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Published on September 18, 2007

Author: Malbern


Autonomic Computing: Implementing the Vision :  Autonomic Computing: Implementing the Vision Alan Ganek Vice President IBM Autonomic Computing Complex heterogeneous infrastructures are a reality!:  Complex heterogeneous infrastructures are a reality! CIO blues:  CIO blues Customers need the ability to configure systems automatically based upon demand, with 24x7 availability of mission critical applications. They need assurance that their employees, customers and partners have secure access to the right systems, which are continuously optimized for productivity. Too much time and money is spent running existing infrastructure Complexity in running and managing the IT infrastructure Difficulty in deployment of complex systems The inability to manage the infrastructure seamlessly 'Most of my IT budget is spent on what I already have, leaving little for new projects' Swamped by the proliferation of technology and platforms to support Customers currently deal with this by…:  Customers currently deal with this by… Training specialists to hand-configure systems by specifying, installing and configuring hundreds of components Paying specialists to babysit mission critical systems around the clock Hiring auditors to manually probe systems for vulnerabilities Organizing teams to study end-to-end performance across many systems 'People make mistakes when they are under pressure. Autonomic computing holds the most promise in helping administrators reduce human error and improve data integrity.' —Andrew Hall, President The computer is not living up to its job description! Autonomic Vision:  Autonomic Vision 'Intelligent' open systems that… Manage complexity Know themselves Continuously tune themselves Adapt to unpredictable conditions Prevent and recover from failures Provide a safe environment Focus on business, not infrastructure! 'Autonomic computing allows companies to operate more efficiently and achieve more from their existing IT environments, enabling increased responsiveness, business continuance and availability.' —Rick Sturm Autonomic ComputingSelf-managing systems that …:  Autonomic Computing Self-managing systems that … Increase Responsiveness Adapt to dynamically changing environments Business Resiliency Discover, diagnose, and act to prevent disruptions Operational Efficiency Tune resources and balance workloads to maximize use of IT resources Secure Information and Resources Anticipate, detect, identify, and protect against attacks ...achieving the correct balance between what is managed by a person versus the system How does autonomic computing help customers?:  How does autonomic computing help customers? Improved resiliency and quality of service Always there when you need it Safe and secure Accelerated time to value Optimizes productivity and business value Faster deployment of applications that execute business strategies Increased return on IT investment (ROI) Better asset utilization More productive people Reinvestment of IT productivity and cost savings Slide8:  on demand operating environment Autonomic Core Capabilities Business Policy Delivering Autonomic Capability Autonomic Product Features and Enablers A Holistic Approach to Autonomic Computing:  Architecture Framework Common Autonomic construct for all system elements Distributed components and systems integrated as one virtual operating system Web Services Interfaces to elements Industry standards are key to the success of Autonomic Computing A Holistic Approach to Autonomic Computing Architecture Framework Autonomic control loops: next step evolution:  Autonomic control loops: next step evolution Autonomic features Local view Global environment view and knowledge USER RESPONSE TIME AVAIL. RESOURCE BUSINESS SLA POLICY Core Building Blocks for an open architecture:  Core Building Blocks for an open architecture An autonomic element contains a continuous control loop that monitors activities and takes actions to adjust the system to meet business objectives Autonomic elements learn from past experience to build action plans Managed elements need to be instrumented consistently How Do We Make Components Autonomic?:  How Do We Make Components Autonomic? Autonomic elements have two management tasks They manage themselves They manage their relationships with other elements through negotiated agreements Autonomic Database Autonomic Storage Array 'I need to allocate some additional table space ' 'I am reallocating storage and moving the information' Autonomic Manager Substructure:  Autonomic Manager Substructure Alerts, events and problem analysis request interface SLA/Policy interface, interprets and translates into 'control logic' Plan Policy Transforms Plan Generators Policy Interpreter Analyze Execute Service Dispatcher Distribution Engine Scheduler Engine Workflow Engine Monitor Metric Managers Filters Simple Correlators Knowledge Policy Calendar Topology Recent Activity Log Sensors Effectors Rules Engines Analysis Engines