Data Center Infrastructure Management and Automation Systems: an Evaluation Method

Transcription

1 Data Center Infrastructure Management and Automation Systems: an Evaluation Method Mauro Faccioni Filho FAZION Ltda Universidade do Sul de Santa Catarina UNISUL Florianópolis, SC, , Brasil Moacyr Franco Neto FAZION Ltda Universidade Federal de Santa Catarina UFSC - PPGEAS Florianópolis, SC, , Brasil moacyr@fazion.com.br Abstract Information technology is growing faster then ever and new challenges appear everyday. One of these challenges is data storage and processing, and data centers have a crucial role in this scenario. But as data centers get bigger, more energy is necessary and availability is fundamental. Considering worries about energy costs and availability management, new systems of data center infrastructure automation are under development. This paper presents a proposal for a method to evaluate hardware and software platforms that compose these systems, called DCIM Data Center Infrastructure Management. I. INTRODUCTION Data centers are getting crucial importance nowadays due to the increasing use of information technology systems for all commercial, industrial and even domestic activities. Information systems need immense data bases that are growing every moment. Information systems need applications running all the time and as fast as possible. Information systems can not fail. A few years ago the concept of a data center was very different of the one we have today. In the past there was not a really dedicated place to host servers, switches and all devices that run the computer network, and these equipments were located in common adapted rooms as possible. From the boost of internet and all related services coming in recent years (like cloud computing, virtualization, parallel programming), exigencies about uptime and service level agreements are in all business contracts. To deal with these requirements new standards came [1]-[3],[16] and are conducting a very strong industrial market branch on data center project, construction and maintenance. Researches [4] show that new data centers in 2012 will consume investments around 2.15 billion dollars in Brazil, 9.2 billion in USA, 3.1 billion in China and so on. Besides this, new data centers will represent an increase of about 50% more electrical energy than the year before [4]. This dramatic energy scenario is pushing several new researches that look for economy, management and control. Following the improvement of data center project and construction techniques, specific automation systems began to be developed focusing on how to monitor and manage the data center behavior, looking at the same time on high quality services and on maximum power efficiency. These automation systems are called Data Center Infrastructure Management systems, abbreviated as DCIM [5]. Following sections will present the concepts of DCIM systems, what are their main characteristics and how they differ from other BAS/BMS (Building Automation/ Management Systems). As DCIM are very new platforms with varied industrial solutions and diverse characteristics, and considering their importance for the whole information technology ecosystem, a proposal for a new Evaluation Method is presented and sample results are showed. II. DCIM CONCEPTS The main objective of a Data Center Infrastructure Management system (DCIM) is to allow managers to get real time information from the data center environment, how is its resources usage, and how are the critical points to take care. With information at hands, managers will be able to perform actions directly on the infrastructure components, simulate work, analyze and plan changes when appropriate. Applying a DCIM platform on the data center, resources management is optimized, devices performance is /ISCA CAINE/Novermber 2012

2 improved, energy is saved, operational costs are reduced and next steps of growing are previewed. DCIM can be understood at the same time as a technical and as a business tool. It is a technical tool because it permits monitoring and analysis of physical infrastructure, and also interfering on it by actuators. It is a business tool because it is oriented to cost reduction, management and general performance improvement. From the technical point of view it is an integrated hardware and software platform, implanted deeply within the data center structure to optimize its operation. For this reason it is considered an infrastructure management system. It may be a junction of several different platforms integrated, or just a single platform developed for this proposal. Generally speaking it combines different technologies for: Infrastructure environment monitoring; Pathways and area management; Operational work planning; Energy efficiency; General performance optimization; Physical security. DCIM platforms are evolving from just a few years and are a new branching of automation systems. Its market is new, strong and high specialized. There is not a leader product and no standards yet. Around just 1% of penetration in data centers in 2012, DCIM systems are expected to