managing the security and billing for those services, is not too far off.
Koclanes concludes, “Software has to present itself as an application-centric networked service” to facilitate the same ease of use and interoperability in storage networking that has been achieved in computer networking.
The fact that interoperability between storage networking hardware components themselves and the software intended to manage that hardware has been insufficiently championed until now is indicative of the fact that component manufacturers have had only one goal in mind: decreasing time to market. Interoperability has been an afterthought at best with most hardware vendors, leading to dissatisfaction in the customer base. For storage networks to approach the same level of interoperability users are accustomed to seeing with LAN networking for hosts, significant energy aimed at standardization of interfaces is necessary.
Note – Fortunately for storage networking consumers, a concerted effort is underway to do just that: standardize interfaces. The Storage Networking Industry Association (SNIA) was formed in December, 1997 as a non-profit organization dedicated to the advancement of storage networking standards through vendor and end-user collaboration.
In April, 2003, SNIA formally introduced Bluefin, also known as the Storage Management Initiative Specification (SMI-S), a specification jointly developed by industry leaders in an effort to ease the pain involved with managing heterogeneous storage environments. Storage networking manufacturers, such as Qlogic, StorageTek, IBM, EMC, HP, and others, worked together for almost a year prior to the announcement for designing and finalizing the specification, which is intended to alleviate many of the interoperability and management problems brought on by a legacy of proprietary storage networking interfaces. Having the Bluefin specification in place gives vendors an open standard to code against, which ensures that end users have products that play nicely together—a luxury that has up until now been completely out of reach for storage networking consumers.
SMI-S is based on Common Information Model (CIM), another networking industry joint venture designed to take some of the headaches out of managing devices on a network. CIM is an object-oriented schema and specification that simplifies and standardizes the interfaces necessary for gathering data from objects on a network and presenting that data in a useful format.
As the first organized effort geared toward interoperability and management, SMI-S offers potentially huge gains, especially for SRM and storage management software vendors and users of those products. One of the primary stumbling blocks for getting robust storage management software to market has been the lack of standard interfaces and schemas. Historically, each HBA, device driver, FC switch, and external storage unit has been designed in a vacuum with little or no effort made toward interoperability. The majority of storage networking and storage device manufacturers has accepted SMI-S as the standard interface specification. Although it will take some time to see products that use SMI-S on the market, after the specification is ratified, consumers will start to feel some relief. Consumers will then find it easier to make the transition from an application-centric to a storage-centric entity.
An application-centric user base is more liable to see storage as cheap and disposable, and although purchase prices have fallen, the management costs for storage have yet to see significant decreases, and the TCO for storage requires constant, active management to keep in line. The knowledge gap between infrastructure and application teams with respect to the costs of storage and storage management has never been greater. As the number of terabytes managed increases, only the storage management team is aware of storage as a depreciating capital asset, and not as a cheap and disposable tool.
It is crucial then that firms with significant amounts of storage installed (500 TB to 1 PB or more) become storage-centric entities in which storage strategies play an important role in the execution of management objectives, such as consolidation and business continuance. Application consolidation, storage consolidation, and business continuance strategies can be driven to success by storage-centric leadership, resulting in decreased costs and increased availability.
Cost-Saving Strategies for Storage-Centric Firms
Becoming a storage-centric entity requires executive-level sponsorship and active participation of individual contributors who foster awareness at every level of the organization of the value of storage as a depreciating capital asset with a corresponding yield and impact to the company’s bottom line.
Reiterating the premise from earlier chapters, it is possible to drive significant change in an organization, from the bottom up as it were, by focusing on storage as an asset. Much like an EVA organization, a storage-centric organization views IT decisions with a focus on storage management strategies to ensure that value is created or at minimum not destroyed. Storage consolidation, server consolidation, virtualization, and Information Lifecycle Management—key initiatives in every storage-centric organization—can all be driven from the bottom up, given a viable, cohesive storage vision and active, executive-level support.
Storage Consolidation
Chapter 3, “Building a Value Case Using Financial Metrics,” analyzed the financial benefits of a consolidation project, whereby Goodrich was able to eliminate $5,760,000 in maintenance fees by consolidating 80 external storage frames. The savings from maintenance fees were augmented by space savings in the datacenter, which deferred a $4,000,000 datacenter expansion project. In addition to resulting in fewer points of management, the consolidation effort provided a centralized agenda for lowering costs.
