Datacenter

1. Data Center Efficiency Measurements http://www.google.cz/corporate/datacenters/measuring.html 2. Virtualization and Automation Drive Dynamic Data Centers http://www.datacenterdynamics.com/Media/MediaManager/Virtualisation%20and %20Automation%20Drive%20Dynamics%20Data%20Centers.pdf 3. Data Center Measurement, Metrics & Capacity Planning http://www.byteandswitch.com/document.asp?doc_id=174585 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. 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. Measuring IT resources across different types of resources, including multiple tiers, categories, types, functions, and cost (price bands) of servers, storage, and networking technologies, is not a trivial task. However, IT resource metrics can be addressed over

time to address performance, availability, capacity, and energy to achieve a given level of work or service delivered under different conditions. It is important to avoid trying to do too much with a single or limited metric that compares too many different facets of resource usage. For example, simply comparing all IT equipment from an inactive, idle perspective does not reflect productivity and energy efficiency for doing useful work. Likewise, not considering low-power modes ignores energy-saving opportunities during low-activity periods. Focusing only on storage or server utilization or capacity per given footprint does not tell how much useful work can be done in that footprint per unit of energy at a given cost and service delivery level. Virtual data centers require physical resources to function efficiently and in a green or environmentally friendly manner. Thus it is vital to understand the value of resource performance, availability, capacity, and energy usage to deliver various IT services. Understanding the relationship between different resources and how they are used is important to gauge improvement and productivity as well as data center efficiency. For example, while the cost per raw terabyte may seem relatively inexpensive, the cost for I/O response time performance needs to be considered for active data. Having enough resources to support business and application needs is essential to a resilient storage network. Without adequate storage and storage networking resources, availability and performance can be negatively impacted. Poor metrics and information can lead to poor decisions and management. Establish availability, performance, response time, and other objectives to gauge and measure performance of the end-to-end storage and storage networking infrastructure. Be practical, as it can be easy to get caught up in the details and lose sight of the bigger picture and objectives. 4. HP Capacity Advisor Version 4.0 User's Guide http://www.docs.hp.com/en/T8670-90001/T8670-90001.pdf Introduction HP Capacity Advisor is a utility that allows you to monitor and evaluate system and workload utilization of CPU cores, memory, network and disk I/O, and power. With this information, you can load your systems to make best use of the available resources. You can monitor and evaluate one or more systems that are connected in a cluster configuration or to a network. A single system can include multi-core or hyper-threaded processors. Capacity Advisor helps you evaluate system consolidations, load balancing, changing system attributes, and varying workloads to decide how to move workloads to improve utilization. The quantitative results from Capacity Advisor can aid the planner in estimating future system workloads and in planning for changes to system configurations. With Capacity Advisor, you can perform the following tasks within an easy-to-navigate, clearly notated graphical user interface: • Collect utilization data on CPU cores, memory, network and disk I/O, and power • View historical resource utilization for whole-OS and sub-OS workloads on HP-UX and whole-OS workload resource utilization on Microsoft® Windows systems.

• View historical workload resource utilization and aggregate utilization across the partitioning continuum (nPars, HP-UX vPars, HP-UX Virtual Machines) • Generate resource utilization reports • Plan workload or system changes, and assess impact on resource utilization • Assess resource utilization impact for proposed changes in workload location or size • Evaluate trends for forecasting future resource needs Capacity Advisor can be used to simulate changes in system configuration, such as the following: • Consolidating several systems into one system • Re-sizing a system for an upgrade • Re-sizing the demands on a system to reflect a forecast • Replacing older, small to mid-sized systems with virtual machines Capacity Advisor can use data collected over time to show the results of these configuration changes in many ways. Graphical views are available so you can see what the effects of the changes are over time. Tables are available that give the percentage of time and the degree to which the system is busy; this information is valuable in comparing resource utilization and quality of service before and after a change. Other tables show how many minutes per month the system is unacceptably busy–a measure valuable for both quality of service and for estimating TiCAP bills. Because Capacity Advisor works from data traces collected over time, it is much more accurate than using only peak data or average data in understanding your systems and the workloads they support. 5 Understanding Relative Server Capacity. http://www.ibmsystemsmag.com/mainframe/marchapril03/technicalcorner/10041p2.aspx

6. 7.

http://www.mathematik.uni-trier.de/tf/98_16.ps