Modern Data Centers: Creating a New Value Proposition

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1 Modern Data Centers: Creating a New Value Proposition América Latina 2008 Inter-secretarial Commission for the Development of Electronic Government Mexico City 24 May 2013

2 Data Center Consolidation Consolidating data centers is much more than physical movement of servers and infrastructure from many locations to fewer sites. The facility costs and power savings that can be achieve are just the beginning of the opportunity The biggest benefits come from using the consolidation initiative to Rationalize the application portfolio and reduce license cost Virtualize the server, storage, and network infrastructure Reduce labor and/or cost of external services associated with maintenance activities Archive inactive data Monitor the quality of active data Monitor overall performance to improve service delivery Create a network of consolidated data centers for DR Slide 2

3 Large Data Centers Slide 3

4 Medium Sized Data Centers Slide 4

5 Small Data Center Slide 5

6 Questions for You How many data centers are represented in this room? How many that are Large >5,000 sq ft Medium 1,000 4,999 sq ft Small <1,000 sq ft Slide 6

7 Classification of Data Centers Fault Tolerant Site - Redundant capacity components and multiple electrical path distribution simultaneously serving computing equipment Concurrently Maintainable - Redundant capacity components and multiple electrical path distribution but only one path serves computing equipment at any time Redundant capacity Redundant capacity components but only single non-redundant electrical path distribution Basic Infrastructure - Non redundant capacity components and single non redundant electrical path distribution Slide 7

8 Service Availability Area Tier I Tier II Tier III Tier IV Operational Implications Average Annual impact of maintenance/ unplanned outages Site is susceptible to disruption from planned and unplanned activities and events Average Downtime for a Tier I data center is estimated at 28.8 hours per year or 99.67% availability Site may be susceptible to capacity component failure and will be susceptible to a distribution path failure Average Downtime for a Tier II data center is estimated at 22 hours per year or 99.75% availability Site is susceptible to disruption from unplanned activities Average Downtime for a Tier III data center is estimated at 1.6 hours per year or 99.98% availability Site is not susceptible to a single worst-case unplanned event or any planned maintenance activity Average Downtime for a Tier IV data center is estimated at 0.8 hours per year or 99.99% availability Slide 8

9 Attributes of Small Data Centers Smaller facilities have limited scale and access to few resources Since support personnel are few, they tend to be less organized and more vulnerable to staffing absences Since these sites generally have less access to financial resources: They are less secure, Less able to operate within recommended temperature and humidity ranges, Generally unmonitored after working hours Small data centers of this sort are highly susceptible to disruption from planned and unplanned activities and events. Average downtime is at least 65 times greater than a Tier 4 data center and at least 17 times greater than a Tier 3 data center Slide 9

10 Consolidation: An Active Trend U.S. Federal Government initiative Baseline ~2,900 data centers Goal 1,132 data centers Canada Baseline plus centers Goal 140 data centers single purpose 10 data centers General Motors Baseline 23 major data centers Goal 2 major data centers HP Baseline Goal 85 major centers 6 major centers Australia Goal Cost Savings of $1 Billion AUS Intel Baseline Goal 130 major centers 8 major centers Slide 10

11 States Are Consolidating At the state level within the United States, data center consolidation has been active since 2007 Despite varying definitions for what constitutes an enterprise data center, the trend towards consolidation appears to be universal States have been consolidating their computing assets into raised floor, secured, centralized data center facilities. Many states are utilizing remote back-up data center facilities for the purpose of back-up and disaster recovery and business continuity. 11

12 Why Consolidate? Improve service levels Reduce costs Make strategic moves to or away from certain platform types Reduce staff levels or avoid further hiring Align systems with the enterprise's organization Improve focus on business, operational excellence, or architecture issues Support systems added in a merger or acquisition (Datacenter Rationalization) Private Sector Slide 12

13 Next Generation Data Center - Server Server Infrastructure Racks of servers, with each server (or sets of servers) tied to a specific application Every new application brings the demand for more new servers Typical utilization for Intel based servers ranges from 10% to 30% And yet spikes do occur that can affect overall application performance Impact of Virtualization Server hardware and the actual business workload get uncoupled Consolidation of physical servers ranges from 10 to 20 down to 1 In effect 20 physical servers now operate as 20 virtual servers on a single machine Improved application performance as virtualization software is continually making adjustments to computing resource allocations Enhances overall disaster recovery capability since all applications are now the equivalent of files that can be easily transferred to a DR site 13

14 Next Generation Data Center - Storage Hypervisor technology at the server Virtualization of physical storage Solid state memory disk Multiple disk technologies within a single array Improved performance and data protection features Performance based Tiering Slide 14

15 Next Generation Data Center - Network Network Switches New switch technology allows a single switch to support the load that would have required as many as 10 older switches Network virtualization enabled through software-defined technologies help organizations enable such things as Global Server Load Balancing and device interrogation. Software defined networks allow more robust disaster recovery and business continuity environment Slide 15

16 Next Generation Data Center Other Technologies Blade Chassis HP, Cisco, Dell, IBM, etc. all make more efficient and consolidated pieces of hardware This has also helped improve wiring and reduced energy consumption Power Distribution and Racks Controlling rack space has allowed significant reductions in the costs associated with cooling, power, and airflow Single Pane of Glass Management Tool set consolidation to reduce license cost, improve operational coverage, promote higher skills, and deliver enhanced performance Slide 16