Consolidation is, of course, not without its caveats. The process of moving terabytes of critical data storage from multiple external arrays to just a handful does require significant foresight and planning to ensure that all high-availability requirements are met. A single, extended outage for several hosts attached to a 10- or 20-terabyte frame can affect large portions of a Fortune 500 company and virtually wipe out a small-to-medium sized business. Therefore, when planning a large-scale consolidation, it is critical that considerations be made for high availability and recoverability, and that the affected clients are aware of (and agree to accept) the possible risks.
Note – As consolidation begins to gain traction, environments are disturbed and many applications that had been forgotten are discovered. These applications might have less stringent requirements since their original deployment or they might not even be in use, at which point, the server and application can be fully decommissioned.
The consolidation bandwagon will likely become something that disparate business functions want to get behind. Other teams will want to take part in the success of storage consolidation and will either support the initiative or start separate consolidation initiatives. Application teams might respond positively to a bounty system for recovery, whereby rewards are given for the most terabytes recovered or decommissioned. Business units might offer similar rewards for applications decommissioned.
A storage-centric business strategy built on consolidation is capable of driving significant change in an organization.
Consolidation, a process marked by repeated planned outages to install HBAs and to copy databases, also requires considerable effort on the part of storage managers to ensure that disks are properly allocated and utilized. The process of dynamically migrating data to increase utilization and bolster operational efficiency is one that storage software manufacturers seek to automate.
Server Consolidation
Increased disk capacity translates into greater storage capacity in a single footprint. By the same token, increased processing power and decreased processing costs, along with advances in server and processor partitioning and management software, lessen the need for multiple servers and applications in order to do the same amount of work. Advances in operating systems software and processor architecture have made it not only feasible, but also cost-effective to implement server and application consolidation projects on a wider scale.
During the pre-Y2K era, processor sharing and server partitioning features were not widely available. Today, server partitioning is a widely accepted method of providing increased power and reliability to application environments. Logical partitioning at the operating system level allows for the dynamic allocation of central processing units (CPUs), offering the flexibility to meet changing project requirements. Hard partitioning at the server hardware level offers the capability to completely isolate from each other resources assigned to different applications within the same chassis. Although hard partitioning does have its own drawbacks in terms of flexibility, the capability to dynamically reallocate resources within the same hard partition is retained.
Equally pertinent to this discussion is the increased economies of scale gained by clustering multiple, smaller (or blade) servers as hosts to create server farms capable of providing highly available, efficient, and cost-effective processing power. The ability to scale horizontally, due to increased processor power, has all but replaced the drive to scale vertically. High prices for software and operating system maintenance drive many companies to adopt Linux and other open-source tools, whereas low-priced options for server infrastructure increase the use of blade servers for server farms (as mentioned in Chapter 1, “Industry Landscape: Storage Costs and Consumption”).
In either case, the potential to provide increased availability to more applications at a lower price point is there. Regardless of the decision to implement fewer high-end server platforms or more low-cost servers, the decision to increase the application-server ratio is one that must be seriously considered to lower TCO over the long term.
The issue of risk versus reward raises its head in any discussion of consolidation, and server or application consolidation is no exception. The basic argument for server consolidation is easy to understand: Due to increased processor power, better fault management and load-sharing software, and lower costs, it is now possible to relieve the burden of expensive hardware maintenance costs by collocating applications on the same hardware. As long as the performance, availability, and uptime requirements can be met, then server consolidation, either to Linux farms or high-end servers, should be transparent to the application owners, with the exception of the downtime required to move the application.
Application consolidation is a riskier proposition and one that is harder to sell based on perceived diminished rewards. There are tangible benefits from using fewer software licenses required to perform the same tasks; however, despite the benefit of decreased points of management, the process of migrating and collapsing applications is much harder for businesses and IT departments to agree to than storage or server consolidation. Consolidation at the software level addresses the intricate methods that business functions use to interact with IT and with each other. Consolidation at the hardware level makes sense to many individuals because of the nature of computing advancement (Moore’s Law) and the concept of an asset’s useful life. Application infrastructure, however, reflects a company’s proprietary knowledge whose wealth and value go far beyond that shown on the balance sheet. The primary issue of application consolidation is a question of business process engineering and requires a much broader scope of involvement across the enterprise.
