Presented by: Angela Wilson Tim Wilson

Transcription

1 Presented by: Angela Wilson Tim Wilson

2 What is DCIM? Data Center Infrastructure Management (DCIM): Monitors, measures, manages and/or controls data center performance, utilization and energy consumption of: ALL IT-related equipment: Computing resources (such as servers, storage and network switches) Infrastructure components (power components, such as PDUs and cooling components such as CRACs)

3 What is DCIM? Basic DCIM Components and functions include: A Single Repository Asset Discovery & Asset Tracking Visualization Provisioning New Equipment Real-time Data Collection Process-Driven Structure Capacity Planning Reporting Holistic Approach An Effective Bridge Between IT & Facilities

4 Data Centers: Before and Now Data Center Size + Density Data center consolidations Mergers and acquisitions Virtualizations lead to increased compute demand Exponential increase for storage

5 Data Center Complexity Increased network complexity 10 and 40 Gigabit Ethernet SAN over Fibre Channel + Ethernet InfiniBand Increased power demands Increased heat loads Hot and cold isle containments Increased thermal envelopes

6 Data Center: Before and Now Ever Increasing Data Center Size, Density and Complexity Compounded Pain Points

7 Common Pain Points within Data Centers Unable to locate assets Unable to know what is connected to what (manage relationships and dependencies ) Unable to find available resources (rack space, power, cooling, network, IP addresses, etc) Unable to do accurate capacity planning Unable to manage change and enforce best practices and processes Unable to comply with internal and external regulatory audits

8 Tools Domains What does an Enterprise Data Center look like? Facilities Networking Systems Raised Floor, UPS, PDU/RPP, Rack PDUs CRACs, Probes Structured Cabling, LAN, SAN, WAN Mainframe, Servers, VMs, Storage, Apps Asset Tracking: Spreadsheets, Homegrown DBs Floor Plan: AutoCAD, Visio Monitoring: Raritan, Sitescan, Foreseer, Environet, etc. Cable/Net Tracking: Spreadsheets, Homegrown DBs Configuration: CiscoWorks, etc. Monitoring: HP OpenView, IBM Tivoli Asset Tracking: Spreadsheets, Homegrown DBs CMDB: HP OpenView, BMC BladeLogic, etc. Monitoring: HP Insight Manager, IBM Director

9 Manual Processes Labor-intensive processes Slow, time-consuming Add New Device Rack Space Unreliable Prone to conflict and errors Dispatch Personnel to DC Cabling Patch Panels Costly Unable to meet SLAs Query Available Resources Network or SAN Switches IP Address Space Power Sockets + Capacity Problematic

10 Domains How is the Data Center Operations Model Evolving? Data Center Operations Executing Work Orders Racking and Stacking Power Rack Connectivity Fiber and Copper Cable Patching Raised Floor, UPS, PDU/RPP, Rack PDUs CRACs, Probes Structured Cabling, LAN, SAN, WAN Mainframe, Servers, VMs, Storage, Apps Facilities Networking Systems

11 What is the solution? Data Center Infrastructure Management (DCIM) Systems

12 The Solution: DCIM S o l u t i o n Automated Intelligent Powerful Data Center Infrastructure Management (DCIM) D o m a i n Facilities Networking Servers/Hosts Space Heat Power Cabling VLANS IP Subnets Stand Alone Blade Virtual Apps A c t i v i t y Asset Tracking Assignments Connections Change Management

13 Where is the Industry Heading?

14 Gartner DCIM Model Sensors Database Input Process Output Other system feeds Trend analysis (or more ) Source: DCIM, New Tools to Monitor, Manage and control Power Jay Pultz, Gartner Data Center Conference, December 2010

15 Gartner DCIM Model Evolution

16 Gartner s Trending Forecast DCIM tools and processes will become mainstream in data centers, growing from 1% penetration in 2010 to 60% in % Source: Gartner Analysis Report by David Cappuccio, March 29, %

17 The 451Group DCIM Model

18 IDC Research Report "DCIM will grow to shape datacenter facilities and IT operations for years to come. DCIM's combined software and services revenue will grow from $179.4 million in 2010 to reach $557.7 million by Source: IDC, Katherine Broderick, Senior Research Analyst, 2011

19 Picture of a DCIM Solution Intelligent Capacity Management Accurate Asset Management Available Power, Space and Networking Cooling Search, Place and Reserve All Data Center Physical Resources & Logical Connections Maintenance and Lease Information Intelligent Rack Asset Strip Change Management Visualization Workflow for Move, Add and Change Approvals and Status API to third party ticketing system Dashboard Floor Plans Rack and Row Elevations Power Chain Network and Power Ports

