WELCOME

1. WELCOME

2. AUTONOMICCOMPUTING PRESENTED BY: NIKHIL P S7 IT ROLL NO: 33

3. OVERVIEW • Motivation • Introduction • Why Autonomic Computing • Characteristics • Architecture • Application • Challenges • Conclusion

4. MOTIVATION • Present day IT environments are complex, heterogeneous in terms of software & hardware from multiple vendors. • Computing systems have evolved into millions of interconnected devices whose interactions create complex web on increasingly complex architecture.

5. Present day IT environment

6. Complexity of Information Technology

7. INTRODUCTION It is a term coined by IBM . Principle similar to autonomic nervous system. Its main aim is to make computer system more self managing and elastic, removing obstacles to growth and flexiblity. Helps to address complexity by using technology to manage technology

8. WHY AUTONOMIC COMPUTING • “Civilization advances by extending the number of important operations which we can perform without thinking about them”- ALFRED NORTH WHITEHEAD • This quote made by the preeminent mathematician Alfred Whitehead holds both the lock and the key to the next era of computing. • The high-tech industry has spent decades creating computer systems with ever- mounting degrees of complexity to solve a wide variety of business problems.

9. CONTD….. Ironically, complexity itself has become part of the problem. It’s a problem that's not going away, but will grow exponentially, just as our dependence on technology has To overcome this problem IBM suggested a solution: build computer systems that regulate themselves much in the same way as our autonomous nervous systems regulates and protects our bodies. This new model of computing is called autonomic computing

10. The vision for Autonomic Computing “Intelligent” systems that: • Manage complexity • Know themselves • Continuously tune themselves • Adapt to unpredictable conditions • Prevent and recover from failures • Provide a safe environment

11. CHARACTERISTICS

12. Self-managing systems that deliver Business Resiliency Discover, diagnose,and act to prevent disruptions Increased Responsiveness Adapt to dynamically changing environments Operational Efficiency Tune resources and balance workloads to maximize use of IT resources Secure Information and Resources Anticipate, detect, identify, and protect against attacks

13. SELF-CONFIGURATION Adapt automatically to the dynamically changing environment • Internal adaptation – Add/remove new components – configures itself on the fly • External adaptation -Systems configure themselves into a global infrastructure

14. SELF-HEALING Discover, diagnose and react to disruptions without disrupting the service environment • Fault components should be – detected – Isolated – Fixed – reintegrated

15. SELF-OPTIMIZATION Monitor and tune resources automatically – Support operating in unpredictable environment – Efficiently maximization of resource utilization without human intervention Dynamic resource allocation and workload management. – Resource: Storage, databases,networks – For example, Dynamic server clustering

16. SELF-PROTECTION Anticipate, detect, identify and protect against attacks from anywhere – Defining and managing user access to all computing resources – Protecting against unauthorized resource access, e.g. SSL – Detecting intrusions and Reporting as they occur

17. And also • Self-aware System is aware of its internal state. • Context-aware System is aware of its execution environment. • Open System is able to operate in an heterogeneous environment. • Anticipatory System is able to anticipate the optimized resources needed.

18. LEVELS OF AUTONOMIC MATURITY

19. CONTD… • Basic : IT professionals manage everything by hand. • Managed : Data are collected from the system (via sensors) and selected .The time is reduced. • Predictive: Recognition of patterns and suggestion of a solution, the decision is made still by human.

20. CONTD… • Adaptive : The system makes and applies the solutions. IT staff provides policies used for plans and monitors system’s actions. • Autonomic : Integrated IT components are collectively and dynamically managed by business rules and policies.

21. ARCHITECTURE • Autonomic element is the fundamental atom of the architecture • It consist of two parts • Managed Element • Autonomic Manager • Consist of one or more managed elementscoupled with a single autonomicmanager

22. CONTD.. • A Managed Element can be: Hardware resource, CPU, database, Application service, etc. • The components and functions of a single autonomic manager often referred to as the "MAPE loop" for Monitor, Analyze, Plan, and Execute, supplemented by a Knowledge base.

23. Core building blocks for an open architecture Management using MAPE: – Monitoring managed elements and their external environment – Analyzing the gathered information – Planning and executing based on information

24. CONTD… MONITOR • An autonomic manager monitors instrumentation data from multiple sensors in a system. • The sensors "sense" various aspects of the state of the monitored computing system. • This can include aspects of the hardware instrumentation, ambient information ,and aspects of the software components

25. CONTD… ANALYZE • This component of the autonomic manager contains the intelligence required to interpret and correlate the above mentioned instrumentation data. • This component usually has the ability to consult historical data and to compare them with current state to detect significant changes.

26. CONTD… PLAN • Once an analysis report of the situation is completed, the planning component can define a series of control actions that should bring the system to a normal operating range. EXECUTE • This component receives the series of action steps from the planning component, and puts the plan into action. • It activates appropriate control points, or effectors, on the managed platform following the proper sequence and timing

27. CONTD… • Knowledge base This serves as a repository of knowledge, such as historical data and policies, which can be utilized by the other components in their operation.

28. APPLICATIONS • E−Sourcing • Problem determination • Complex analysis • Autonomic management

29. CHALLENGES • Autonomic System challenges • – Self-configuration in large-scale application • – Problem localization and automated remediation • – Decision making of coordination of optimizing process • – Self-protecting against active threats specific types of threats • −Needs for a abstraction and co-operation in relevant fields

30. CONCLUSION Autonomic computing is: • Solution of today’s increasing complexity in computing science. • Self-Management and dynamicadaptive behaviors “The new economics requires that systems be autonomic: autoinstalling, automanaging, autohealing, and autoprogramming.”

31. REFERENCES • http:// www.ibm.com • http:// www.research.ibm.com • http:// www.wikipedia.org

32. THANK U… QUERIES…???