Data Center Measurement, Metrics & Capacity Planning
April 01, 2009
Good decision making requires timely and insightful information. Key to making informed decisions along with implementing strategies is having insight into IT resource usage and the services being delivered. Information about what IT resources exist, how they are being used, and the level of service being delivered is essential to identifying areas of improvement to boost productivity, raise efficiency, and reduce costs. It is important to identify metrics and techniques that enable timely and informed decisions to boost efficiency in the most applicable manner to meet IT service requirements.
The overall health and status of the equipment, the steady supply of raw materials, energy or power supply, and the quality of service need to be constantly measured for timely management decisions to be made. For example, in an electrical power plant, control rooms' or operations' nerve centers closely monitor different aspects of the facility and its resources, including fuel supply and cost, production schedules and forecasts, boilers, exhaust air scrubbers, water chillers and associated pumps, turbines, and transmission status.
A common focus, particularly for environments looking to use virtualization for server consolidation, is server utilization. Server utilization does provide a partial picture; however, it is important to look also at performance and availability for additional insight into how a server is running. For example, a server may operate at a given low utilization rate to meet application service-level response time or performance requirements. For networks, including switches, routers, bridges, gateways, and other specialized appliances, several metrics may be considered, including usage or utilization; performance in terms of number of frames, packets, IOPS, or bandwidth per second; and latency, errors, or queues indicating network congestion or bottlenecks.
From a storage standpoint, metrics should reflect performance in terms of IOPS, bandwidth, and latency for various types of workloads. Availability metrics reflect how much time, or what percent of time, the storage is available or ready for use. Capacity metrics reflect how much or what percentage of a storage system is being used. Energy metrics can be combined with performance, availability, and capacity metrics to determine energy efficiency. Storage system capacity metrics should also reflect various native storage capacities in terms of raw, unconfigured, and configured capacity. Storage granularity can be assessed on a total usable storage system (block, file, and object based and content accessible storage-cas) disk or tape basis or on a media enclosure basis -- for example, disk shelves enclosure or individual device (spindle) basis. Another dimension is the footprint of the storage solution, such as the floor space and rack space and that may include height, weight, width, depth, or number of floor tiles.