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Capacity management

Information technology resources are sufficient to meet business requirements effectively

  • 6 min read
  • 4 chapters

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Through Virtual machine

As the usage of IT services change and functionality evolves, the amount of central processing units (CPUs), memory and storage to a physical or virtual server etc. also changes. If there are spikes in, for example, processing power at a particular time of the day, it proposes analyzing what is happening at that time and making changes to maximize the existing IT infrastructure; for example, tuning the application, or moving a batch cycle to a quieter period. This capacity planning identifies any potential capacity related issues likely to arise, and justifies any necessary investment decisions - for example, the server requirements to accommodate future IT resource demand, or a data center consolidation.

These activities are intended to optimize performance and efficiency, and to plan for and justify financial investments. Capacity management is concerned with:

  • Monitoring the performance and throughput or load on a server, server farm, or property
  • Performance analysis of measurement data, including analysis of the impact of new releases on capacity
  • Performance tuning of activities to ensure the most efficient use of existing infrastructure
  • Understanding the demands on the service and future plans for workload growth (or shrinkage)
  • Influences on demand for computing resources
  • Capacity planning of storage, computer hardware, software and connection infrastructure resources required over some future period of time.

Capacity management interacts with the discipline of Performance Engineering, both during the requirements and design activities of building a system, and when using performance monitoring.

Factors affecting network performance

Not all networks are the same. As data is broken into component parts (often known frames, packets, or segments) for transmission, several factors can affect their delivery.

  • Delay: It can take a long time for a packet to be delivered across intervening networks. In reliable protocols where a receiver acknowledges delivery of each chunk of data, it is possible to measure this as round-trip time.
  • Jitter: This is the variability of delay. Low jitter is desirable, as it ensures a steady stream of packets being delivered. If this varies above 200ms, buffers may get starved and not have data to process.
  • Reception Order: Some real-time protocols like voice and video require packets to arrive in the correct sequence order to be processed. If packets arrive out-of-order or out-of-sequence, they may have to be dropped because they cannot be inserted into the stream that has already been played.
  • Packet loss: In some cases, intermediate devices in a network will lose packets. This may be due to errors, to overloading of the intermediate network, or to the intentional discarding of traffic in order to enforce a particular service level.
  • Retransmission: When packets are lost in a reliable network, they are retransmitted. This incurs two delays: First, the delay from re-sending the data; and second, the delay resulting from waiting until the data is received in the correct order before forwarding it up the protocol stack.
  • Throughput: The amount of traffic a network can carry is measured as throughput, usually in terms such as kilobits per second. Throughput is analogous to the number of lanes on a highway, whereas latency is analogous to its speed limit.

These factors, and others (such as the performance of the network signaling on the end nodes, compression, encryption, concurrency, and so on) all affect the effective performance of a network. In some cases, the network may not work at all; in others, it may be slow or unusable. And because applications run over these networks, application performance suffers. Various intelligent solutions are available to ensure that traffic over the network is effectively managed to optimize performance for all users. See Traffic Shaping

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