This is not to say that application consolidation should be dismissed as a potential opportunity for lowering costs, but only that it should not be entered into lightly. On the one hand, the gains from a large-scale application consolidation effort can be significant, but it takes time, energy, and focus to turn them into a reality. Server and storage consolidation, on the other hand, can be sold as quick wins, which might spark some interest and initiative in consolidating applications. Consolidation at the disk, server, and application level ensures that the firm is capable of increasing the utilization of its assets.
Virtualization extends the concept of increasing utilization to the firm’s entire set of computing assets. The ultimate goal of managing any resource is to achieve its maximum utilization rate. This applies not only to enterprise disk assets, but also to server and application entities. Unless there is a compelling reason to maintain a buffer of unutilized disks (or CPUs or switch ports), underutilization signifies waste. Tools designed to virtualize resources greatly simplify the processes behind management and consolidation, and therefore increase the utilization of those assets.
Virtualization
Although virtualization software packages are in the early adopter phase, the promise of virtualization of the CPU and the disk coupled with the capability to eventually shield system owners from storage and system administration pain (while increasing utilization) appeals to decision makers.
Host-based virtualization products have been in use in production datacenters for over a decade. Applications, such as VERITAS Volume Manager and Hewlett-Packard’s Logical Volume Manager, provide transparency between the host and the storage unit to simplify the management of thousands of logical devices. These types of disk virtualization products are widely accepted solutions.
Network-based virtualization provides an additional layer of abstraction between heterogeneous storage and the hosts on a storage network, which eases the management of different storage platforms across the network. Virtualization at the network level increases application uptime by allowing resources to be dynamically allocated in the event of a planned or unplanned outage. Network-based virtualization also increases allocation efficiency rates by allowing devices anywhere on the storage network to be reassigned without impact to the application or the end user.
Companies, such as IBM and VERITAS, the first to bring to market intelligent virtualization solutions embedded on a switch, have set the pace of development with their releases of SAN Volume Controller and Storage Foundation for Networks respectively, and they will quickly erect barriers to entry to prevent further competition. Other types of virtualization products will quickly come to market to meet pent-up demand for virtualization functionality.
Early adopters of virtualization products find performance, reliability, and interoperability issues to be a factor, but for large environments in which the potential benefits of virtualization far outweigh the risks and costs associated with implementing immature products, virtualization is already making inroads.
As networked-based disk virtualization products mature, labor costs for managing storage across the enterprise decrease dramatically. Likewise, the virtualization of the CPU decreases the TCO for servers and applications. In addition to IBM and VERITAS, whose virtualization solutions are both available as separate service modules on the Cisco MDS platform switches, MonoSphere and Egenera are two more companies whose products are designed to virtualize and optimize computing assets.
MonoSphere
MonoSphere was founded two and a half years ago on the premise that corporate leaders facing dramatic growth in data storage would soon recognize the strategic importance of managing storage at the enterprise level and the need to address the rising TCO associated with managing heterogeneous storage with fewer staff.
Note – In February, 2004, I visited the corporate headquarters of MonoSphere, makers of cross-platform automated storage management (ASM) software solutions, to gain some insight on the storage software market, and to understand the effect MonoSphere’s leadership believes virtualization and consolidation will have on the overall market for storage hardware. When I was at MonoSphere, I spoke with Ray Villeneuve, President and CEO, and Shridar Subramanian, Director of Business Strategy and Alliances.
Similar to CreekPath, Onaro, and other storage-related independent software vendors (ISVs), MonoSphere believes that future growth in the enterprise storage market is heavily tied to advances in software designed to manage and leverage networked storage. MonoSphere differentiates itself, however, from other storage software providers with the scale and scope of its flagship product, MonoSphere Storage Manager_, which is designed specifically to automate tasks and policies that increase utilization of and lower the TCO for enterprise storage assets.
In April, 2003, the company began shipping MonoSphere Storage Manager_ for the Windows platform and, later in 2003, they shipped versions of the product for Solaris and Linux hosts.
MonoSphere is headquartered in Silicon Valley and has a research and development center in Tel Aviv, Israel.
The MonoSphere Storage Manager_ product is designed to provide a highly detailed view of the utilization of an enterprise’s storage assets and to provide a methodology and toolset for migrating data to unused or unallocated storage, thereby increasing allocation efficiency and protecting the value of the storage asset.
