A VOYAGE OF DISCOVERY Data Center Optimization Requires Comprehensive Knowledge of All Data Center Assets and Relationships

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1 White Paper A VOYAGE OF DISCOVERY Data Center Optimization Requires Comprehensive Knowledge of All Data Center Assets and Relationships Introduction IT departments have always been expected to deliver value for money. However, recent economic and competitive pressures intensified the demands to maximize data center efficiencies. For most organizations, those demands have not diminished despite the improving economy. There may be opportunities to realize data center cost savings by consolidating hardware, software and services. That s the good news. The bad news is that the complexity of most medium- to large-sized IT facilities makes the job of optimization much more difficult as it obscures knowledge of the underlying technology and business-process details. Put simply, you can t optimize what you don t know you have. Yet, that may not be the worst of it. An effort to transform your data center based on incomplete information, without paying attention to the interdependencies between hardware, software, data and users, may threaten business continuity. This white paper examines these challenges and offers suggestions for embarking on a voyage of discovery that will overcome the obstacles imposed by existing information gaps. What Have You Got? There is much talk these days of optimizing data centers through server consolidation and cloud computing. Achieving efficiencies sounds like an obvious objective, but talk is easy. Doing it is much more challenging. Optimizing your data center requires first knowing what is in there. That is normally not as straightforward as it sounds. In many, if not most data centers, technology was added piece-bypiece over the years. A new server was brought in to support a newly computerized business function. A merger or acquisition amalgamated heterogeneous hardware and software. More storage units were added to accommodate new and/or growing databases. Networking components were added to improve connectivity and/or bandwidth. And so on. 1

2 Documentation on technologies added over time is often scant. In fact, 15 to 18% of assets are not properly documented in the typical data center. The relevant purchase orders and invoices may still be on file, but going through them to create a comprehensive inventory is difficult at best and next to impossible at worst. You could do a physical inventory, but that is an error-prone exercise, particularly if the equipment is spread out over multiple locations. And a physical inventory will not take into account virtual assets, such as data, applications, and middleware. Furthermore, the picture used to be much simpler. At one time, a server was a server was a server. It was a piece of hardware that you could visually count. That s no longer necessarily the case. Thanks to virtualization, a single physical server may host several virtual servers, possibly running differing operating systems. What s more, a physical inventory won t tell you how IT assets are being employed. Sometimes, that information resides only in people s heads. If so, and if people with critical knowledge leave the Figure 1: Today's data centers are complex ecosystems. company, their knowledge might leave with them. That s not a problem as long as everything continues to work as it should and you don t want to make changes. Yet, by definition, data center transformation requires changes. How Do The Pieces Fit? Knowing what you have isn t enough. You also need to know how the pieces fit together and interrelate and what business processes they support. Which storage units, networking gear, and physical or virtual servers support which applications? Who owns and uses those applications. What business processes depend on each application? What dependencies exist between applications and technologies? These questions are fundamental. If you try to make changes to your IT infrastructure without first answering them you might find that after your optimization project, rather than your data center being optimized, some applications won t work at all because vital 2

3 components were not incorporated into the new environment and/or some necessary linkages were broken. What You Need to Know It s not the big issues that are likely to trip up a data center transformation project. It s the details. One piece of seemingly trivial hardware that isn t moved over to your optimized environment can shut down a vital system or, because of interdependencies, possibly multiple systems. The following is a checklist of some of the items that you must account for before beginning a data center optimization project: Business Processes and Application Discovery Business processes typically depend on a variety of hardware and software components. When cataloging IT assets in preparation for a project, it s important to identify these dependencies. Failure to do so may cause you to take actions that unacceptably degrade the performance of a business function or, worse, cause it to stop working entirely. In addition, applications interact. If a dependent application is unavailable or not functioning properly, the affected applications that depend on it may deliver suboptimal performance or not work at all. You must work to catalog these dependencies to ensure that they will continue to be supported adequately during project execution. And, of course, many people are utterly dependent on technologies to do their jobs. It is, therefore, also critical to catalog the relationships between people, processes and IT assets. Some critical dependencies are buried under layers of hardware, software and processes. As a result, they can be difficult to spot. Servers Servers are the workhorses of your data center. Accounting for them is an essential first step in any transformation project. The information you need to collect for every physical server includes the following: Makes and models Locations IP addresses MAC addresses Configuration settings 3