20 What is a true DCIM View? Beyond Asset Tracking Enable visualization, tracking and management of all data center assets as well as their physical and logical relationships including structured cable plant, networks, power infrastructure, and cooling. A Holistic Approach Bridge the organizational and functional gaps across all domains including facilities, networking, and systems domains. A Single Pane of Glass Used by all data center domains and groups regardless of hierarchy including managers, system administrators, and technicians. A Single Repository A single database to house all data from across all data centers and sites. Process Driven A change management system by which you can provision new systems and all their related physical and logical resources. DCIM becomes the gate through which you enter the data center

21 Green Data Center Initiative: DCIM Model Energy Efficiency Automate Predictive Provisioning Informed Decision Trending Analysis Recommended Intelligent Management Change Management Provisioning Process & Visualization Visualization of Physical & Logical Configuration Servers, Storage & Network Devices Operational Management Data Collection Power + Environmental + Space Tracking & Measurement

22 Energy Efficiency Issues Data Center Managers must utilize energy more efficiently 65% report they have facility capacity problems now or will experience them within 18 months with 15% saying they are completely capped out (Gartner) 84% are running energy-inefficient data centers with one-third having an efficiency rating below 50% (Gartner) Data Centers use more than 61 billion kwh of electricity per year representing 1.5% of all US Energy Consumption (DOE) DOE is expecting energy usage to grow more than 12% per year (DOE)

23 Green IT Initiatives National Data Center Efficiency Information Program Joint Venture with: Department of Energy (DOE Industrial Technologies Program Save Energy Now Initiative) DOE Federal Energy Management Program (FEMP) EPA Energy Star Program Program consists of Several industry Stakeholders: 7x24 Exchange AFCOM American Society of Heating, Refrigeration, and Air Conditioning (ASHRAE) Critical Facilities Roundtable Information Technology Industry Council (ITIC) Silicon Valley Leadership Group The Green Grid Association The Uptime Institute

24 DOE Initiatives Need better energy management practices & best available technology to process digital information Deliver & condition electrical power to computers energy efficient servers Remove heat rejected from data center information technology (IT) equipment Report to Congress EPA stated that if DOE & EPA initiatives are adopted that energy efficiency of Data Centers infrastructure & IT equipment could be improved by as much as 70% EPA stated that a 10% savings of total energy usage would equate to a savings of 10.7 billion kilowatt hours per year Equivalent to the electricity consumed by one million US Households and valued at $740 million

25 DOE Program Overview Consensus energy efficiency metrics & benchmarking 1. Consistent industry measurement protocols & metrics to define energy performance 2. PUE = Power Usage Effectiveness = Total Facility Power/IT Equipment Power 3. DCiE (Data Center Infrastructure Efficiency) Energy Savings tools & training 1. DOE Save Energy Now DC Pro Tool Suite 2. EPA Energy Star Portfolio Manager Certification of data center efficiency experts Equipment performance specification and labeling 1. Energy Star specs for Enterprise Servers 2. Specs for IT Equipment a. Data Storage b. Networking equipment

26 Case Study Department of Energy (Los Alamos Labs) Challenges: High Performance Computing Division planning expansion Lack of awareness of current state prior to major infrastructure upgrades New super Computer Ceilo install scheduled(emits 120degree exhaust runs at 54kW per rack) Needed a complete picture of current power usage (IT and Facility devices) Needed a capacity planning strategy for growth

27 Case Study Department of Energy (Los Alamos Labs) Solutions & Results: Installed a DCiM system Power Metering sensors installed on substations, distribution switchboards, and rotary uninterruptible supplies Line to line voltage, current, percent load, power factor, and power on each phase was not being measured in real time Total Facility Power Usage IT Power Consumption Total mechanical power consumption Temperature, humidity, and air flow readings from wireless devices Real time computations Historical data and trending Alarm notifications

28 Case Study Department of Energy (Los Alamos Labs) Benefits of installing a DCIM system: 1. Future planning for high-density exascale computing 2. Validation of Computational Fluid Dynamic (CFD) modeling software 3. Historical trending & reporting can be exported into other programs for data analysis 4. Site preparation, capacity planning, and maintenance schedules 5. Real time monitoring of both facility & IT devices 6. Alarm notification to prevent equipment failure and/or damage 7. Reduction in energy consumption and loss

29 Case Study ebay Challenges: With compute loads and operating costs on the rise, ebay created and began executing a four-year data center plan with an ambitious goal: To Cut power costs in HALF To Double compute performance To Gain greater operational agility and increased reliability Note: Reliability was imperative Any downtime would cost ebay approximately $2,000 a Second

30 Case Study ebay Results: Installing a DCIM system Developed a model that made IT operations both highly reliable and 50% less expensive to operate than the data centers they are de-commissioning. In addition to minimizing faults & reducing operating costs, ebay s South Jordan, Utah facility has achieved the U.S. Green Building Council s Leadership in Energy & Environmental Design (LEED) Gold Ranking. Five additional key designs were implemented complimenting the information gathered from their DCIM tool Hot Aisle Containment 400 V Distribution to each Cabinet Detailed Server Power Instrumentation Granular Temperature Instrumentation Overhead Power Distribution Busway