MonoSphere Storage Manager_ virtualizes storage devices and allows the user to create virtual pools that can be allocated and de-allocated with little or no impact to the host environment. This abstraction of the storage device, as seen by the host, facilitates the use of a tiered storage strategy to lower the overall total cost of storage ownership. The simplification of implementing a tiered approach to storage helps customers avoid some of the interoperability issues associated with heterogeneous storage, thereby increasing purchasing power for storage decision makers.
From a single, out-of-band console on the storage network, storage managers can view reports showing true capacity utilization based on a fine-grained view of which storage blocks actually contain user data. This is in contrast with SRM products that cannot distinguish between storage that is allocated and that which is used. To act upon insights gleaned from these reports, storage managers either use prepackaged (canned) policies or they create their own policy-based rule sets to manage data layout across pools of free storage.
At the application server level, a software driver continuously monitors usage patterns, latency, and throughput, providing historical trending and assisting the environment’s owner with ongoing policy refinement.
Intermediate volumes, known as MonoSphere Adaptive Volumes, are used to stage and destage data as it is moved between pools of storage by a separate, in-band server dedicated to the MonoSphere Storage Manager_ application. This server handles the actual data migrations between the unused devices, pools, and tiers as dictated by policies specific to the environment, and it minimizes the impact of the migrations on the hosts on the storage network. A common application for this unique capability is to create “spillover” storage that is used as local storage capacity becomes filled. In this way, local storage can be made to behave as if it were infinitely large, without impacting applications, so applications never outgrow their storage.
By simplifying the process of data migrations between tiers and by providing an accurate and up-to-date view of an environment’s allocation efficiency, MonoSphere Storage Manager_ is positioned to radically change the way storage is managed in today’s enterprise.
Egenera
Egenera, based in Marlboro, Massachusetts, intends to capitalize on the confluence of events and market drivers that it believes led to the next inflection point in the server market. Egenera builds the Egenera BladeFrame system, pools of massively scalable processing resources designed to meet the market demand for highly redundant, highly available environments. The nature of the blade computer, coupled with the virtualization of the IO components in the subsystem, means that the BladeFrame can lower the TCO by increasing the utilization of the processor much in the same manner as SANs increase the utilization of disk storage.
Note – In February, 2004, I spoke at length with Susan Davis, Egenera’s Vice President of Product Marketing and Management, about server consolidation, grid computing, and the latest inflection point in the market for high-end servers.
Egenera was founded in 2000 by Vern Brownell, former CTO of Goldman Sachs, as an answer to the primarily physical problems he saw facing large enterprise datacenters. The traditional view of the server as an isolated resource, similar in concept to direct-attached storage (DAS), along with the need to provide highly-available computing power, has led to rampant growth of server islands that have become a cost and management nightmare. The proliferation of servers and storage in the datacenter, the increased points of management, and the related costs inspired Brownell to design a system capable of meeting performance and reliability constraints while reducing the number of managed resources in the enterprise. The end result has been a fundamental change in the concept of the server itself.
Server consolidation (or grid computing in a larger sense) is at a basic level about raising the utilization of the processor by providing sharable computing resources as a utility. Just as storage networking and storage consolidation is about increasing the utilization of the storage resources, processing area networks, such as those built by Egenera, increase the utilization of server resources by allowing groups of CPUs to be allocated to and de-allocated from an application’s resource pool. The unutilized processors can therefore be shared between environments lacking resources, thereby offering investment protection and increased return on investment (ROI).
The virtualization of IO components in the BladeFrame creates a holistic view of the resources managed with intelligent software to make allocation and assignment of resources a painless process. Whereas in the past, the purchase, installation, and assignment of server resources in the datacenter involved the management of a number of different processes and physical elements, the use of blade farms to virtualize all IO components at the server level adds flexibility while reducing operational complexity.
This level of virtualization goes beyond the common concept of layers of abstraction provided by complex software stacked on top of numerous hardware entities. Egenera seeks to limit the number of IO entities underneath the virtual view provided by its management software.
Susan Davis believes that the inflection point in the server market is the result of the recent economic downturn, increased processor power, the growing acceptance of Linux in the datacenter, and, of course, customers’ requirements to reduce acquisition and management costs while providing world-class technology solutions for their clients.
Egenera’s successive years of triple-digit growth indicate that even though the grid computing concept is still in the early adopter phase, the market for solutions such as those provided by Egenera is rapidly growing.