4 Virtual servers running on each physical server Applications running on each physical/virtual server Keep in mind that it s not only application and database servers that matter. Infrastructure servers that support under the hood functionality are also crucial. Storage The cost of storage has dropped dramatically over the years. That s been both a blessing and a curse. The benefit is obvious. The cost of storing each gigabyte of critical data is a small fraction of what it once was. The downside is that low costs have encouraged data proliferation. Organizations now store much more data, little of which is ever thrown away. Managing all of the data contained in large, ever-expanding disk farms can be a serious challenge. Critical information that must be documented includes the following: Where are all of the storage units? What makes and models are in service? What data is stored where? Is the data structured or unstructured? Which applications will be affected if some storage units are shut down for maintenance? Is all data backed up to the level warranted by its criticality? What, if any, archiving plans are in place? Networks Networks tie everything together. If they aren t there, users won t be able connect to servers, servers won t be able to connect to other servers and business operations will stop even if everything else is functional. Networks are typically neither simple nor homogenous. They may include a collection of local area networks, wide area networks and the bridges between the two. Network complexity may extend beneath the physical gear because many organizations employ virtual networks. Physical networking infrastructure may support multiple virtual networks that are isolated from each other, possibly for security reasons. For example, a segregated network may be necessary to comply with Payment Card Industry (PCI) standards or regulatory requirements such as 4

5 those imposed by the Health Insurance Portability and Accountability Act (HIPAA) or the Sarbanes-Oxley Act (SOX). Your networks might not stop at your organization s walls. You might also need to support third-party connectivity to credit card processors and supply chain partners, possibly through a private network or a virtual private network. Understanding your network infrastructure is a prerequisite for ensuring that a data center transformation project does not disrupt vital connectivity. You need a complete inventory of all of the makes, models, IP addresses, and installed hardware options for a variety of devices including the following: Routers Switches Firewalls Proxy servers Network appliances WAN topology You must also have a thorough understanding of the role that each piece of equipment serves in your network architecture. Services and Middleware Applications often don t operate in isolation. Instead, they may share information and interact in real-time. These interfaces are supported by middleware and other services. Failure to recognize and accommodate these components when reorganizing a data center may cause critical interfaces to fail. Services include both business services and core services. Business services, such as a service used to check in an airline passenger, may draw data from several databases and access the functionality of a variety of applications. Core services support business applications, technology infrastructure and/or middleware. Examples of core services include domain name services (DNS), directory services, authentication services, and FTP services. From an end-user perspective, these services operate transparently but only as long as they function properly. However if, for example, a domain name server fails, that failure might impact every application in your organization. Middleware services include services for queuing and transaction management, services to transport data and services that coordinate data movement and transaction flows. Middleware services don t directly provide business functionality, but they are essential elements that support business operations. 5

6 The discovery phase of a data center optimization process must catalog these services and other middleware components and document how they function and what applications depend on them. Contracts Many, if not most, IT assets have contracts associated with them. In the case of hardware, the contracts might define warrantee protection. There might also be maintenance and service contracts for both hardware and software. And Service Level Agreements might guarantee the performance, reliability and availability of an IT asset or service. All of these contracts must be tracked with the associated asset when transforming a data center. Some contracts might be affected by the transformation. For example, if hardware is moved to a new geographic location, possibly to centralize operations, that move might impact service agreements. In addition, virtualizing multiple servers onto one larger physical server might have implications for software contracts. The Necessary Voyage of Discovery When the need for IT asset discovery is discussed a question that often comes up is, doesn t the IT department already have a good handle on that? Doesn t the IT staff know what hardware and software they have, how it interacts and which users those assets support? After all, IT supports its systems every day. For the reasons stated above, the answer is often no or, rather, not in the detail that is required to successfully complete a data center optimization project without running into serious problems. Consequently, a discovery phase is a necessary first phase of a data center optimization project. In a complex environment, this phase can last a long time, possibly months, particularly if it is performed manually. Therein lies a problem. The business cannot stand still. While the discovery phase is ongoing, new equipment may be added and applications may change. Consequently, unless care is taken to keep it up to date, the discovery phase deliverable may be out of date before it is completed. Getting the Discovery Job Done Manual discovery of all IT assets is a time-consuming, cumbersome, error-prone job. A tool that automates many discovery processes is necessary to make the task both cost-effective and comprehensive. Many of the existing tools are generally good at discovering the technologies that exist in your data center, but they are usually less good, or possibly totally ineffectual, when it comes to matching those assets with the people and business processes they serve. To achieve this objective, the tool must interview individuals to gather the missing information. 6

