Convergence of Complexity

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2 Convergence of Complexity Optimize Existing Data Center Space Measure And Allocate Energy Cost Plan for new data centers or additional capacity How to make your Data Center Last Longer, Gartner, December 2008 Self Benchmarking Guide for Data Center Energy Performance, Lawrence Berkeley Nat l Labs, May 2006 Changing Data Center Behaviour Based on Chargeback Metrics, Data Center Dynamics, September 2008 By 2010, expense to power and cool worldwide installed base of servers is expected to grow to $44.5 billion, equivalent to 70% of new server spending. - IDC study

3 The Changing Face of Data Centres The need to address power, space, cost and capacity issues as well as the demand for resilience requires a new approach Energy-Efficient Blade Servers Virtualization to Create Internal Clouds within the Data Centre Public Cloud Platform Service Providers

4 Clouds Increase IT Management $ Spending (US$B) $300 $250 $200 $150 $100 $50 $1 Capital = $7 Management Power and cooling costs Management of virtual servers in the internal cloud Server mgmt. and admin. costs New server spending Millions Logical server installed base: Physical server installed base: $ *Source: IDC, CIO Strategies to Build the Next Gen Data Center

5 What s Driving Virtualization? Many companies are implementing virtualization technology to achieve a variety of benefits Build internal clouds to optimize resources More efficient use of server hardware Overcome space, energy, cooling limits Cheap redundancy Flexible response to production and development

6 A New Paradigm and Problem Logical Virtual Environment Physical Environment Most IT organizations want an integrated view between virtual and physical environments; visions are often ahead of existing product capabilities. - Stephen Elliot, IDC analyst

7 Virtual & Physical Management Challenges Issues in managing virtual and physical servers in a cloud computing environment Accessing both types of servers in a similar manner Administering access rights to both types of servers Maintaining those rights as virtual servers get moved around the datacenter Managing virtual machines across different VirtualCenters Collecting events from both types of servers Auditing access to both types of servers Reinforcing the availability of the physical foundation which support multiple virtual servers

8 The Challenge of Cloud Control New challenges in cloud-based data centres Virtual server sprawl A single application may span multiple VMs and physical servers The server configurations are changing all the time These challenges arise from two basic causes Virtual servers need to be managed differently from physical servers Data centers are only partially virtualized

9 A Holistic Management Approach to Cloud Control Simply [Manage]

10 Centralised Management Goals A service-oriented data centre architecture Ability to more widely deploy virtualization Achieve an efficient cloud computing environment in the data centre Lower cost of virtual server ownership Faster/easier response to change Reduced risk Convert CAPEX to OPEX by outsourcing to emerging cloud computing service providers that offer infrastructure-as-service

11 The Strategy Access to all resources from a single console Management of access and control in a common manner Insulation from virtual server moves Consolidated alarms, auditing Better, more granular security

12 Track Monitor Measure Your Data Center power consumption and cost IT Service Management Single, (Inventory, Secure, Monitoring Browser-based & Remote Alert, Patch Interface Power Blade Management, servers Provisioning) Management and enclosures Console devices Embedded service processors (IPMI, ilo, RSA, DRAC, ILOM/ALOM, irmc) Virtual Centers, ESX Servers and Virtual Machines Rack-mounted servers

13 A Service-Driven Model Data Center Maturity Model Ad-Hoc Reactive Proactive Service Minimal IT Operations Limited Staff, part-time Limited or No documentation Unrestricted IT Access No Standard Change Processes Outages Commonplace IT may not be mission critical No Predictability No SLA Audits Inaccurate Documentation High Error Rates Limited repeatability / re-use Fragmented Monitoring Little SLA predictability Incident Fire Fighting mode Some Change Management Fragmented Documentation Basic Charge-backs Limits on access Lower Error rates Focused Monitoring Root cause analysis Service Driven Management Integrated Change- Management Holistic dynamic monitoring Alignment with Business Demands Formal Capacity Management Accurate Configuration database Increase Value & Effort

14 Central Management Model Singapore Sydney New York Tokyo Mumbai Shanghai Hub and Spoke architecture a fully redundant, replicating database system that allows real-time updates and load balancing across multiple sites. It provides secure browser-based control of all of the local and remote servers and networking devices in your IT infrastructure.

15 Managing Power from the Data Centre to the Desktop Case Studies

16 The Data Center Power Crisis Over the next five years power failures and limits on power availability will halt data center operations at more than 90% of all companies By 2011, more than 70 percent of US enterprise data centers will face 'significant disruptions' related to energy consumption and floor space Power management and cooling have emerged as a bottleneck and critical element in data center operations and planning Increased densities make power and cooling the number one factor to ensuring satisfactory data center operation

17 How should we approach? Introduce Power Management Initiatives Change the way we access our IT assets globally, remotely Management solutions for data centers and desktops Power solutions which covers holistically in entire IT infrastructure Address power not only servers but other IT peripherals residing in data centers Real time information Gather feedback with power usage, power trending, threshold, availability of your enterprise IT resources

18 Datacenter Energy Costs Example Datacenter energy costs significant $$$$ By 2010, expense to power and cool worldwide installed base of servers is expected to grow to $44.5 billion, equivalent to 70% of new server spending. IDC study Typical Midsize Datacenter Energy Consumption Calculation 50 racks, 4 kw / rack Annual energy consumption of IT equipment 50*4*8760 = 1.75 million kwh Total IT equipment annual energy costs 1.75 million *11c/kWh = $192K Total Datacenter annual energy costs, accounting for energy consumption of cooling equipment $192K x 2 = $384K USD