Information Lifecycle Management
Instituting an information lifecycle management (ILM) framework, a process designed to guide the migration of data to different tiers or classes of storage as its usefulness declines over time, is a fundamental strategy designed to lower costs. As part of an ILM infrastructure, different tiers of storage with varying levels of functionality and availability are provided at different cost structures. As the value of the data declines over time, it is migrated to cheaper and cheaper disks until it is archived or deleted.
Note – Migration to storage networks and consolidation should be considered a fundamental step before initiating plans for instituting an ILM infrastructure.
As a holistic approach to IT infrastructure, ILM addresses the data itself, the kernel of intellectual property at the firm’s core, and it weighs the value of the data against the costs of the infrastructure required to support it. In many ways, ILM extends the core-context debate into the tangible realm of managed terabytes: Core data is that which should reside at the uppermost tier, whereas contextual data can be transformed into a more manageable format or deleted entirely. In either case, it is necessary to determine the break-even point at which it becomes too costly and unwieldy to provide tier-one support for tier-three data. An example of this analysis is provided in the next section.
Note – Also keep in mind that the labor involved in implementing both SRM and ILM in your framework increases your TCO for the solution. Including the costs of the SRM and ILM management solution in the TCO analysis for your environment is required for an accurate portrait of cost trends.
Managing Costs in an ILM Environment
Managing storage costs for the life of the storage asset requires up-to-date and accurate cost data at each tier and across the enterprise. Few organizations have sufficient time and energy to devote to tracking and fine-tuning TCO data. Where possible, TCO initiatives can be driven by the storage team, but they are always reliant—at least to some degree—on asset management and purchasing data to provide granularity and accuracy.
To correctly position the data in the requisite tier, it is necessary to analyze the break-even point for managing that data according to its priority, business relevance, and revenue impact. For the purposes of this discussion, we cover only three tiers: a high-end tier (Gold), a mid-range tier (Silver), and a low-end tier (Bronze). Additional tiers can be created, although management costs increase as the number of tiers increases. In the following examples, the per megabyte purchase price is (inclusive of maintenance) $0.10 for Tier 1, $0.05 for Tier 2, and $0.03 for Tier 3. In addition, the following assumptions are made for each tier:
The discount rate is ten percent.
Future labor costs are discounted using net present value (NPV).
One full-time equivalent (FTE) can effectively manage 1.5 TB.
Utilization is ignored.
Growth is stagnant.
The depreciation schedule is three years.
Cash basis is for all three years.
This section shows an example at each tier.
Note – It is critical to note that at this point in time, heterogeneity is key to gaining economies of scale, and management costs through a tiered infrastructure without the benefits of interoperability initiatives such as Bluefin, actually increase with the addition of different platforms into the support matrix. As hardware and software products mature and long-awaited interoperability subsequently materializes, then and only then will a tiered infrastructure be able to aggressively lower management costs.
Currently, hardware solutions for each vendor at each tier (low-end, mid-range, high-end) require different management interfaces and different support processes, hampering the ability to scale support for different platforms across the enterprise. Although products from the major disk vendors have Java-based or web-based GUI interfaces, there is no way at this time to manage, provision, allocate or de-allocate storage across a vast array of different storage solutions from a single console without a third-party product.
The capability for a tiered storage infrastructure to increase supportability for hundreds of terabytes is wholly dependant on hardware interoperability and virtualization software. For the purposes of the tiered TCO discussion, the assumption should be that virtualization software as a mature product has been implemented and that the tiered solutions are transparent to the storage managers and the end users—a scenario that should materialize in production datacenters by 2005–2006.
Classifying Tiers Based on TCO
It is important to understand that migration from DAS to SAN or network-attached storage solutions (NAS) (and from a non-tiered to a tiered storage environment) invariably requires significant time and resource commitments. These migrations do not happen overnight. During considerable lengths of time, there might be multiple environments in place for the same application at the switch, disk, and host level. These duplicate environments increase the management, and hardware costs contribute to an initially higher TCO. Consolidation efforts also involve the creation of duplicate environments, which raise the hardware cost components associated with the consolidated environments. Over time, the costs decrease; in the short run, costs spike. The following examples should help identify the break-even point of TCO and tier application.
Tier 1 (Gold)
This example assumes the following:
The environment uses a total of 1500 GB (including local and remotely replicated copies).
The $0.10 purchase price includes all licenses and maintenance.
