Leveraging DCIM to Increase Energy Efficiency and Savings

Contents Challenges of Today s Data Centers Turning Challenges into Opportunities with DCIM DCIM elements for Optimized Efficiencies and Green IT Summary and Q&A Siemens AG 2013 All rights reserved. Page 2

Challenges in Today s Data Centers Critical operations relying on data center Average downtime cost $300,000/hour Data centers use 10 to 30 times more energy per Sqft. than office space Silo ed systems: IT and Facility organizations often misaligned Nearly 25% of companies will run out of capacity in at least one of their sites this calendar year Increasing Publicity and Stringent Government Regulations Source: 1) The State of Data Center Evolution, April 2013, UBM Tech and InformationWeek Marketing Services 2) Research Roundup for Data Center Infrastructure Management Tools, March 2013, Gartner, Inc. 3) Uptime Institute 2013 Data Center Survey, April 2013. 4) Siemens internal estimate based on market research Siemens AG 2013 All rights reserved. Page 3

What is Datacenter Infrastructure Management (DCIM)? 2013 Gartner, Inc. and/or its affiliates. All rights reserved. Gartner is a registered trademark of Gartner, Inc. or its affiliates. For more information, e-mail info@gartner.com or visit gartner.com. Used with permission. Data center infrastructure management (DCIM) software tools monitor, measure, manage and/or control data center performance, utilization and energy consumption Ideally, DCIM provides this functionality for all IT-related equipment (such as servers, storage and network switches) and infrastructure components (such as PDUs and CRACs). Cs) DCIM enables IT professionals to understand energy consumption from a holistic data center perspective DCIM tools integrate facets of system management with building management and energy management, with a focus on IT assets and the physical infrastructure needed to support them Source: Courtesy of Gartner Siemens AG 2013 All rights reserved. Page 4

An Example of Facility Field Technology for Power Distribution Busway Power Busway Server Busway PDU / RPP integration Compared with cable and conduit 15-40% lower cost 50% less space Capability to transmit power quality and usage to EPMS/BMS/DCIM Siemens AG 2013 All rights reserved. Page 7

Power Metering and Monitoring Solutions for the Data Centers MV Metering Relays & transient Power Meters MV Metering Relays & transient Power Meters LV Switchgear / Switchboard Power Meters and communicating trip units LV Switchgear / Switchboard Power Meters and communicating trip units LV Branch Circuit Embedded Metering PDU / RPP integration LV Branch Circuit Embedded Metering Siemens AG 2013 All rights reserved. Page 8

DCIM Backbone of Integration Collect Information Network Fire/Life Safety Firewall Security & Access Consolidate Information VOIP Rack Cooling Power Distribution DCIM Storage Water HD Visualization Server Metering What-If Analysis Web Application Lighting Siemens AG 2013 All rights reserved. Page 10

Functional Overview & Key Features High definition asset visualization and analytics Collaboration and process management Real-time monitoring, alarm and event notification DCIM Computational Fluid Dynamics (CFD) Key performance indicator dashboard Infrastructure life cycle management Open interface and protocol support Siemens AG 2013 All rights reserved. Page 11

Visual Analytics for Asset Management, Monitoring, Alarm and Event Notification 4D Dashboards Import / export of model information in universal format (Spreadsheet, html, etc.) Rack / server visual reporting Cooling, power, physical U-space Real-time monitoring in 4D Cost, client, license expiry, age, etc. Intelligent attributes / tags Our brain can digest far more information when spatially distributed in 3D 4D Dashboard Spreadsheet-based information is difficult to digest Siemens AG 2013 All rights reserved. Page 12

Case Study Eindhoven, Netherlands Monitoring = Energy Savings Power chart showing real energy savings In one of the data centers Atos saw that the cooling fans were working too hard. After analysis, Atos found that the layout of the tiles was suboptimal. Without the trigger from the DCIM data, Atos would not have been able to see this. Due to DCIM Atos could rectify the error and check the effect of changing the tiles. Effect: 9% energy savings after 2 weeks = Benefit: energy savings of 50 kw/yr Siemens AG 2013 All rights reserved. Page 14

Case Study Eindhoven, Netherlands Meaningful Report = Longevity of Equipments + Energy Savings Cooling report on 3 different cooling machines Cooling facilities need to balance their load because they have to be changed together. In this benchmark report you can see that they were not balanced. This means that one cooling machine had to work harder while the others were more relaxed. Identifying this imbalance and correcting it therefore had a positive impact on improving the life expectancy of all cooling machines. Balancing of the load for different cooling facilities could mean: A longer life expectancy of all cooling facilities. Significant energy savings. Siemens AG 2013 All rights reserved. Page 15

One Way to Predict and Prevent is to Simulate A look at the datacenter supply chain Extensive CFD simulation Designed by Best practice concepts and detailed design best practice and organic growth and some CFD High ROI if done right: Lifecycle- Enabled CFD with Datacenter Clarity LC is key to the solution Virtual model of a datacenter 10W 140W+ 350W 1280W+ 4kW 30kW+ 150kW 25MW+ Predictive Energy Efficiency Siemens AG 2013 All rights reserved. Page 16

CFD & Energy Efficiency Recommendations Initial set point temperature = 68 F (20 C) Final set point temperature = 75 F (24 C) Max air temperature = 100 F (38 C) ) 12% energy savings Case study Temperature Uniformity = Higher Efficiency = Saving $$$$$ Cutting plane raised 1,500 mm from the room bottom Siemens AG 2013 All rights reserved. Page 17

Considerations for DCIM Gradual Deployment Establishing an accurate asset inventory Developing an accurate baseline using current state and utilization Monitor and alarm in real-time using previous asset behavior knowledge Data is often: Know what, when and how Know what and when to alarm, Decentralized long to monitor and whom should act on Incomplete Know what is the ideal warnings or alarms probing frequency Move from reactive Inaccurate Leverage Integration Expertise state of affairs to prevention Leverage your stakeholders! from the DCIM vendor and control Manage the baseline! STEP 1 STEP 2 STEP 3 Siemens AG 2013 All rights reserved. Page 18

Summary Technologies advances in areas such as physical infrastructure and IT stacks are improving efficiencies at the field level DCIM Reaching new levels in data center efficiencies Bridging gaps of IT and Facility Management Smarter Decisions Optimized Efficiencies Green IT Siemens AG 2013 All rights reserved. Page 19