Proposal for an Automated System

III. PROPOSED SYSTEM

All traditional frameworks do not discuss functional requirements or, explicitly automatable parts of ITSM processes. Automation is identified as one of the approach to tackle the challenges of current service management processes.

The architecture of the system is shown below in Figure 1:

Figure 1. Block Diagram for the Architecture

As shown in the figure above, the architecture consists of three main blocks i.e., ITSM Server, Secondly the Knowledge server and finally the configuration Management logic for triggering the actions.

Firstly an incident does gets created or submit in the iTop Server with respect to the client request. Then there is a constant polling for the current status of the incident. As the status for the given incident does have three stages i.e. New, Assigned, Closed. Subsequently, for the given new Incident the status gets changed to Assigned when the based on which an Issue also gets created in the Knowledge server.

For the given Incident Id an AP Issue Id also gets created in the Knowledge server for which the status is also polled back to the ITSM server in the Public logs with respect to the given incident.

Once an issue and issue id gets created within the knowledge Server based on the issue type specific knowledge Item gets triggered. KIs are the considered to be a simple rule with context written in xml format which does have an Issue condition tag which gets cross checked with respect to the given incident. Based on the issue conditions corrective actions are taken to resolve the issue which is mentioned in the command tag for the respective KI.

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Subsequently, the triggering actions given by the KI are been executed by the configuration management tool. After the successful execution of the actions the issue gets closed for which the status is again polled back to the ITSM server and the related incident status also gets changed to close.

The MARS model basically defines the environment in which the KS (Autopilot) runs. With the help of this model the environment gone under excessive changes can be automated easily and quickly. It illustrates the interdependencies of application, resource, software and Machine. With this model, the IT landscape of a given company can be mapped to both a technical and business perspective. Here application and resource maps to the business relevant and organizational parts of IT operations whereas the software and the machine refers to the technical side of the IT operations.

Hence, it allows us to optimize the IT environment based on a lightweight and reusable model which could the basis for automated IT operations i.e., services. It can also be used to create the CI’s (Configuration Items).

IV. MATHEMATICAL MODEL

The system can be modeled mathematically given below.

Let, “S” be a proposed system such that,

S = {s, E, X, Y, F_S, DD, NDD …| Φ}

s = Starting point

= R->ITS_s

Where C_R = Set of client requests

ITSM_{s =} IT Service Management Server

E = Ending Point

= The given incident in terms of issue is solved

X = Input to the system

Set of Incidents (I) = {I₁, I₂, I₃ , ….}

Y = For the Given incident an issue in created in KS;

I->KS

Where KS =Knowledge Server

Deterministic Data (DD):

– Given Incident is already resolved.

Non-Deterministic Data (NDD):

–for the given incident there is no solution.

Success = Issue created in the KS in successfully solved.

= I_n-> r_n

Where, I_n is Incident created & r1 is desired result for r_n.

Failure = Failure in execution of user request

Conditions: -Insufficient input request and not valid user.

V. EXPERIMENTAL SETUP

The experimental setup for proposed system will be building an ITSM infrastructure and a Knowledge Server using built on Linux based machine using ITSM tool iTop. The ITSM Infrastructure would be having a Linux Machine Node on which ITSM tool iTop is been installed. Then we need to setup other Machine node i.e., for the implementation of the DS (Delivery Integration) where the deployment for the implemented code will be done. Third is the knowledge server i.e., another Linux Machine Node for the automation tool is required and the for configuration management.

The particulars about platform and technology used are mentioned as follows:

• Base Operating System: Linux Based Machine server

(Centos 6.5+ 64bit Preferred)

• Technology: iTop For ITSM server ,Version 2.1.0

Arago AutoPilot, Version 5.1

Ansible 1.7.2 / Chef. (Open Source).

• Databases: iTop Backend MySQL.
• Language: Java JDK 1.7.
• Java Tool: Eclipse JEE
• Other Dependencies: Maven3,Apache2,Tomcat7,

REST APIs, Shell Scripting, and XML for Knowledge Items, MARS model.

According to above specifications and structure, the proposed system is built up.

VII. CONCLUSION

Unlike other automation solutions, Knowledge based automation can deal with high levels of incorrectness and inaccuracy and only uses the given input as an entry point, or considers as a general universe description. Using this automation technology we try to enhance the power of IT configuration management process which is quite critical for our business processes. Our approach could also serve as input for discussing a reference model for the design of management services that could help tool vendors to create interoperable Management tools by enabling service-oriented access to specific tools functionality.

REFERENCES

[1] ISO/IEC, ISO/IEC 20000-1:2005: Information Technology Service Management, www.iso.org, 2005.

[2] Office of Government Commerce (OCG): IT Infrastructure Library (ITIL) Service Support (ISBN 0113300158), 2000; Service Delivery (ISBN 0113300174), 2001.

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[4] Information Systems Audit and Control Association (ISACA): Control Objectives for Information and Related Technology (CobiT), isaca.org/cobit.

[5]Microsoft TechNet: Microsoft Operations Framework 4.0,

http://technet.microsoft.com/de/library/cc506049 (enus).aspx

[6] Tele Management Forum (tmf): enhanced Telecom Operations Map (eTOM), 2009.

[7] Schaaf, T., Brenner M.: On Tool Support for Service Level Management: From Requirements to System Specifications.3^rdInternational Workshop on Business-Driven IT Management, 2008.

[8] ITSM reference. http://www.itsm.org

[9] SYMIAN: Analysis and Performance Improvement of the IT Incident Management Process Claudio Bartolini, Member, IEEE, Cesare Stefanelli, Member, IEEE, and Mauro Tortonesi

IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT, VOL. 7, NO. 3, SEPTEMBER 2010.

[10] Model-based Integration of Tools Supporting Automatable IT Service Management Processes, Klaus Scheibenberger IT Infrastructure and Services Karlsruhe Institute of Technology (KIT) 76131 Karlsruhe 2010.

[11] IT service management driven by business objectives: An application to incident management Claudio Bartolini, Mathias Sallé HP Laboratories Palo Alto, USA. David Trastour HP Laboratories Bristol, UK 2006 IEEE.

[12] Synthetic Incident Generation in the Reenactment of IT Support Organization Behavior. Bartolini, C.,HP Labs., Hewlett Packard, Palo Alto, CA, USA, Stefanelli, C.,Tortonesi, M. ,Integrated Network Management (IM 2013), 2013 IFIP/IEEE INTERNATIONAL SYPOSIUM.

[13] K Christiance, J. Lenchner et al, “A Service Delivery Platform for Server Management Services”, to appear in IBM Journal for Research and Development, special issue on Service Delivery, 2008.

[14] Arago: The Automation Experts-Autopilot-version-33-englisch-47-728.

[15] BMC Patrol, www.bmc.com/