be present in almost 60% of all data centers in 2015, accordingly to [6]. III. DCIM OBJECTIVES Three are the keywords to define DCIM objectives and why they are so necessary: availability, manageability and economy. Availability means that the data center is working appropriately every time when any service is demanded from it. But sometimes it may not occur, and all efforts are done to get so much uptime as possible. The Uptime Institute defines standards [7], [8] to orient technical solutions and acceptable levels of downtime. DCIM systems will help on data center availability considering, for instance, the impact of new devices installation and if the power circuits will support them, or if there is enough space within the cabinets. Other questions to consider are as: which are the cabinets that have electrical circuits with enough load, and how to connect equipments on it? Any circuit is possible to use or is there some kind of balancing to take care? Is there any possibility to have a crash if one new device is connected? Where are the critical points of fail on heat generation and how air conditioning systems are working on them? Are there electrical panels overloaded or with some kind of risk? Are there intermittent or minor fails, not clearly perceivable, that could suddenly interrupt the data center availability? Manageability means the capability of managers to administrate the complex data center operations and maintenance. To maintain the data center available, all its subsystems are working in parallel and are interdependent, and this is an additional difficulty because managers must look on, for instance, so different aspects as staff, energy, costs and security. DCIM systems will help management by organizing staff responsibilities, controlling permission accesses and/or actuation, creating forms and reports, showing plots online about all data collected from the field, and several other information that are important to have an in deep view of the data center. DCIM will help managers on creating and sending service orders (for maintenance or new installations), defining where are the best ways and places to locate new devices or relocate existing ones, distributing logins and passwords for staff or visitors access, doing continuous verifications of PUE Power Usage Effectiveness [9] which defines the energy efficiency of the data center, establishing maintenance routines and getting feedback from them, besides several other regular management processes that are usual or specific for each data center. Economy is the third keyword and defines how to reduce continuously the cost of data center operation and growth. The Power Usage Effectiveness (PUE) cited before has become one of the main index numbers to show how is the data center general energy efficiency. DCIM systems can measure electrical power consumption of all circuits and then calculate the rate between general data center electrical power consumption and IT (information technology) devices consumption. But, beyond only measuring and calculating this information, DCIM can also help by analyzing refrigeration at all important locations (as corridors and cabinets) and comparing them to the standards limits [10], dispatching warnings and alarms when overloads were detected. Using automation, even a staff reduction is possible, concentrating efforts only on very specialized proactive jobs and not on mere reactive tasks. As data center construction and operation is an expensive charge, space is disputed within it and IT devices are the focus. DCIM will help on reducing location mistakes, simulating and defining the best places according to heat generation and energy consumption, optimizing the whole data center distribution and organization. DCIM systems (depending on the features of each product) can model and simulate environments, simulate electrical circuits and loads, dynamically draw electrical diagrams with their loads, plan physical growing and new cabinets installation, and several other simulations to help information technology managers on decision taking

3 processes, aiming cost reduction and/or availability. IV. DCIM CHARACTERISTICS There are a series of parameters to monitor and manage within the data center environment, such as temperature, humidity and smoke (within the rooms, cabinets and power panels), and leakage (under the raised floor, below the equipments like air conditioning units, uninterruptible power systems, generators and the like). Electrical energy is another parameter to be verified on main power distribution units, circuits and loads. Use of space is another, and how is the distribution of cabinets and devices on the plan, and specially the servers and other equipments within the racks/cabinets (bayface of racks). Security systems need access control for main doors and entrances, and also for each cabinet if necessary. Images from closed circuit television (CCTV) will enhance security associated to the DCIM platform. Analytical tools and simulators are important features of DCIM systems. These tools are in truth a set of different tools that must be shown