19 Breakdown of Energy Consumption Facility 1 Facility 2 8% HVAC -Chiller & Pumps HVAC - Air Cond. 5% 5% Computer Loads Lighting 33% 9% 16% 34% UPS Loss Computer Load 16% Lighting 1% 73% HVAC- Pumps & Chiller HVAC- Air Movement UPS Losses IT equipment is the single largest component of data center energy consumption x savings on IT equipment translates to 2x for entire data center Source: Self Benchmarking Guide for Data Center Energy Performance, Lawrence Berkeley Nat l Labs, May 2006

20 Reducing IT Equipment Energy Use Chargeback models based on actual consumption Comparing different server architectures Virtualization & Consolidation Typically leads to higher rack densities Workflow analysis Move processes outside of peak rate hours Ability to turn on and off equipment when not in use Common requirement across all these possible methods is the need for visibility of power management and control down to the equipment level

21 Monitoring equipment level usage Rack PDU s with outlet level metering Ability to measure real time power, current, voltage and power factor Thresholding and proactive notification Several servers provide power consumption info Power management software solution Real time collection Historical tracking Reporting capabilities Ability to aggregate Scheduled shutdown Vendor neutral

22 Prep for Virtualization/Consolidation Minimize number of circuits to the rack Run all equipment at V as against 120V For rack densities >5kW, bring 3-phase power to the rack Use PDU s with mix of C19 and C13 outlets Separation of high density and low density zones - Use supplemental cooling for high density zones C13 outlets (low current) 10A Avocent Data Center Survey 2008 C19 outlets (high current) Amp

23 Reduce Infrastructure Energy costs Rightsize electrical infrastructure Saves capex $$ Provides better efficiency for all infrastructure equipment Capacity planning software Capacity vs usage reports Power Cooling Space Weight Connectivity Balance three phases at all levels within the datacenter Choose PDU s with sequential startup & cold start delay Consider equipment efficiencies at partial loads Variable capacity cooling & economizers

24 How to decrease cooling costs Use hot aisle, cold aisle approach Use blanking panels Conduct yearly airflow studies to identify inefficiencies Use environmental sensors to monitor hot spots Use blanking panels Seal gaps in floor and around perimeters Use racks with proper room for cable management Do not use perforated tiles for dead spaces Best practices alone have been seen to reduce cooling costs by 5% or more

25 The Green Grid suggested measurements PUE= PUE (Power Usage Effectiveness) DCiE (Data center Infrastructure Efficiency) Total Facility Power IT equipment Power Maintain Metrics DCiE= IT equipment Power Total Facility Power These measurements define the efficiency of the physical infrastructure equipment What portion of the total power coming into the Data center is being used by IT gear? Total Facility power can be measured at the utility entrance to the datacenter Use monitoring tools that aggregate power consumption for all IT equipment If the output of the UPS is connected strictly to all IT equipment, it could be used as a proxy for IT Equipment power

26 Case in Point Data Center AFCOM ran studies at 19 Data Centers and found the following: The Data Centers were over-cooled by an average of 2.6 times 40-60% of power consumption was used for cooling Potential savings of 20 35%! 5 Megawatts Data cents/kwh Annual power costs = SGD $9,500,220 Power utilization (by modeling power consumption) Selecting appropriate hardware Consolidate underutilized equipment Reduce power consumption by just 20% (est) SGD $1,900,044 annual savings

27 Case in Point Desktop Base on Desktop system utilization on a average PC Average PC is about KWh / week (est 4.3 KWh per day) Using electricity cost of cents /KWh (Singapore Services Tariff) 4.3 KWh / day Desktop using 21.69cents/KWh On a annual usage per desktop SGD $340 With 10,000 desktops / workstations deployed globally On a annual usage per desktop SGD $3,410,000 Reduce power consumption by just 20% SGD $682,000 annual savings

28 Tools in Use Today Multiple Excel Spreadsheets AutoCAD Drawings Individuals Varying Degrees of Completeness & Meetings Visio Databases Vendor Dependent Monitoring Manage the Data Center as a Single Entity

29 Asset Management Capacity Management Operations Management Integrated Management Approach Unable to locate IT asset in multiple Data Centers What are the assets being deployed in every Data Centers Who and how are the assets being manage and maintain Can we have a reporting on assets inventory? How can I get a better workflow process for asset? How much rack capacity do I have left How much power have we consumed in the London Data Centre Where are all of the assets owned by finance located What physical changes occurred globally in the last 90 days If we increase our Blades servers in the Milan Data Centre do we have enough cooling Where can we best deploy the next project How do we access to multiple IT assets globally Can we have a consolidated view of all assets of my datacenters? How can I access servers, switches, Virtual machines, Power of any makes? Can I remotely power off server? How can I indentify who has been accessing my IT assets globally? How can I be inform of notification should there by any outages?

30 Power consumption reports Power Baseline Samples Environmental reports

31 Proactive Monitoring & Reporting Manage and monitor power costs Data center Row Rack (as shown) Asset level Energy Cost Reports Historical View

32 Holistic Data Centre Power Mgmt Reduce power consumption / costs Balance cabinet heat distribution Reduce labor costs Avoid expensive consulting engagements & engineering services Data Centre Reduce risk of moves/adds/changes

33 Summary Chargeback your customers on actual usage Provide customers the tools to monitor equipment level power usage Deploy the simple best practices for to decrease cooling costs Invest in appropriate power distribution and cooling technologies to support high density zones Deploy the simple best practices for to decrease cooling costs Deploy real time monitoring and Capacity management software Maintain metrics

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