Autonomic Computing with perspective of Cloud Computing and Agile Methodology Dr. Arun Sharma M.Tech., PhD (Thapar University) Dy. Dean and Associate Professor

Autonomic Computing with perspective of Cloud Computing

and Agile Methodology

Dr. Arun SharmaM.Tech., PhD (Thapar University)

Dy. Dean and Associate Professor Indira Gandhi Delhi Technical University for Women

Kashmere Gate, Delhi - 619/04/23 Autonomic Systems 1

Complex heterogeneous infrastructures Scenario

Directory Directory and Security and Security

ServicesServicesExistingExisting

ApplicationsApplicationsand Dataand Data

BusinessBusinessDataData

DataDataServerServer

WebWebApplicationApplication

ServerServer

Storage AreaStorage AreaNetworkNetwork

BPs andBPs andExternalExternalServicesServices

WebWebServerServer

DNSDNSServerServer

DataData

Dozens of systems and applications

Hundreds of components

Thousands of tuning

parameters

Issues within IT industry!

• It's complexity of applications!!!!

• As computing power has increased, we've got the ability to create much larger kinds of applications.

• With millions or tens of millions of computer systems all cooperating, this complexity comes at a cost because humans are sitting behind the scenes, making all these machines work together.

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Why we need new Computing Strategies?

• Costs are also rising dramatically. • In the 1990s, approximately 80% of the cost of

major computer systems revolved around HW & SW acquisitions.

• Now the human expenses are roughly equal to equipment costs. If nothing changes, the human costs will double that of equipment in the next five to six years.


Need for new computing system• In this present rapidly growing complex world, the odds to a

complex computing system are very high.• To overcome the rapid growth of complex computing

systems and to reduce the barrier that complexity poses to further growth.

• IBM has initiated a vision to create self managed systems to address today’s concern of complexity.

• The self-managed and self-regulated systems which are capable of making decisions on its own are known as

“AUTONOMIC SYSTEMS”

INTRODUCTION TO AUTONOMIC COMPUTING

The word “autonomic” is from autonomous meaning self-governed or act independently.

Autonomic systems as the name suggests these are self-governed and self-regulated systems.

These systems are capable of making decisions on its own, using high level policies.

Biological Systems

• Think about biological systems, e.g. the human body, they're tremendously complex and very robust.

• The human body, for example, is constantly making adjustments. Your heart rate is being controlled; your breathing rate is controlled.

• All of these things happen beneath the level of conscious control.


Without requiring our conscious involvement- when we run, it increasesour heart and breathing rate

Biological Systems…• Attributes of biological systems

• Self-aware• self-healing• self-configuring• self-protecting

• Self-preservingAlso referred to as: Self-* features

THE human body is self-healing: Broken bones mend, cuts heal, and a child’s immunity system grows stronger with age,….


OUR CHALLENGE ????

• The body’s self managing nervous system, which controls involuntary actions without conscious awareness or involvement, has fascinated the world of medicine.

• So why can’t it be the same with computers and software systems?

• Must a computer engineer or a systems administrator monitor a server round-the-clock to ensure normal operation?


From Biological to Computer Systems

• We wish to build the attributes that we see in biological systems into complex computer systems.

• Such complex systems will be easier to maintain and administer


“Future Vision of IT”

• Convergence of Biology and Information Technology

• To incorporate Autonomic features and behavior in the computer

systems


Autonomic SystemFirst proposed by IBM in 2001

A system is autonomic if it:• has knowledge of itself, in terms of resources and

capabilities• has the ability to configure and reconfigure itself• has the ability to continuously self-optimize itself• has self-healing capabilities• has self-protection capabilities• has the ability to discover knowledge of its environment and

context and adapt accordingly• has the ability to function in a heterogeneous environment• has the ability to anticipate and adapt to user needs


Autonomic Computing

Autonomic - Pertaining to an on demand operating environment that responds automatically to problems, security threats, and system failures.

Autonomic computing - A computing environment with the ability to manage itself and dynamically adapt to change in accordance with business policies and objectives. Self-managing environments can perform such activities based on situations they observe or sense in the IT environment rather than requiring IT professionals to initiate the task

There are four distinct characteristics of an autonomic computing system: These environments are Self-configuring, Self-healing, Self-optimizing, & Self-protecting

ELEMENTS OF AUTONOMIC COMPUTING

Autonomic computing consists of following elements :• Possess system identity—detailed knowledge of components• Self-configure and reconfigure—adaptive algorithms• Optimise operations—adaptive algorithms• Recover—no impact on data or delay on processing• Self-protection• Be aware of environment and adapt Function in a

heterogeneous world• Hide complexity

Architecture details• Autonomic manager is a component that implements the control

loop– Monitor Function

• the function that collects, aggregates, filters and reports details (e.g. metrics, topologies)

– Analyze Function• the function that models complex situations to understand

current system state.– Plan Function

• the function that structures the actions needed to achieve goals and objectives.