in a unique interface, aiming ergonomics and easy of use. The main tools to be cited are charts and diagrams showing real time data, reports, spread sheets, two-dimension and three-dimension (2D, 3D) plans of all data center rooms, where the IT managers could see what is happening or just taking views to maintain visual control. On the other hand the simulation tools will help managers trying a preview of the future and then helping them on new plans. These tools are, citing only some of the most important, placement simulators, new arrangement of internal cabinets location views, thermographs (showing on 2D or even 3D interface color scales), electrical diagrams with synoptical buttons, reports showing historical events and trends, intelligent tools dispatching warnings and alarms when parameters are touching boundary limits. Power efficiency and cost reduction tools complete the minimum set of tools that are present in a DCIM platform. These tools control the energy consumption of each device and circuit. They can monitor and operate loads, balance circuit phases and also switch them if necessary. Having these measurements at hands, managers can decide, for instance, about devices location based on consumption at each rack or heat generation in certain areas of the data room. Data centers are now considering DCIM installation from the beginning to enhance efficiency and maintenance cost reduction [11],[12]. Some features are yet under research and development to implement on future versions of DCIM systems. These features are web based software, mobile access, and parallel monitoring of data centers from several different sites. Other challenge is the integration of DCIM to legacy software (like BMS and BAS) already installed. But as a platform, DCIM is a dynamic system which must grow and adapt itself to the new data centers under construction and development around the world. V. METHOD TO EVALUATE DCIM SYSTEMS DCIM platforms have not yet an assessment model to verify their qualities and how extents are their capabilities. Some research institutes are trying to fill this gap creating DCIM evaluation frameworks [13]. For sure these frameworks are valid and good for market choice, but as they are very focused on the commercial appeal, they can not assure technical capabilities or the level of quality development of each platform. There are several standards and quality models with guidelines to evaluate processes and products, as ISO/IEC [14] and CMMI (Capability Maturity Model Integration) [15]. Each of them presents evaluation models, either analytic or based on best practices. Here is proposed a method based on these standard guidelines and also on data center infrastructure requirements, as showed at [1],[16]. Table I shows these basic requirements. TABLE I DATA CENTER INFRASTRUCTURE REQUIREMENTS Requirements 1 Availability 2- Power efficiency 3- Low cost Infrastructure 4- Security 5- Monitoring Taking into account these requirements and the quality evaluation problem, here is proposed a method to analyze the DCIM quality development. The analysis considers five criteria: Data Criterion, Automation Criterion, Diagnosis Criterion, Interface Criterion, Management Criterion. These criteria cover aspects of all areas that a DCIM platform must support. Data Criterion is related to the collecting and storage of information from the data center environment as a whole. Automation Criterion considers how DCIM interacts with all data center subsystems in terms of automatic controls, and also how it dialogs with legacy software, if existent. Diagnosis Criterion considers the capacity of DCIM to analyze and create real time diagnostics. Interface Criterion defines the way that DCIM can show to users the information from data center, diagnostic results and tools for actuation (buttons, forms, etc). Management Criterion considers DCIM capabilities related to planning, simulation and intelligence, helping

4 managers on day to day and future management of the data center. The evaluation of each criterion is defined by a table filled with several topics that constitute its specific features. For each topic the model proposed considers three levels of Quality, as shown at Table II. TABLE II LEVELS OF QUALITY Level (r i ) Description 0 Feature does not meet the requirement 1 Feature partially meets the requirement 2 Feature meets the requirement Each DCIM criterion development Quality is then defined by the mean of all level topics, according to equation (1), where n is the number of topics of the Criterion, l i is the weight of the requirement, and r i is the level of its Quality. Each Criterion has requirements for each feature, which are detailed on specific forms, as shown below (Tables III to VII). However, it is important to notice that these forms are a proposal and do not exhaust all possibilities. New requirements and features can be defined and then improve the forms and evaluation results. 1. Data Criterion The focus of this Criterion is the assessment of how DCIM is collecting and storing information from data center environment. Also, it analyzes the qualitative and quantitative scope of these data. Table III shows the evaluation requirements shared on different topics. 