The value of one FTE is $100,000.00.
Installation costs are $0.01 per megabyte.
Backups are taken weekly and twice daily.
Note – Note that for the cash basis analysis, the FTE costs are the NPV of one FTE over three years using a ten percent discount rate.
Table 5-2 shows the TCO for a typical Tier 1 storage environment. Note that this number is the TCO for the storage only and does not include the costs for server hardware or application licenses. Cost components are shown as both cash basis and depreciation basis.
Table 5-2 Tier 1 (Gold) TCO
Click to view table dataNote – SRM and virtualization software costs of $1,000,000 spread over a 100-TB environment would be $0.01 per megabyte. For an environment as small as 500 GB, the contributions to TCO are negligible. Although noted here, these costs are not included in the TCO calculation for these environments. However, these costs would be included in the TCO for the enterprise.
This mission-critical environment is comprised of three copies (a primary copy and two replicated copies). The value of this data is such that the increased TCO that accompanies the multiple copies and the multiple backups is an accepted cost of the firm.
As the data matures, however, the value of the data can decline, and therefore might not merit the increased TCO. Aging sales reports and last year’s intranet data might have less stringent replication requirements and might not require multiple daily backups. At this time, the firm can decide to move the data to the next tier. The same size of environment classified as a Tier 2 and stored on a Silver-level storage infrastructure has a significantly lower TCO.
Tier Two (Silver)
The same assumptions hold for the Tier Two (Silver) environment, with two exceptions:
The environment uses a total of 1000 GB (one primary copy and one locally replicated copy).
The $0.05 purchase price includes all licenses and maintenance.
Backups are taken weekly and once daily.
The same 500-GB environment stored at Tier 2 has significantly lower capital costs, as shown in Table 5-3. Note that this number is the TCO for the storage only and does not include the costs for server hardware or application licenses. Cost components are shown as both cash basis and depreciation basis.
Table 5-3 Tier 2 Silver TCO
Click to view table dataThe value of this data is still likely to decrease, and over time might not merit multiple online copies and daily backups. The management team should then make a judgment call about whether or not to migrate to Tier Three, the Bronze tier.
Tier Three (Bronze)
With the Tier Three environment, the same assumptions still hold for the Tier Two environment, with three exceptions:
The environment uses a total of 500 GB (one primary copy only) of NAS devices (no FC switch components are required).
The $0.03 purchase price includes all licenses and maintenance.
Backups are taken only once a week.
As expected, the third tier (shown in Table 5-4) has an even lower TCO associated with it, primarily due to the lower acquisition costs of the hardware. Less frequent backups and no replication also lower the overall costs.
Table 5-4 Tier 3 Bronze TCO
Click to view table dataTable 5-5 summarizes the TCO comparisons.
Table 5-5 TCO Summary
Tier | TCO Cash Basis | Depreciation Basis: Year 1 | Depreciation Basis: Year 2 | Depreciation Basis: Year 3 |
Tier 1 | $0.42 | $0.17 | $0.13 | $0.12 |
Tier 2 | $0.33 | $0.15 | $0.10 | $0.10 |
Tier 3 | $0.22 | $0.08 | $0.07 | $0.07 |
For a 500-GB environment with three copies (one production, one locally mirrored, one remotely replicated) stored at Tier 1, the TCO is $0.42. As the number of online copies and the number of backups decreases, the TCO decreases accordingly.
If the per MB revenue associated with this environment is sufficiently greater than $0.42 per MB to cover all labor and fixed costs associated with additional server hardware and application licenses required to store data at the first tier, then it is in the best interest of the company to store this data at the first tier.
For example, assume that this external facing application facilitates an average of five transactions per hour every day for a year for a total of 43,800 transactions. If the average sale for each transaction is $100, then the annual revenue associated with this environment is $4,300,000. The corresponding revenue per megabyte is $8.55. The percent of storage TCO to revenue is then 4.90 percent. If this rate of costs to revenue meets the corporate goal, then the extra costs associated with the additional hardware for mirroring and replication is well within accepted limits. The following breaks down the costs and revenue associated with this environment:
Primary data storage (MB): 500,000
Average transactions per hour: 5
Average transaction: $100
Revenue: $4,380,000
Revenue/MB: $8.55
TCO/MB: $0.42
Percent of costs: 4.90%
Another way to look at revenue and associated costs is in terms of availability. If this same electronic commerce environment hosts 100 transactions per hour at an average of $1,000 per transaction, then an environment that provides only four nines availability—99.99 percent—or 8759.12 hours per year, cost the firm $87,600 in lost revenues. Table 5-6 shows the number of minutes downtime associated with the percentage of availability.