– Execute Function• the function that changes the behavior of the managed

resource using effectors.

Autonomiccomputing

VISION

OBJECTIVES

ATTRIBUTES

ACTIVITIES

Self-management

Self-configuring

Self-healing

Self-protecting

Autonomic computing properties tree

Self-aware

Self-monitoring

Self-adjusting

New

Convert

Self-optimizing

Table: Aspects of Self-management without and with Autonomic computing

Properties of Autonomic computing

Current Computing without autonomic concept

Future computing with Autonomic Concept

Self-Configuration

Due to multiple platforms and vendors, installing configuring and maintaining systems are time consuming and error prone tasks

Automated configuration and system follows high-level policies. Rest of system adjusts automatically and seamlessly

Self-optimizationSystems have hundreds of manually set, nonlinear tuning parameters

Components and system continually seek opportunities to improve their own performance and efficiency

Self-healingProblem determination in large complex systems can take a team of programmer weeks

System automatically detects , diagnoses and repairs localized software and hardware problems

Self-protection Detection of recovery from attacks and cascading failure is manual

System automatically defends against malicious attacks or cascading failures. It uses early warning to anticipate and prevent system wide failure

Self Configuring


Autonomic Features in MS-Office

• MS Office (ver. 2007) include a Repair feature. • If key program file (such as Winword.exe) gets

corrupted or accidentally deleted, the software can reinstall it.

• Such features will soon be present in other desktop software.


Autonomic Features in Windows XP/7

• Windows XP/7 also incorporates self-healing technology. When an application crashes, the user can shut it down systematically, thereby preventing the entire system from freezing or hanging. This operating system also offers to report program errors to the Microsoft Support team. Further, Windows XP/7 looks out for updates and automatically downloads these when available.



• Plug-and-play is another element of autonomic computing. Plug in a new device to your PC and the system will automatically detect it. The operating system will then fire up its hardware wizard, which guides you through the process of installing the appropriate drivers for the new device.


Windows XP optimises its user interface (UI) by creating a list of most often used programs in the start menu. Thus, it is self-configuring in that it adapts the UI to the behaviour of the user, although in a fairly basic way, by monitoring what programs are called most often. It can also download and install new critical updates without user intervention, sometimes without restarting the system. Therefore, it also exhibits basic self-healing properties.



Intel's Itanium 2 Processor

• Intel Itanium 2 processor has built-in Autonomic Features.

• It allows the system to continue executing transactions as it recovers from several error conditions.


DB2: Self-tuning

• Autonomic computing requires servers, operating systems, and middleware and software to diagnose and correct problems without human intervention.

• DB2 has capabilities for self-management and automation for the database administrator.

• Self-tuning capabilities of DB2 Universal Database; rapid DB2 deployment via optimized configuration tooling; dynamic adjustment and tuning; simple and silent installation processes; integration with Tivoli® for system security and management.


DB2: Self-Optimization

Standard query optimisers would not be considered as providing autonomicity. However if while a query was running and the DBMS was monitoring the query’s execution and deciding on a different query plan, then we would consider that autonomic.


Research Issues in Autonomic Software Development

• Decision Making• Agility• Cloud


Runtime Decision Making

• Introduce a runtime decision making • RDM will be based on Artificial Intelligence• RDM will help IT systems to recover from unexpected errors

32

Sensors

ResourceManager

Effectors

Managed Element

ManageabilityInterface

Sensors Effectors

Knowledge

Plan

ExecuteMonitor

Analyze

Data Action

Autonomic Manager


19/04/23 Sandeep Kumar Chauhan 33


• Fuzzy Logic implementation for processing the actions

• Implementation of Intelligent Agents for learning• Data Mining and Knowledge Discovery for getting

historical data• Incorporation of template decision trees to be

used as base for creating new decision trees• Data ware house for storing and retrieving for

knowledge queries• ANN Based implementation

Sandeep Kumar Chauhan 34

Development of Self-Managing Systems and Agile Methodology

• Self Managing requirements may not be clear in initial phases

• Adding extra Self Management behaviour results into higher cost in traditional SDLC models