2. Automation Criterion Automation Criterion considers the automatic systems related to the several subsystems present in a data center, like cooling, security, power and so on. It defines requirements for control and interaction between these subsystems, and also with legacy software, if existent. Table IV shows the automation criterion evaluation requirements and topics. 3. Diagnosis Criterion The purpose of this Criterion is the evaluation of DCIM diagnosis capabilities, considering, for instance, analysis of points of risk or fail, critical areas within the data center, and how to manage them. Table V shows the diagnosis (1) criterion evaluation requirements and topics. TABLE III DATA CRITERION EVALUATION REQUIREMENTS 1 Environmental Data Monitoring 1.1 DCIM collects and stores power data 1.2 DCIM collects and stores humidity data 1.3 DCIM collects and stores temperature data 1.4 DCIM detects smoke and stores data 1.5 DCIM detects fluid flow and stores data 1.6 DCIM detects leakage and stores data 1.7 DCIM collects and stores CCTV Images 1.8 DCIM registers and stores information from data center devices and components 1.9 DCIM collects and stores Access control data 2 Monitoring Scope 2.1 DCIM monitors each Rack/cabinet unit 2.2 DCIM monitors each Room 2.3 Real time monitoring (online) 3 Interval between data collects 3.1 Fraction of seconds 3.2 Fraction of minutes 3.3 Fraction of hours TABLE IV AUTOMATION CRITERION EVALUATION REQUIREMENTS 1 Subsystems integration 1.1 Automation is integrated to data monitoring, alerting tools, security access control and CCTV. 1.2 Access control (rooms and cabinets) and CCTV are integrated. 2 Heterogeneous platforms. 2.1 Heterogeneous hardware platforms are integrated in a unique console 2.2 Hardware using different open protocols, as Modbus, BACnet, CAN, SMNP, can be integrated. 3 Limits 3.1 Limits can be set for predictive alarms/warning. 3.2 Different limits for different devices can be set for predictive alarms/warning on the same platform. 4 Control 4.1 In just one control network all subsystems are integrated. 5 Operation 5.1 DCIM operates contingency apparatus in case of predictive alarming. 5.2 DCIM controls and operates heterogeneous devices, even if they are from different vendors. TABLE V DIAGNOSIS CRITERION EVALUATION REQUIREMENTS 1 Real time management of fails 1.1 DCIM shows fail events in real time. 2 Infrastructure and environment management 2.1 It is able to verify connection between devices 3 Environment analysis 3.1 DCIM shows all environment events in consolidated and synthesized reports. 3.2 DCIM shows all power circuits and loads in consolidated and synthesized reports.

5 3.3 DCIM shows all air conditioning events in consolidated and synthesized reports. 3.4 DCIM shows temperature values in two dimensional maps (thermographs). 4 Diagnosis 4.1 DCIM can scanner and show data center fails and/or overload status. 4.2 DCIM shows consolidated reports from critical points and probability of fails. 4.3 DCIM has maintenance routine tools. 4.4 DCIM has automatic dispatch of service orders. 4. Interface Criterion This criterion is focused on the presentation of all information and diagnosis operated by the DCIM platform. It analyses how this information is showed and formatted, and also the presentation of results and tools for actuation (buttons, forms, etc). Table VI shows the interface criterion evaluation requirements and topics. 5. Management Criterion This criterion analyses the DCIM Quality to deal with planning, simulation and intelligence tools, aiming the management of day to day and future of the data center. Intrinsically related to all other criteria, it may coordinate the evolution and growth of the data center itself. Table VII shows the management criterion evaluation requirements and topics. 2.2 Information from the environment allows location and/or relocation of devices accordingly to power and cooling availability. 3 Simulators 3.1 Data center growth simulator tools. 3.2 Power availability simulators. 3.3 Heat simulators through thermographs. 4 Modularity 4.1 DCIM has a modular basis, allowing flexibility and dynamical growth. Considering these five criteria, any DCIM platform can be analyzed. Each one of the criteria has a final value, calculated by the equation (1). Comparisons between different products can be done criterion by criterion, depending on what is important for a specific use or application. The final Quality evaluation for a DCIM platform will be given by the sum of each one of the values obtained. Equation (2) shows the calculus for a DCIM Quality general level. VI. RESULTS APPLYING THE METHOD (2) TABLE VI INTERFACE CRITERION EVALUATION REQUIREMENTS Ways to access and view information 1.1 Local area network access only 1.2 Web access 1.3 Mobile access (via tablets and cell phones) 2 Presentation layout 2.1 Three dimensional data center plan. 2.2 Two dimensional data center plan. 2.3 All information in charts 2.4 All information in reports 3 Alerts 3.1 Buzzer alarms 3.2 s alarms 3.3 SMS alarms 4 Diverse information 4.1 Data from other systems are integrated in the DCIM console. TABLE VII MANAGEMENT CRITERION EVALUATION REQUIREMENTS 1 Metrics 1.1 Environment parameters history of events shown in report and charts. 