Table 5-6 Availability and Minutes of Downtime
Minutes Per Year | Availability | Minutes Downtime Per Year |
525600 | 0.99999 | 5.256 |
525600 | 0.9999 | 52.56 |
In this particular case, a Tier One environment, if properly architected, is virtually assured of providing 99.999 percent availability. The justification for the environment is then related to the company’s overall hurdle rate.
Table 5-7 highlights the associated costs, savings, and revenue impact as a percent of the fully burdened costs of the environment. If the company’s hurdle rate is 14 percent or less, then the Tier 1 solution is sufficient investment protection based on four nines availability. If the hurdle rate is above 14 percent or less, then the electronic commerce environment should be hosted on the Tier 1 solution.
Table 5-7 Revenue Impact as Percent of Tiered Costs
Tier | Fully Burdened Costs | Availability | Minutes Downtime | Revenue Impact | Revenue Savings | Percent |
Tier 1 | $637,000 | 0.99999 | 5.256 | $8,760.00 | $91,240.00 | 14.32% |
Tier 2 | $328,860 | 0.9999 | 52.56 | $87,600.00 | $12,400.00 | 3.77% |
It is critical to understand that the fundamental costs associated with each environment and each tier are the acquisition costs of the storage itself and the labor costs associated with supporting the storage and migrating the data between tiers. In a heterogeneous storage environment that lacks requisite virtualization and ILM-based software to make management through the tiers transparent to the storage manager, costs necessarily increase.
Note – Labor costs are a key factor in keeping TCO to a minimum. As mentioned earlier, currently the primary strategy for keeping labor costs down is homogenous storage. Force-fitting a tiered storage strategy into any environment with immature management software products raises management costs, and therefore, increases the TCO. As the number of terabytes managed by one FTE increases, the per gigabyte cost of management decreases, a classic example of increasing returns to scale.
At Cisco, as shown in Chapter 8, “Cisco Systems, Inc.,” management costs for a homogeneous environment scale linearly, whereas management costs for smaller heterogeneous environments increases over time. As enterprise storage software products mature, however, this distinction will disappear.
Conclusion
This chapter showed how the TCO for storage environments is directly related to management costs. As the purchase price for storage continues to decrease, and growth remains constant or accelerates, storage management processes will remain dependant on home-grown tools and immature software products. Until interoperability becomes a reality and storage management software matures, labor costs will increase, unless the environments are homogeneous. The Bluefin initiative, along with storage virtualization software will succeed in lowering the overhead associated with storage management.
Storage-centric organizations can execute a cohesive storage vision to lower costs and increase operational efficiencies. A storage vision comprised of consolidation and virtualization initiatives (both at the storage level and at the server level) can drive change throughout IT to increase utilization of IT assets and reduce waste.
As storage software products mature, a sustainable storage vision will include an ILM framework for managing information through its useful life, which, in turn, will continue to lower the TCO for storage.
As the case studies in Part II indicate, few companies have fully implemented a sustainable storage vision. Most early adopters have implemented only select strategies (migration and consolidation typically), where need is most acute and impact, in terms of both ROI and operational efficiencies, is quickly felt. Migration to storage networks is the most important strategy any company can implement. Without networked storage, storage-centric management strategies (consolidation, recovery, and virtualization) will not be successful.
The following case studies clearly show that implementing storage networks offers true business benefits, primarily increased utilization and increased availability, which have a measurable impact on the company’s bottom line.
References
1 IDC. Framinghaus, MA, 2004.
—Worldwide Disk Storage Systems 2003-2008 Market Forecast and Analysis: Conservatism Persists, but Opportunities Abound, IDC #31663, forthcoming.
—Worldwide Storage Software Forecast and Analysis, 2003-2007, IDC #29983, August 2003.
—Worldwide Storage Software Forecast and Analysis, 2002-2006, IDC #27477, June 2002.
—Worldwide and U.S. Storage Services 2004-2008 Forecast: The Opportunity Shifts, IDC #31042, March 2004.
—Worldwide and U.S. Storage Services Forecast and Analysis, 2003-2007, IDC #28992, March 2003.
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