Abstract; Introduction; Calculating The Mcu - HP Bc1500 - BladeSystem - Blade PC Supplementary Manual

Abstract

A cost-efficient Consolidated Client Infrastructure (CCI) implementation is one that can satisfy end user
demands without an excessive amount of hardware. Since the maximum number of concurrent users
defines the amount of hardware to be purchased, calculating maximum concurrency becomes an
important aspect of designing a CCI solution. This document provides guidelines for calculating the
amount of hardware required to meet maximum concurrency.

Introduction

The most cost-efficient model of CCI uses Dynamic Allocation methodology to allocate one blade PC
to every end user who logs in. Blade allocation is essentially a random assignment. There must be at
least as many blades available as there are employees trying to log-in or already logged on at any
one moment in time.
Obviously, it is extremely unlikely that in a sample size of 1,000 employees, all employees will be
trying to use a PC at the same time. As such, with CCI's Dynamic Allocation model, there is no need
to purchase and support a blade PC for every possible user. Instead, a CCI implementation needs
only enough hardware to support the number of Maximum Concurrent Users (MCU).
HP has concluded that a maximum concurrency rating of 70% is the recommended baseline for large
CCI implementations.

Calculating the MCU

In establishing 70% as the baseline MCU rate, the following assumptions are made:
• There are 250 work days in each year ((52 weeks x 5 work days) – 10 national holidays).
• Each employee is actively on their computer an average of 225 days per year, based on the
following number of days each employee takes off from work: 10 vacation days, 5 sick days, 5
paid time off days, 2.5 off-site training days, and 2.5 travel days.
• On average, each employee is not working an additional 10 days for the following reasons:
maternity and paternity leave, emergency leave, military leave, academic and other leaves of
absence,
• The above assumptions result in an average employee using their PC 215 days a year.
If a typical user was able to claim a blade for the entire workday, and absences were evenly
distributed across a year for all workers, there would only be a need to purchase and support 86%
(215/250) as many blades as there are employees.
Furthermore, if blade PCs can be returned to a common pool if idle for a specified period of time (as
can be done with CCI), then the MCU can be much less than 86%. The assumption is that at least
25% of a typical large enterprise's personal computers are idle at least 2 hours a day even for those
people who are working. This is due to employees coming in late, leaving early, long lunches,
meetings, briefings, seminars, etc. This implies that of all employees, only 64% are active on their
computers at any one time. However, a computer that is idle but still logged on cannot be part of the
pool available for assignment to another user. In addition, since peak demand (not just the average)
must be met, we round up by 10% and conclude that an MCU assumption of about 70% is
reasonable as a starting point.
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