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HP Thermal Sensor Grid

HP Thermal Sensor Grid. Mathew Brown HP Cloud Services Global Data Center Operations Jun 13, 2013. Agenda • Introduction • Problem Statement • Rack Sensor Solution • Software Architecture • Using the Data (Visualizations and more) • Measuring Success. Introduction.

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HP Thermal Sensor Grid

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  1. HP Thermal Sensor Grid Mathew Brown HP Cloud Services Global Data Center Operations Jun 13, 2013

  2. Agenda • Introduction • Problem Statement • Rack Sensor Solution • Software Architecture • Using the Data (Visualizations and more) • Measuring Success

  3. Introduction Data Centers: HP-IT Global Data Centers • (6) Data Centers & (100) Satellite compute spaces • 400,000+ Sq./ft. • 13,000+ IT racks • 30,000+ servers Core Members: Matt Brown ItoroMeshioyoe Brad Ziemer Erick Levitre Ken Jackson Kevin Smith George Mckee • Organizations: • HP-IT Global Data Center Strategy and Design • HP-IT Cyber Security • HP-IT Global Telecom • HP Cloud Services • HP Labs • End-User Organizations: • Facilities • Data Center IT Operations • Data Center IT Engineering • Enterprise Services • Vendors: • RFCode • Rovisys • OSISoft

  4. Problem Statement • Data Center Engineering was engaged in lots of Data Center energy efficiency projects • Hot Aisle containment • VFD controls • Variable flow floor tiles • Plenum sealing • Temperature adjustments • Etc… • We understood the operational performance and impact to the Mechanical plant, but we realized we didn’t know anything about cooling performance at the IT. • Point measurement solutions were not very useful • Dynamic IT loads were difficult to understand and predict • CFD models were only as good as the quality of input data • We needed a Performance metric for cooling

  5. Technical Objectives • Objectives: • Instrument enough racks in the data center provide an adequate coverage grid to measuring cooling performance • Use Herrlin, M. K., 2005, Rack Cooling Effectiveness in Data Centers & The Green Grids Data Center Maturity Model as a framework for instrumentation • Deliver a hardware abstract solution that meet IT application architecture requirements • Unify data across all data centers into a single database with common role based analytics tools • Standardize one single performance metric for analyzing cooling effectiveness across all data centers

  6. What is RCI ?

  7. RCI – Rack Cooling Index • The Rack Cooling Index (RCI) • Developed by ANCIS • Magnus K. Herrlin, Ph.D. Formerly, Principal Scientist for Telcordia Technologies • The RCI: a dimensionless index that could become the basis for a common standard • measures how effectively equipment racks are cooled and maintained within industry thermal guidelines and standards • provides the basis for interpreting modeled or measured air intake temperatures

  8. Calculating RCI • The Math Degree Range Tmin rec –Tmin allowable of RCI Low intake temp calculations Degree Range Tmax allowable –Tmax rec of RCI IHI intake temp calculations Number of intake temps Number of intake temps Number of intake temps Number of intake temps Example Excel Formulas =IF(20=0,"",(1-(1/(20*10)))*100) =IF(20=0,"",(1-(42/(20*6)))*100)

  9. Benefits of RCI • Benefits of RCI • Meaningful measure that can also be shown graphically • Easily understood numerical scale - 100% means all racks are cooled to a standard or objective • By using two indices, over-cooling of some racks does not compensate for under-cooling of others • Provides the means to isolate potential heat-related failures • Portable and non-dimensional - it work with any standard or guideline that specifies max/min temperature ranges.

  10. Rack Sensor Solution

  11. Methodology • Technology Evaluations: • Compared several different sensor & software solutions • Developed TCO cost analysis • Created Test /Dev environment for small scale solution testing / POC • Made sure solution could integrate with existing technologies i.e. EPMS, DCIM solutions • Engaged IT security and Network engineering teams for high level solution design and buy in.

