Tratamientos e intervenciones en esquizofrenia

The amount of time an IT service is usable is referred to as its availability; availability represents the percentage of time that the hardware and software in use offers the service that it was deployed to provide (Bauer & Franklin, 2006). IT departments ensure the timely and reliable access to and use of information when the data and the information system on which it resides are available (Government Accounting Office (GAO), 2009). Availability is measured so that the business that uses the computer hardware systems, software applications, and network components on which it depends can make decisions about the performance of those systems. Measuring availability allows the business to determine the

ability of the IT department to provide the tools needed to operate the business. Availability is the time that computer systems can be used by a business to enable it to satisfy its objectives and is expressed as the percentage of the agreed service hours for which the component or service is available (Cartlidge et al., 2007). Because there are a finite and measurable number of minutes in a year, the annual availability of a computer environment can be easily calculated. Simply expressed, availability is the total number of minutes in a year minus the minutes that the computer environment was not available, presented as a percentage. This equation is shown in Table 2-14. The only times when a computer system can be not available is when there is a planned or unplanned outage.

Table 2-14. Calculating Availability Calculating Availability

Availability Variable Values

A = (M–P–U) M

A = Availability

M = Minutes per Year (525,600)

U = Unplanned Outage Minutes per Year P = Planned Outage Minutes per Year

Availability has become increasingly important and can now be reviewed as a three-phase evolution during which the attention of both the IT departments and the business changed from IT component availability to business process availability. In phase one, technical teams designed for individual hardware components to ensure they were able to stay available. In phase two, availability focused on the needs of the IT end-users and their perspective of availability, including software applications and data. The third phase, however, focuses on the needs of the business that pays for the IT environment and the processes it uses to run its business (Bailey, Frank-Schultz, Lindeque, & Temple, 2008).

The Service Availability Forum (SAF) has championed the standardisation of availability and has been driven, primarily, by the telecommunications industry (Lumpp et al., 2008). A consortium of telecommunications and computer companies across the world, the SAF was established to encourage the use of commercial-off-the-shelf (COTS) technology solutions to create high availability IT environments. Though SAF has focused on two major technology areas to achieve high availability (hardware and the integration of software), it is comprised of a variety of computer application, hardware, and component organisations, including Nokia Siemens, Sun Microsystems, Oracle, Hewlett-Packard and Alcatel-Lucent, among others. SAF defines high availability at 99.999 percent (Industry Leaders, 2009). Knowing that use of the Internet by business is growing and there is a desire to move the costs associated with servicing customers from personal contact to having customers use on-line

self-service options, the high availability of a computer enterprise is critical. The typical requirement for a telecommunication network, for instance is 99.999 percent availability (Guida, Longo, & Postiglione, 2008). Referred to as the gold standard for availability, ―five-nines‖ provides 99.999 percent availability. That gold standard allows a total of 5.26 minutes of outage time per year (Bauer & Franklin, 2006; Kimber et al., 2006). Those 5.26 minutes include both planned and unplanned outages.

This desired level of computer system and component availability (Ganesh, Illsley, Rodger & Thompson, 2008) is costly and difficult to achieve, yet many organisations appear as if they are making inroads to attain it. An availability attainment of 99.999 percent is a requirement for some businesses (Boam, Gilbert, Mathew, Rasovsky, & Sistla, 2003;

Hochmuth, 2004; Prabhakar, Rastogi, & Thottan, 2005) and there has been an integration of computer-centric features for resiliency, redundancy, serviceability and manageability (Boam et al., 2003) to minimise the number of and duration of planned outages. More importantly, these contribute to meeting the actual needs of the business (Ganesh et al., 2008). There is no challenge that high availability is valuable to many businesses. There is also no challenge that achieving high availability is costly. It is also noted that some businesses need IT systems available only when the IT systems are actually used. Some applications do not need 99.999 percent availability (Mankowski, 2007; Radhakrishnan, Mark & Powell, 2008). Most organisations use a combination of models, management tools, and analysis to determine the level of availability needed by a particular application or computer system.

Once it is classified as either mission- or business-critical, its availability is, generally, set at 99.9 percent or higher, allowing, at most, just fewer than 526 minutes (approximately nine hours) of planned and unplanned downtime per year (Radhakrishnan et al., 2008). High availability is not a new concept in the IT industry nor is the understanding that it cannot be attained due to system failures, human error or both. Understanding it from the perspective of the end user is not well researched; however, decisions are made by the businesses that pay for IT departments without all necessary information to make informed decisions (Zeng, 2007). Table 2-15 lists only the costs of annual lost revenue to some industry sectors, even when commitments and investments have been made in order to achieve some degree of high availability. The lost values are increased if the availability value listed is not obtained and greater amounts of annual downtime are experienced.