• Customers can get early view of the benefits of Self Management features


Agile SDLC’s

• Speed up or bypass one or more life cycle phases

• Usually less formal and reduced scope• Used for time-critical applications• Used in organizations that employ disciplined

methods

Agile SDLC’s

• Speed up or bypass one or more life cycle phases

• Usually less formal and reduced scope• Used for time-critical applications• Used in organizations that employ disciplined

methods

Agile Modeling for self-managing Systems


Autonomic through agile

• The Agile methodology is the best to create the different software components that support the change in requirements.

• Agile methodology may be the best solution for providing the Self-Managing capabilities in the system.


Autonomic Computing in Cloud


Cloud Computing Both software applications and computing

infrastructure are moved from private environments to third party data centres, and made accessible through the Internet. Cloud computing delivers infrastructure, platform, and software (applications) as subscription-based services in a pay-as-you-go model.– Cloud computing is a style of computing paradigm in

which typically real-time scalable resources such as files, data, software, hardware, and third party services can be accessible from a Web browser via the Internet to users.

Cloud Computing

• “refers to both the applications delivered as services over the Internet, and the hardware and system software in the data centres that provide those services”.

• “is a utility-oriented distributed computing system consisting of a collection of inter-connected and virtualized computers that are dynamically provisioned and presented as one or more unified computing resource(s) based on service-level agreements established through negotiation between the service provider and consumers”


Cloud Computing - Some terms

Term cloud is used as a metaphor for internet.Concept generally incorporates combinations of

the following Infrastructure as a service (IaaS) Platform as a service (PaaS) Software as a service(SaaS)

Autonomic Computing and Cloud


Clouds are complex, large-scale, and heterogeneous distributed systems (e.g., consisting of multiple Data Centres, each containing 1000s of servers and peta-bytes of storage capacity), management is a crucial feature.

To manage it manually is very difficult.

Autonomic Computing and Cloud

Effective management of services becomes fundamental in software platforms that constitute the fabric of computing Clouds.

It needs to be automated and integrated with intelligent strategies for dynamic provisioning of resources in an autonomic manner with the services that are self managed, secure, reliable, and cost-efficient.


Conclusion

• The Autonomic computing aims to provide a zero cost maintenance and highly reliable system to end user.

• Self-Management provides the monitoring, diagnosis and repair capabilities to maintain the systems’ behaviour and grants the expected service. It may be a very cost effective and efficient method for cloud computing also.


Conclusion :

Autonomic computing is Solution of today’s increasing complexity in computing science.

References[1] IBM Corporation: An architectural blueprint for autonomic computing. White

Paper, (2003)[2] J.O. Kephart and D.M. Chess, "The Vision of Autonomic Computing," Computer, vol.

36, no. 1, Jan. 2003, pp. 41-52. [3] R. Sterritt, M. Parashar, H. Tianfield and R. Unland, "A Concise Introduction to

Autonomic Computing," Journal of Advanced Engineering Informatics, Engineering Applications of Artificial Intelligence, Special Issue on Autonomic Computing and Automation, Elsevier Publishers, Vol, 19, pp. 181 ~ 187, 2005.

[4] Wikipedia.org, http://en.wikipedia.org/wiki/Autonomic_computing/ [5] IBM Autonomic Computing Website, http://www.ibm.com/autonomic/ [6] IBM Corporation: Practical Autonomic Computing: Roadmap to Self Managing

Technology, January 2006[7] Applied Autonomics, http://www.appliedautonomics.com/ [8] IPsoft, http://www-ip-soft.net/[9] Enigmatec Corporation, http://www.enigmatec.net/[10] HandsFree Networks, http://handsfreenetworks.com/[11] Ana project, http://www.ana-project.org/[12] MACE 2006, http://www.manweek2006.org/mace/mace.php

http://en.wikipedia.org/wiki/Autonomic_computing/

http://www.ibm.com/autonomic/

http://www.appliedautonomics.com/

http://www-ip-soft.net/

http://www.enigmatec.net/

http://handsfreenetworks.com/

http://www.ana-project.org/

http://www.manweek2006.org/mace/mace.php

…

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Autonomic Computing with perspective of Cloud Computing and Agile Methodology Dr. Arun Sharma M.Tech., PhD (Thapar University) Dy. Dean and Associate Professor