  12. Cost Comparisons • Average cost for a wired solution is ~$500 per rack with cost of associated infrastructure. • Network infrastructure cabling to each rack >~$40K per cell • Three control modules per row for sensors ~$3-5K • Sensors ~$100-250 per sensor • Switches ~$35K per cell • Total per cell >~$200K • Cost of the RF Code solution is ~$250 per rack (4 sensors per rack) minimal infrastructure costs. • Hardware cost is approximately $80K per cell • POE switch $6K per cell • Software/Integration: $14K per cell • Total cost estimate per cell: $100K • Cost of leveraging existing wired Sensors in particular locations <$25K

  13. Solution • Launch a project to deploy 13,000+ sensors across (6) Core IT data centers and (100) compute spaces • Leverage OSIsoft PI system as the data collection and analytics layer • Utilized RFCode 433mhz RF sensors for rack level instrumentation where we didn’t already have legacy wired sensors • Integrated 4000+ pre-existing wired sensors • Hired a systems integrator to build the PI interfaces and visualizations • Project lasted for 9 months • 1900 software development man hours • 7200 install man hours

  14. System Components Cont. RF Code Sensors / Readers • Sensors / Wireless “Tags”: • Simple to deploy • Operate at 433 MHz • Transmit every 10 seconds • Small form factor (2”w * 1.7”d * .3”h) • Long lithium cell battery life (3 to 4 yrs.) • Replaceable battery • CR2302 • Transmit range of 300+ ft. • Installation methods available • Push Pins • Adhesive • Magnetic • Screw

  15. System Components RF Code Reader Layout (Typical) • Readers - are similar in size to a residential wireless router • Security • Tags only transmit data • Readers only receive tag data. • No network entry point via reader. • POE reader every third row on avg. • 3 temp & 1 temp/humidity wireless sensors per rack every 3rd rack • 2 power redundant POE switch connected to the network per cell. • Approx. 12 readers per cell • Approx. 1200 sensors per cell

  16. Challenges Fears around wireless sensors in the DC? • Security • RF Interference • Frequency conflicts (licensing) Ease of Deployment & Maintenance • Zip ties are horrible… • Push pin fasteners are great… • Replacing batteries not great.. • Custom software had to be developed with wired sensor network • Containment areas • Devices that had unique air flow characteristics Environmental • Batteries in the DC • Shhhh…Don’t tell anyone but servers have batteries

  17. Software integration

  18. What is PI ? HPIT PI System factoids: Single application instance Collects and processes 1.5 million streams of data every min Analyzes over 30,000 data generating devices Annually stores 1.2TB of real-time data 300 different interfaces supporting all major protocols , i.e. Modbus, BACNET, SNMP, OPC etc.. 300,000 concurrent connections The PI System - is a real time “Big Data” historian capable of analyzing and storing millions of data streams • Industries that use PI: • Critical Facilities • Industrial manufacturing • Oil & Gas refineries • Data Centers • Utilities • Power plants

  19. Solution Architecture PI System Components – The software erector set The Visuals: PI Datalink PI ActiveView PI Process Book Mobile PI PI Coresite • The Server: • PI Archive Database (time series) • Asset Frame Work Database • Real-time interfaces The Analytics: Advanced Compute Engine

  20. Transformation of data to information PI System Architecture • Objects represent equipment & processes • PI and non-PI data related to objects • Intuitive search & browse for data • Quick replication of structures • Provides dimensions for BI Data Center Capacity Long-term archival in PI Server PI- Interface Nodes Real-time data collection Energy Trending Real-time energy cost by asset Power Gen & Distribution Building Automation Utility Meter Sensor Network Eco Pod ECS

  21. Solution Architecture Rack Thermal Sensor • Deployed 13,000 + sensors across (6) data centers & 100 remote compute spaces • ~9000 RFCode Sensors • ~4000 Wired Sensors • – RF Code Readers • – RF Code Zone Manager • – OSIsoft PI Interface servers • – PI OPC Interface • - PI RDBMS Interface OPC OPC RDBMS

  22. Visuals - Mobile CELL RCI Rack Temp Row Temps HP Private Cloud - HP Mobile PI Citrix Server hosts visualization – PI ProcessBook – PI ActiveView Rack/Row Based Screen Navigation Real Time Data Trends

  23. Measuring Performance

  24. Key Performance Indicator RCI High racks that are below 81 F RCI Low racks that are above 65 F RCI Index racks that are within 65 and 81 degrees F RCI The RCI is designed to be a measure of how effectively equipment racks are cooled and maintained within industry thermal guidelines and standards, where 100% means that all racks are cooled within the recommended temperatures RCI RCI

  25. Key Performance Indicator Cooling Improvement Results and Findings: 27% increase in RCI Index across all Data Centers We weren’t as good at the basics as we thought Measuring closer to the IT allows for a more aggressive Energy program Using PI Analytics allows us to identify optimization opportunities Need to incorporate real-time data into other tools i.e. CFD & DCIM application 99% 72% 27% Improvement Estimated Energy Savings 10 million kwh

  26. Thank you

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