Table 2-15. Availability, Downtime and Lost Revenue

Availability, Annual Allowed Downtime and Annual Lost Revenue, by Industry, when Allowed Downtime is Achieved, in US dollars (Zeng, 2007, p. 24)

Lost Annual Revenue Shown in $US Dollars by Industry

Availability

Annual Downtime (hours-minutes) Energy Manufacturing Banking Insurance Retail

99.000 % 87-36 $247.0 M $141.0 M $131.0 M $105.0 M $97.0 M 99.500 % 43-48 $123.0 M $70.0 M $65.0 M $53.0 M $48.0 M 99.900 % 08-46 $ 20.0 M $14.0 M $13.0 M $11.0 M $9.8 M 99.950 % 04-23 $ 13.0 M $7.0 M $6.9 M $5.5 M $5.1 M 99.990 % 00-53 $ 2.5 M $1.1 M $1.3 M $1.1 M $1.0 M 99.999 %^a 00-05 $ 235.0 K $134.0 K $125.0 K $100.0 K $92.0 K

a Also referred to as ―five nine‘s‖ or the ―gold standard‖

Though availability is measured, there are additional pieces of data that are reported that can provide a business, and its IT department, valuable information on the unplanned outages being experienced. These include the number of unplanned outages reported, by type, by time period, by group of users and by impact to the business; the percentage of incidents by root cause; the overall time to recover from incidents, etcetera. Few IT departments want to report systems‘ availability that does not, at least, sound good to the business that pays for its services. In some cases, there will be too detailed information available to corporate managers about the performance by the IT department and, in other cases, too technical information (GAO, 2009).

One attraction of measuring availability is that a percentage is easy for senior managers to understand. One of the principles applied to optimise the likelihood that computer hardware systems and application software are highly available is to minimise change–in hardware, software, firmware, support personnel, etcetera–in any area that might influence the systems‘ stability, and therefore, availability. However, change is a required activity in an IT environment. At some point in time, bug fixes must be deployed; firmware must be upgraded; new hardware subcomponents must be added or replaced. While the actual value of availability may be correctly calculated, it is often reported by IT departments as a value designed to indicate a higher availability delivered than actually attained. Table 2-16 provides an example of how availability can be calculated and how that availability can be reported to the business.

Table 2-16. Calculating Availability and Calculating Reported Availability Calculating Availability and Calculating Reported Availability

A = Availability

M = Minutes per Year (525,600)

U = Unplanned Outage Minutes per Year ( 5,244) P = Planned Outage Minutes per Year ( 47,200)

Availability Reported Availability

A = (M–P–U) M

(525,600)–(47,200)–(5,244) = 90.02%

525,600

A = (M–U) M

(525,600)–(5,244) = 99.00%

525,600

A = 90.02% A = 99.00%

By ignoring the duration of planned outages as needing to be included in the availability percentage achieved by the IT department, the reported availability is nearly nine percent higher than the actual availability attained. It allows the IT department to report it has delivered systems that provided the company high availability. When reporting to an executive committee holding the purse strings for the coming year‘s IT budget, IT personnel are likely to report optimal data and await questions as how it was calculated.

In addition to the actual data values used when reporting availability, the report creators and the users of the reports benefit from knowing that availability is the product of the availability of the system components factors that comprise an IT environment (Zeng, 2007).

When, for example, a database is not available, it may be not available because of the hardware on which it resides (the storage), the database software itself, or the server on which the database software executes. If each of the three components has different availability values, the best availability that can be provided is the product of the three values, never allowing for gold standard availability in total, even if each subcomponent has gold standard availability. As shown in Table 2-17, the best possible availability of the subsystem is always less than the best possible availability of any single component, being the product of the best availability of all subcomponents of the subsystem.

Table 2-17. Calculating IT System Optimal Availability

Overall IT Availability Cannot Meet the Optimal Availability of the Least Available Subcomponent in an IT Environment

Overall Desired Availability = 99.99%

Server Availability = 99.90%

Storage Likelihood Availability = 99.99%

Database Likelihood Availability = 99.00%

Best Achievable Availability = Availability (Server Storage Database

)

Best Achievable Availability = (99.90 99.99 99.00) = 98.89%

In document FACTORES ASOCIADOS A LA RECUPERACIÓN DE PERSONAS CON PROBLEMAS DE SALUD MENTAL DE (página 54-61)