A Model For Monitoring And Control Of Data Center Entrance And Exit Scenario

A Model For Monitoring And Control Of Data Center Entrance And Exit Scenario
A Model For Monitoring And Control Of Data Center Entrance And Exit Scenario
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Chapter1
 Introduction to Data Center

1-1-    Data Center Basics
The need for high availability did not originate with the Internet or e-commerce. It has existed for thousands of years. Also With the recent explosive growth of the Internet and our dependence on information systems, high availability has taken on a new meaning and importance. Businesses and consumers are turning to the Internet for purchasing goods and services. People conduct business anytime from their computer. They expect to buy clothes at 2 a.m. on the Web and expect the site to function properly, without problem or delay, from the first click to the last. If the Web site is slow or unavailable, they will click away to a competitor’s site.
On the other hand every Downtime can make big financial damages to companies. Some causes of Downtime are made by process and people which are called unplanned Downtime. While other planned tasks that lead to host or application outage are scheduled activities such as application or operating system upgrades, adding patches, hardware changes, and so forth.
Therefore unplanned service outages are expensive and are caused by hardware and software failures, human errors, Internet viruses and attacks, natural disasters, and human-caused crises.
 
Figure 1-1 Causes of downtime
Figure 1-1 shows, approximately 70% of outages are about unplanned downtime whereas rest of outages is made by planned downtime.
Data Center is created for solving these problems, which should have some properties for helping to service availability:
•    Reliability, Reliability represents the probability of a component or system not encountering any failures over a time span.
•    Resiliency, Resiliency is the property of a component that allows it to continue with full or partial functionality after one or more faults.
•    Availability, Availability measures the ability of a system or group of systems (cluster) to keep an application or service up and running.
•    Serviceability, Serviceability is the probability of a service being completed within a given time window. If a system has a serviceability of 0.98 for 3 hours, then there is a 98 percent probability that the service will be completed within 3 hours. In an ideal situation, systems can be serviced without any interruption of user support.
•    Fault-tolerant systems, these are systems that have redundant hardware components and can operate in the presence of individual component failures.
•    High availability clusters, These clusters consist of two or more nodes with a number of external interconnections such as shared disks and private heartbeat network and are managed by special software with a goal of providing uninterrupted service despite node failures. If a node running one or more applications fails, one or more of the remaining nodes in the HA cluster take over applications from the failed server. Ideally, the only downtime is the time it takes to stop the application on the failed host and start it on another. In a HA cluster, the focus for availability changes from hardware components or servers to applications. It does not matter which server is running the application. What matters is that the application is running and available for clients and users.
•    High-performance clusters (parallel computing clusters), each cluster has a group of computers, tied together to work at the same time on a problem, not as backups to each other.
•    Disaster recovery, Disaster, in the context of online applications, is an extended period of outage of mission-critical service or data caused by events such as fire and terrorist attacks that damage the entire facility. A DR solution requires a remote, mirrored site where business and mission-critical applications can be started within a reasonable period of time after the destruction of the primary site.


Refrences 
[1]  Cisco Systems, “Cisco Data Center Infrastructure 2.5 Design Guide”. Cisco Systems, Inc.
170 West Tasman Drive San Jose, CA 95134-1706 USA, 2007.
[2]  A.K.   Talukder,  H.A.  Prahalad,  “Security  &  scalability  architecture  for  next  generation
internet services “, IEEE Inc. page(s): 1 – 4, 2009.
[3]  V.Wheatman, “Integrating Physical and Information Security”, July 1, 2009.
[4]  E.Roback,“ Logical Access Control”, DRAFT Handbook, part of  NIST,1990.
[5]  R.Snevely,  “Enterprise  Data Center  Design  and Methodology”,  Sun Microsystems,  Inc.
901 San Antonio Road Palo Alto, CA 94303-4900 USA, 2001.
[6]  M.Kutare,  G.  Eisenhauer  “Monalytics:  Online  Monitoring  and  Analytics  for  Managing
Large Scale Data Centers”, ICAC, USA, 2010.
[7]  F. Li,  P. Zhang N. Bhatt  “Next Generation Monitoring  and Control Functions  for Future
Control Centers “, IEEE, 2008.
[8]  G.  J.  PALJAK,  I.  SZOMBATH,  I.  KOCSIS,  T.  KOVÁCSHÁZY,  A.  PATARICZA,
“Model-Based control of  IT  Infrastructures”,  International Carpathian Control Conference,
ICCC, Eger, Hungary May 26-29, 2010.
[9]  M. Mahadavi  ,” Data Center Operations  Security  in  the E&P  Industry”,  cyrusOne,Digital
Energy 2005.
[10]  K.Jayaswal: “Administering Data Centers: Servers, Storage, and Voice over IP” .chapter 6.
Page 61-68. Publishing by Wiley Publishing,  Inc.    Indianapolis,  Indiana. Manufactured  in
the United States of America. 2006.
[11]  A.K.   Talukder,  H.A.  Prahalad,  “Security  &  scalability  architecture  for  next  generation
internet services “, IEEE Inc. page(s): 1 – 4, 2009.
[12]  V.Wheatman, “Integrating Physical and Information Security”, July 1, 2009.
[13]  E.Roback,“ Logical Access Control”, DRAFT Handbook, part of  NIST,1990.
[14]  R.Snevely,  “Enterprise  Data Center  Design  and Methodology”,  Sun Microsystems,  Inc.
901 San Antonio Road Palo Alto, CA 94303-4900 USA, 2001.
[15]  M.Kutare,  G.  Eisenhauer  “Monalytics:  Online  Monitoring  and  Analytics  for  Managing
Large Scale Data Centers”, ICAC, USA, 2010.
[16]  F. Li,  P. Zhang N. Bhatt  “Next Generation Monitoring  and Control Functions  for  Future
Control Centers “, IEEE, 2008.
[17]  G.  J.  PALJAK,  I.  SZOMBATH,  I.  KOCSIS,  T.  KOVÁCSHÁZY,  A.  PATARICZA,
“Model-Based control of  IT  Infrastructures”,  International Carpathian Control Conference,
ICCC, Eger, Hungary May 26-29, 2010.
[18]  ISO 9000/9001/9004. Quality Management Systems, ISO, Geneva, 2000.
[19]  ISO/IEC  17799.  Information  Technology  –  Security  Techniques  –  Code  of  Practice  for
Information Security Management, ISO, Geneva , 2005.
[20]  ISO/IEC  27001.  Information  Technology  -  Security  Techniques  -  Information  Security
Management Systems - Requirements, ISO, Geneva, 2005.

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