7 Tools that provide scanning for network and security purposes are common, but they generally don t show you the big picture. The data collected by these tools must be correlated to provide a better view of the enterprise-wide infrastructure, including all of the interrelationships among the various components and with the people who use it. As stated above, because the data center isn t static during a discovery project, the tool should also be able to refresh the data on an ongoing basis. Discovery: The Four Step Process The details are obviously more complex than outlined below but, from a high-level perspective, a data center discovery process consists of four phases: Step One: Business Processes and Owners Discovery Catalog all business processes. In many cases there is a one-to-many relationship between applications and business processes. For example, an ERP may support order entry, shipping, purchasing and other business functions. However, there may also be many-to-one relationships between applications and processes. For example, booking a ticked for an airline passenger may require access to a seat-inventory application, an order-entry application and a credit card payment application. Two owners must be identified for each business process. The business owner is the person in the user community who is ultimately responsible for managing the process. The technical owner is the IT manager who is responsible for the systems that facilitate the process. Step Two: Technical Discovery The next step is to generate a complete inventory of all of your hardware servers, storage and networks and map them to the business processes that use them and, in turn, to their business and technical owners. Network scanning tools, as well as existing monitoring/management tools, can perform much of the grunt work in this phase, however there will also be considerable unstructured data contained in documents that must be considered. 7

8 Step Three: Missing Dependency and Other Information Discovery At this point, all of the hardware and software is cataloged and mapped to business processes and their owners. The next step is to identify all of the interdependencies between business processes, applications and hardware. Without this information, a data center transformation project may inadvertently break vital dependencies, causing systems to fail. Some discovery tools can use autonomic processing to identify missing data center dependencies and provide the necessary information about them, without the need for manual input. Step Four: Autonomic Social Discovery Figure 2: Just identifying hardware, software and their functions is not adequate. You must also recognize dependencies. It is almost inevitable that the first three phases of a data center discovery project will fail to identify the full social context of your systems. There will likely be gaps in the information about business and technical owners of hardware, data and applications. A good data center discovery tool provides autonomics that can determine likely owners and then pose questions that will have to be answered manually to fill in the gaps. Figure 3: Discovery Process Results 8

9 Human Resources Even when using a highly automated tool, the data center discovery process can consume considerable time and resources. Nonetheless, business operations cannot stop. IT staff must still provide the same level of support for business applications and their users. Because of budget restrictions, many IT shops are already headcount-constrained. It s exceptionally rare to find a surplus of human resources who can be assigned to a data center discovery process for several weeks or even a few months. Beyond the lack of excess IT staff time, the necessary skills are often in short supply or non-existent within the organization. Effective discovery techniques, including experience in using the relevant tools, are unique skills. Training or hiring the required skills for what might be only a few one-off projects, may not be cost-effective. There is a way to overcome this challenge. Contracting data center discovery specialists can cost-effectively bring the necessary expertise on board when it is needed. However, as previously mentioned, data centers are not static. If left unchanged, the results of the data center discovery process will likely be out of date within a few weeks after the consultants finish their work and leave. Consequently, a comprehensive, autonomic discovery tool that keeps the inventory database and relationship map up to date should be one of the deliverables of any data center discovery engagement. About Virima Technologies An innovator in accelerated Data Center Transformations and IT Operations, Virima Technologies provides leading-edge solutions that align an organization's IT operations with its business strategy. Its technology-enabled data center consolidation and optimization services leverage the world s first autonomic and intelligent IT Operations Automation software suite that enables organizations to peer deep into the enterprise IT ecosystem to dramatically improve IT-Business alignment, performance and governance. Virima's Discovery Services feature its patent-pending EcosystemManager, which jumpstarts any complex Data Center Transformation (DCT) project by capturing and correlating all necessary asset, configuration and dependency information as well as the often elusive human "tribal knowledge" and vast amounts of scattered documentation. EcosystemManager intelligently correlates data from multiple sources and then builds an inventory database that serves as the core resource for a DCT project. It also keeps the IT asset inventory and dependency mapping database fresh throughout the DCT project and beyond, updating it as assets are added to or removed from the IT environment. EcosystemManager will continue to generate value after the project is finished as it will provide IT operations managers and staff with greater insight into the overall IT ecosystem. By providing unprecedented visibility through detailed monitoring and advanced analytics, Virima solutions automatically turn IT information into actionable intelligence, resulting in productivity and operational efficiency gains that can return significant savings. Headquartered in Atlanta, Georgia, Virima services organizations in North America. 9

10 More information is available at Virima Headquarters Virima Technologies, Inc Mt. Vernon Road Suite 200 Atlanta, GA Phone: Website: 10