17 The Virtualization Management Gap Slide 17

18 The Dark Side of Virtualization - Complexity Headwinds For many organizations, as the number of virtual machines increases so does the complexity of data center infrastructure management As the number of virtual applications continues to grow, the cost of managing and maintaining the data center continues to increase Tailwinds High performing organizations make extensive use of automation as countermeasures to these is headwinds By automating the provisioning and management processes, management complexity is reduced The allows high performing organizations of the full benefits of virtualization and partially avoid the virtualization management gap Mind the Gap - Additional Tactics Are Required Slide 18

19 Create Headwind Offsets To achieve superior productivity, organizations must simplify, standardize, and automate management processes Automate the provisioning process to remove labor content, promote velocity, and improve quality Free IT staff from maintenance activities so they may focus on strategic projects that increase the organization s competitiveness Reduce management cost as a percentage of total data center costs Remove management complexity as a barrier to further virtualization Slide 19

20 Server Virtualization Affects Networks Slide 20

21 New Source of Latency Current three-tier hierarchical networks aren t well suited for high-volume server-toserver communications. Server-to-server traffic is forced to traverse multiple layers of switches, and each switch adds latency to the connection Implementation of flat, low-latency networks is required to accommodate volumeintensive east-west traffic flows that are delay-sensitive Slide 21

22 The Problem With Latency 9 AOL Analysis Change in Average Page Views Per Visit 8 7 Page Views Per Visit Average Page Views Per Visit Autos Average Page Views Per Visit Money Average Page Views Per Visit Shopping th 20th 30th 40th 50th 60th 70th 80th 90th 100th Slide 22

23 The Problem with Latency Increases in latency degrade user satisfaction and in some cases also reduced revenue Amazon: 100 ms of extra load time caused a 1% drop in sales. (Source: G. Linden, Amazon) Google: 500 ms of extra load time caused 20% fewer searches. (Source: M. Mayer, Google) Yahoo!: 400 ms of extra load time caused a 5 to 9% increase in the number of people that clicked "back" before the page even loaded. (Source: N. Sullivan, Yahoo!) Decreases in latency improve user satisfaction Google: trimming page size by 30% resulted in 30% more map requests. (Source: M. Mayer, Google) Next Generation Network Switching and Revised Topologies Mitigate this Risk Slide 23

24 Key Technical Success Factors A prior high level of operating maturity prior to starting Strong experience standardizing configuration across development, test, and production environments Solid understanding of the application portfolio and its forward demand requirements Effective deployment of Application Lifecycle Management (ALM) tools Solid experience with automated provisioning of virtual machine images Solid experience automating production system maintenance activities Slide 24

25 What is the Journey? Feasibility Assessment Architecture Implementation Manage Business Goals Applications App Grouping Applications Enterprise Success Criteria Server/OS Server Servers Optimization Target Apps Storage Storage Storage Monitor Target Servers Network Network Network Infrastructure Target Storage Security Security Security Security Infrastructure Infrastructure Infrastructure Labor/Services Financial Return Financial Return Financial Return Financial Return Slide 25

26 Is the Journey Worth it? The single best metric for data center labor efficiency is the ratio of system administrators to physical servers. Small footprint data centers typically achieve ratios of 10 physical servers per 1 system administrator. High performing data centers invest heavily in labor saving automation Task automation, Workload monitoring, Virtualization of servers, storage, and network Process monitoring, and Establishment of gold build configurations They can achieve ratios of up to 1,000 physical servers per 1 system administrator It is unlikely that the Federal Government can achieve this ratio, simply because the nature of the computing load has more variability than companies like Google or Facebook. Slide 26

27 Labor Productivity and Service Availability Performance and Productivity Comparison versus Tier 1 Data Center Assuming 10,000 servers Tier 1 Tier 3 Tier 4 Improvement in Availability n/a 17x 65x Administrator Ratio 10: : '1000:1 Estimated # of Administrators 1, Average cost per Administator $ 35,000 $ 35,000 $ 35,000 Cost for System Adminitrators $ 35,000,000 $ 3,500,000 $ 3,500,000 Recurring Savings vs. Tier 1 n/a $ 31,500,000 $ 31,500,000 Well run, large scale data centers deliver both superior availability and lower cost than their smaller footprint counterparts Slide 27

28 Non Labor Savings Approximate areas of savings 5-15% cash creation on the value of reclaimed data center assets 4-10% savings by installing best-in class power equipment 7-15% savings due to more efficient cooling and air flow architectures Slide 28

29 Lower Cost is Only Part of the Value Created Rationalize the Applications Portfolio Consolidate common applications Retire legacy applications Remove inactive data from live applications Many applications that are still active and useful are carrying years of transactional data that is rarely used. Compress this data on disk and restore to production systems as necessary Monitor the quality of active data Profile data to find inconsistencies, develop scorecards to monitor and report on data quality trends, and provide workflow and analysis tools to enable the business users and data stewards to effectively deal with exceptions Monitor overall performance Establish thresholds and alerts to promote higher performance Enable DR across network of consolidated data centers Establish dynamic mirrors between sites to reduce outage window Slide 29

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