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Whitepapers

This section contains whitepapers produced by Capacitas as part of our programme of research.

Sizing the UK Identity Card System

This paper summarises the findings of an exercise carried out by Capacitas to establish a demand plan for the UK Identity Card System.
The demand plan is a statement of the expected business and technical demand of the UK Identity Card System and is a key indicator of both its scale and cost. This is the first published demand plan of the UK Identity Card System.
The appendix, which contains more detailed information, can be found here

Automated Detection of Workload Profile Changes

Capacity Planners want to understand the daily, weekly and monthly demand profile of a system over time. This analysis is called workload profiling. A common approach to workload profiling is to size the system so that it meets demand during the busiest hour of a day. However the daily workload profile may change over time as new workloads are introduced with different busy hours and existing workloads with the current busy hour decrease or grow more slowly relative to the new workload. The capacity planner will not see these changes in workload profile by simply analysing busy hour values until after the workload profile has changed. This article outlines a simple approach to determine if a workload profile has changed over a period of time.

The Challenges of Capacity Planning Multiple Services across a Single Infrastructure

The advent of technologies such as MPLS promise more cost effective network solutions by using the same infrastructure to support multiple service types. However, the full savings cannot be realised without the use of more sophisticated capacity planning methodologies. The use of these sophisticated methodologies is more time consuming than those used for planning networks with a single service type and hence more expensive in terms of operational costs. This paper compares the capacity planning methodologies for multiple service types over single and multiple network infrastructures.

Demand Driven Capacity Planning: Improved Expenditure Control & Customer Service

The most effective method for capacity planning within any organisation is to use Demand Driven Capacity Planning. This enables infrastructure capacity to accurately reflect expected demand for the services supplied, and is as proactive a method as is possible in most circumstances. There are several dependencies to using Demand Driven Planning that require careful consideration before this method is adopted, some of which may seem insurmountable in many organisations but in reality are not. Key benefits of this approach are the ability to respond to customer requirements faster, thereby improving revenue recognition, and more accurate financial forecasting of expenditure. This paper is intended to help key decision-makers examine the benefits of demand-driven planning prior to adoption.

How to Outsource your Network Without Losing Control

In the past decade the outsourcing of corporate networks has become common practice within the UK. To control costs, and reduce excess corporate assets, corporations have 'sold' their entire network infrastructure to third-party network services companies. The use of outsourced fixed-line networks and VPNs has created control issues for many of the customers of these services. With these issues in mind Capacitas has developed a set of services which can provide the outsourced network customer with an independent method of validation and auditing. This allows either occasional or regular monitoring to be established independent of the outsourcer. Reporting can be then validated accurately and discrepancies investigated in depth with the outsourcer.

Using Capacity Planning and Supply Chain Automation to Competitive Advantage

Capacity Planning is the key function that maximises an organisation's profit. Without capacity planning the organisation will not meet customer demand, thereby losing revenue, or over supply its product, thereby wasting capital. We call this the balancing act of capacity planning, or value chain optimisation. As the telecommunications and IT industries become more competitive the rate of change is increasing dramatically, whereas our capacity planning philosophy has remained static. We must learn that our discipline is not different to other industries, such as manufacturing, where there has been a paradigm shift in the last two decades. We must investigate and where possible adopt these techniques.

Automated Threshold Alerting using Statistical Filtering

There are inherent limitations in traditional threshold reporting methods where fixed thresholds are used with no historical trending. This paper introduces an alternative mechanism, which provides long term trending and generates exceptions when significant change has taken place, be it growth in capacity requirement or freeing up of capacity. The mechanism also goes some way to prevent the generation of false alarms, which often occur in the use of traditional threshold reporting methods.

Capacity Planning for Automated Provisioning Tools (Part 1)

With the market moving towards faster network service provisioning the planning of network capacity must change accordingly. The use of Automated Provisioning Tools creates new challenges for the Network Planner, requiring rethinking some old concepts.

Are Capacity Planners Just Bean Counters?

This paper outlines an approach for deriving the optimal values for some of the Enterprise Java Beans (EJB) container parameters. The EJB container parameter values derived include the minimum and maximum number of beans and the pool idle out timer. The values for these parameters are derived in order to reduce latency in applications that use EJB technology. The approach assumes that the EJB containers can be represented as M/M/m queuing systems. The approach uses standard queuing formulae to optimise the number of bean instances. The results from this approach have not being validated against actual results from a test or live environment. The author hopes that once this approach has been validated that capacity planners or developers can use the formula results to tune the EJB container parameters.
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