1.2 Rooms and cabinets security access history of events 2 Planning 2.1 Consolidated power data permits PUE (Power Usage Effectiveness) calculus. The method was applied to a DCIM platform called DataFaz [5], and to a competing product (called here DCIM2, company name omitted). The DataFaz DCIM was developed by the authors and launched in It is a result from two years of research and is used in several Brazilian and multinational customers. Applying, first of all, the Data Criterion (Table III) and considering the weight l i equal to one, the results are 2.00 and 1.60 for DataFaz and DCIM2 respectively. The results for Automation Criterion are 1.89 and 1.50 respectively. The results for Diagnosis Criterion are 1.70 and The results for Interface Criterion are 2.00 and The results for Management Criterion are 1.38 and These results show that DataFaz has a better level of Quality then DCIM2 at Data, Interface and Automation Criteria, whereas DCIM2 is better at Management and Diagnosis Criteria. Considering the general value of Quality, according to equation (2), DataFaz has a Quality level 8.96, and DCIM2 has Quality level Figure 1 shows a chart with both results plotted on five axis, where DataFaz is represented by the continuous line and DCIM2 by the dashed line. For sure the comparison here is relative and only for demonstrative reasons, expecting to show the model capabilities. The model proposed necessarily must have

6 more detailed requirements in each of the criteria, and developers from academic and commercial background can help enhancing the table method, either creating and detailing requirements or applying different weights for these requirements, represented by l i at equation (1). VII. CONCLUSIONS Data centers became the core of information technology and nowadays are top consumers of energy, comparable to big manufacture plants. Due to the importance of data for all activities, data center availability is the focal point. Automation systems dedicated to data center availability, economy and management are emerging forces and will represent expressive part of all new data center installations. These automation systems, called Data Center Infrastructure Management DCIM, do not meet yet a standard or a general pattern. Different products are launched everyday to the market and there is not a technical comparison basis for choosing. Here is presented a proposal for a DCIM Evaluation Method, which is based on several feature requirements, both for hardware and software. Five are the criteria proposed to analyze: data, automation, management, interface and diagnosis. The method is dynamical and new evaluation requirements can be added to it anytime, as a way to improve it regularly. Two existent commercial platforms were analyzed in this paper and results were shown as a sample of the method possibilities. Future work will show a survey of commercial DCIM products, submitted to this Evaluation Method. Data REFERENCES [1] Cabeamento estruturado para edifícios comerciais e data centers, ABNT NBR 14565/2011, [2] Telecommunications Infrastructure Standard for Data Centers, ANSI/TIA 942, [3] Information technology Generic cabling systems for data centers, ISO/IEC 24764, [4] DatacenterDynamics Global Industry Census 2011 [Online]. Available: [5] M. Faccioni Filho, Plataformas online para gestão e monitoramento da infraestrutura de data centers, in IV Congresso RTI Data Centers 2012, São Paulo, SP, [6] D. J. Cappuccio, DCIM: Going Beyond IT, Gartner Inc, Stamford, CT, USA, G , March [7] Data Center Site Infrastructure Tier Standard: Topology, Uptime Institute, LLC, [8] Data Center Site Infrastructure Tier Standard: Operational Sustainability, Uptime Institute, LLC, [9] V. Avelar, Guidance for Calculation of Efficiency (PUE) in Data Centers, Schneider Electric, Rueil Malmaison, France, White Paper 158 Rev 2, [10] Thermal Guidelines for Data Processing Environments, Second Edition, ASHRAE - American Society of Heating, Refrigerating and Air-Conditioning Engineers, August 3, [11] The Promises, Challenges and Imperatives of Data Center Infrastructure Management, Emerson Electric Co, Columbus, OH, USA, 0810-DCIM-;MPP-EN, [12] An Introduction to Data Center Infrastructure Management, Raritan Inc, Capelle aan den Ijssel, The Netherlands2010. [13] K. Broderick, IDC MarketScape: Worldwide Datacenter Infrastructure Management (DCIM) 2011 Vendor Analysis, IDC, Framingham, MA, USA, IDC# Volume 1, [14] Information technology -- Process assessment, ISO/IEC 15504, [15] Software Engineering Institute. CMMI (Capability Maturity Model Integration). Available: [16] Data Center Design and Implementation Best Practices, ANSI/BICSI , ,00 Management 1,00 Automation 0,00 Interface Diagnosis Fig. 1. Results for two different platforms applying the DCIM Evaluation Method. (DataFaz - continuous line; DCIM2 - dashed line.)