31 Case Study University of Phoenix Challenges: Online college enrollment has more than doubled in 5 years creating a need to build a new data center to handle the capacity Critical need to create and maintain an adaptive cooling & power infrastructure for mission critical data center serving more than 300,000 students worldwide Facility would need to handle more than 1000 servers in their 10,000 sq foot headquartered data center Must be able to proactively manage the data center environment and increase data center efficiencies Imperative that a monitoring & management tool be integrated to handle the volume of assets and health measurement of mission critical facilities equipment

32 Case Study University of Phoenix Solution: Install a DCIM system Results: Deployed a flexible & scalable power and cooling architecture that ensures the data center can support future business & technology requirements. Enhanced data center availability through multiple active power and cooling distribution paths with redundant components that are concurrently maintainable. Increased understanding of the current state of critical IT infrastructure through proactive monitoring and management. Gained real-time visibility into available power and cooling capacity. Reduced risk of technology deployment by enabling ability to model impact of technology changes on data center infrastructure. Provided a top-down visualization of the data center with a more detailed and sophisticated tracking of assets.

33 Benefits of a DCIM Model Reduce Operational Expenses Automate manual and time-consuming processes Eliminate the need to query available resources manually by sending technicians in the data center Eliminate manual effort to trace and troubleshoot circuits and devices Reduce and/or Defer Capital Expenses Through better capacity planning, maximize utilization of existing resources By better provisioning and balancing of 3-phase power, increase utilization of power systems Identify unused structured cabling to defer need to install new cable runs Improve Performance and Response Time Reduce time to respond to customer requests by eliminating several manual cycles Maintain True Lights-out Remote Data centers

34 Benefits of a DCIM Model (contd.) Achieve Green Data center Initiatives By better measuring and monitoring energy consumption you will be able to reduce energy and related costs Improve PUE/DCiE metrics Make internal customers accountable for their energy consumption Easily and frequently run CFD models and analysis using real-time data Instantaneous Reporting Executive and management reports Forecasting and trending

35 The Case for Return on Investment Automate Manual Processes Reduce Provisioning Cycle Reduce Number of Hands Increase Provisioning Accuracy ROI Case Profile Data Center Size: 100 Cabinets Average Weekly Change 3 Man-hour Loaded Cost $100/hr

36 The ROI Case. How does it all add up? Staff-hours Effort for Typical Change Before After Savings Change Request Server Configuration Definition Determine Availability of Physical Resources - Rack Power Cabling Network Install Server and Connections % Re-work (due to inaccurate documentation) Project Management and Meetings Totals per new server provisioned % Savings 52%

37 The ROI Case. How does it all add up? Savings per 1 Typical Change Total Hourly Staff Savings per Typical Change 3.57 Average Hourly Staff Cost $100 Savings per Change $357 Savings based on Change Frequency Changes Savings - Weekly Changes 3 $1,071 - Monthly Changes 13 $4,641 - Annual Changes 156 $55,692 ROI Calculations Data Center Size (cabinets) 100 Software, Maintenance + Implementation $69,640 Annual Savings $55,692 Payback Period (in years) 1.41

38 Statistics to Consider Of the 11.8 million servers in the US as of 2007 most were running at 15% capacity or less (Computer World). Over 50% of data centers expected to be out of space by the end of (IDC) Close to 1/5 of the servers in a data center are longer used and should be removed. (Computer Associates). The average data centers are highly energy inefficient. For every 100 watts these data centers consume, only 2.5 watts result in useful computing. (Rocky Mountain Institute) The volume growth of IT infrastructure will exceed the available data center floor space for most organizations. By the end of 2011, more than 70% of US enterprise data centers faced tangible disruptions related to energy consumption, floor space and/or costs. (Gartner) From Jan to Dec of 08, Sprint retired 127 applications, decommissioned or redeployed more than 2,230 servers and freed up 291,042 gigabytes of storage. This translated into $28 million of redeployment assets, a $20 million reduction in operating costs and a reduction of data center-related carbon emissions by 10,450 metric tons.

39 Future Trends The adoption of modular, hardware & software enabled, data center technology will evolve from the early adopter stages to a more main stream solutions for enterprises, governments and service providers. Requirements for robust DCIM software will become a key driver of data center strategies. Data Center consolidations will continue with a move toward higher densities and improved overall utilization. More tiering of enterprise applications, and associated infrastructure service level and resiliency requirements, will drive growth in the colocation and data center outsourcing markets. Capital constraints for new data center investments will drive the need for more cost effective and efficient solutions. Physical and logical security requirements will continue to play an important role in data center decisions.

40 Q & A Angela Wilson Vice President Predictive Technology, Inc 9375 G Court Omaha, NE awilson@ptisolutions.com