Главная Обратная связь


Control and implementation

All changes to service and resource capacity must follow all IT processes such as Change, Release, Configuration and Project Management to ensure that the right degree of control and coordination is in place on all changes and that any new or change components are recorded and tracked through their lifecycle. Service Capacity Management

The main objective of the Service Capacity Management sub-process is to identify and understand the IT services, their use of resource, working patterns, peaks and troughs, and to ensure that the services meet their SLA targets, i.e. to ensure that the IT services perform as required. In this sub-process, the focus is on managing service performance, as determined by the targets contained in the agreed SLAs or SLRs.

The Service Capacity Management sub-process ensures that the services meet the agreed capacity service targets. The monitored service provides data that can identify trends from which normal service levels can be established. By regular monitoring and comparison with these levels, exception conditions can be defined, identified and reported on. Therefore Capacity Management informs SLM of any service breaches or near misses.

There will be occasions when incidents and problems are referred to Capacity Management from other processes, or it is identified that a service could fail to meet its SLA targets. On some of these occasions, the cause of the potential failure may not be resolved by Component Capacity Management. For example, when the failure is analysed it may be found that there is no lack of capacity, or no individual component is over-utilized. However, if the design or coding of an application is inefficient, then the service performance may need to be managed, as well as individual hardware or software resources. Service Capacity Management should also be monitoring service workloads and transactions to ensure that they remain within agreed limitations and thresholds.

The key to successful Service Capacity Management is to forecast issues, wherever possible, by monitoring changes in performance and monitoring the impact of changes. So this is another sub-process that has to be proactive and predictive, even pre-emptive, rather than reactive. However, there are times when it has to react to specific performance problems. From a knowledge and understanding of the performance requirements of each of the services being used, the effects of changes in the use of services can be estimated, and actions taken to ensure that the required service performance can be achieved. Component Capacity Management

The main objective of Component Capacity Management (CCM) is to identify and understand the performance, capacity and utilization of each of the individual components within the technology used to support the IT services, including the infrastructure, environment, data and applications. This ensures the optimum use of the current hardware and software resources in order to achieve and maintain the agreed service levels. All hardware components and many software components in the IT infrastructure have a finite capacity that, when approached or exceeded, has the potential to cause performance problems.

This sub-process is concerned with components such as processors, memory, disks, network bandwidth, network connections etc. So information on resource utilization needs to be collected on a continuous basis. Monitors should be installed on the individual hardware and software components, and then configured to collect the necessary data, which is accumulated and stored over a period of time. This is an activity generally carried out through monitoring and control within Service Operation. A direct feedback to CCM should be applied within this sub-process.

As in Service Capacity Management, the key to successful CCM is to forecast issues, wherever possible, and it therefore has to be proactive and predictive as well. However, there are times when CCM has to react to specific problems that are caused by a lack of capacity, or the inefficient use of the component. From a knowledge and understanding of the use of resource by each of the services being run, the effects of changes in the use of services can be estimated and hardware or software upgrades can be budgeted and planned. Alternatively, services can be balanced across the existing resources to make most effective use of the current resources. The underpinning activities of Capacity Management

The activities described in this section are necessary to support the sub-processes of Capacity Management, and these activities can be done both reactively or proactively, or even pre-emptively.

The major difference between the sub-processes is in the data that is being monitored and collected, and the perspective from which it is analysed. For example, the level of utilization of individual components in the infrastructure – such as processors, disks, and network links – is of interest in Component Capacity Management, while the transaction throughput rates and response times are of interest in Service Capacity Management. For Business Capacity Management, the transaction throughput rates for the online service need to be translated into business volumes – for example, in terms of sales invoices raised or orders taken. The biggest challenge facing Capacity Management is to understand the relationship between the demands and requirements of the business and the business workload, and to be able to translate these in terms of the impact and effect of these on the service and resource workloads and utilizations, so that appropriate thresholds can be set at each level.

Tuning and optimization activities

A number of the activities need to be carried out iteratively and form a natural cycle, as illustrated in Figure 4.12.

Figure 4.12 Iterative ongoing activities of Capacity Management

These activities provide the basic historical information and triggers necessary for all of the other activities and processes within Capacity Management. Monitors should be established on all the components and for each of the services. The data should be analysed using, wherever possible, expert systems to compare usage levels against thresholds. The results of the analysis should be included in reports, and recommendations made as appropriate. Some form of control mechanism may then be put in place to act on the recommendations. This may take the form of balancing services, balancing workloads, changing concurrency levels and adding or removing resources. All of the information accumulated during these activities should be stored in the Capacity Management Information System (CMIS) and the cycle then begins again, monitoring any changes made to ensure they have had a beneficial effect and collecting more data for future actions.

sdamzavas.net - 2020 год. Все права принадлежат их авторам! В случае нарушение авторского права, обращайтесь по форме обратной связи...