Policy Validations Policy Resolution Autonomic computing adoption model:  Core Building Blocks for an Open Architecture Autonomic computing adoption model … Multiple Contexts for Autonomic Behavior:  Multiple Contexts for Autonomic Behavior System Elements (Intra-element self-management) Groups of Elements (Inter-element self-management) Business Solutions (Business Policies, Processes, Contracts) Server Farm Enterprise Network Storage Pool Customer Relationship Management Enterprise Resource Planning Servers Storage Network Devices Middleware Database Applications Putting It All Together – An Example :  Putting It All Together – An Example Systems can go from steady state … Internet to overloaded without warning Autonomic Computing: Dynamic Surge Protection:  Autonomic Computing: Dynamic Surge Protection Database WAS Driver (simulates Internet in/out) Slide18:  Response Time Actual BOPS Predicted BOPS #Active Servers #Requested Servers 1 1. Steady State Slide19:  2. Monitor, Detect Surge Response Time Actual BOPS Predicted BOPS #Active Servers #Requested Servers 1 2 Slide20:  3. Forecast, Provision Servers Response Time Actual BOPS Predicted BOPS #Active Servers #Requested Servers 1 2 1 2 3 Slide21:  4. Monitor, Remove Servers 1 2 4 3 Open Standards for Self-Managing Systems:  Why Standards? Autonomic computing is an industry-wide initiative Proprietary solutions with vendor lock-in are unacceptable to customers Open, level playing field where vendors compete with best solutions Standards-based components can interoperate Easier to integrate multi-vendor components into an end-to-end solution Open Standards for Self-Managing Systems Industry standards are key to the success of Autonomic Computing Game Plan… Leverage existing standards when feasible Drive new standards through open standards bodies when necessary Coordinate disparate standards efforts when required Slide23:  on demand operating environment Core Capabilities For Enabling Autonomic Computing Autonomic Core Capabilities Evolving Interfaces Service Support Solution install/maintain Problem determination Service Delivery Policy based mgmt/security Autonomic monitoring Complex analysis Heterog. Workload Mgmt Provisioning Common Systems Administration Log and Trace Tool for Problem Determination:  Value: Reduced time spent in problem analysis Central point of interaction with multiple data sources Introduces standard interfaces and formats for logging and tracing Correlated views of data Customer pain point: Difficulty in analyzing problems in multi-component systems Log and Trace Tool for Problem Determination Standards-based: JSR47, Apache Tivoli Autonomic Monitoring Engine:  Value: Root cause analysis for IT failures - not just surfacing symptoms Server level correlation of multiple IT systems Applies intelligent, automated corrective action Customer pain point: Difficult to determine problem’s root cause required to take corrective action Standards-based: CIM, SNMP, WMI, JMX Tivoli Autonomic Monitoring Engine ABLE Rules Engine for Complex Analysis:  Value: Fast, reusable and scalable set of learning and reasoning components Intelligent agents for capturing and sharing individual and organizational knowledge Learns from experience and predicts future states Correlates events and applies policy to take action Customer pain point: Complex algorithms required to implement intelligent autonomic behavior Standards-based: FIPA, JSR87 ABLE Rules Engine for Complex Analysis Policy Tools for Policy-based Management:  Value: Uniform cross-product policy definition and management infrastructure, needed for delivering system-wide self-management capabilities Simplifies management of multiple products; reduced TCO Easier to dynamically change configuration in on-demand environment Customer pain point: Complexity of product and systems management Standards-based: DMTF, OASIS, OGSA Policy Tools for Policy-based Management Autonomic Computing Standards:  Core Capabilities Solution Install Common System Administration Problem Determination Autonomic Monitoring Heterogeneous Workload Management Complex Analysis Policy-Based Management Arenas GGF, OASIS, Open Group, IETF, W3C (Web Services, …) J2EE, JCP (JSRs) SNIA (Storage networks) DMTF (Systems management) Autonomic Computing Standards Standards-based: OGSA, Web Services Standards-based: CIM, SNMP, WMI, JMX Standards-based: J2EE, JSR168 Standards-based: JSR47, Apache Standards-based: ARM Standards-based: FIPA, JSR87 Standards-based: DMTF, OASIS, OGSA Autonomic Computing alphaWorks Zone:  Autonomic Computing alphaWorks Zone Get started developing autonomic solutions now Available on alphaWorks: Log and Trace Tool Business Workload Management Developer Kit Tivoli Resource Model Builder Agent Building and Learning Environment (ABLE) IBM Grid Toolbox Web Services Tools Coming in 2H03 – components from: Autonomic Computing Toolkit Solution Install Policy-based Management and more! Research Challenges:  Life cycle of autonomic elements Multi-agent learning andamp; negotiation/conflict resolution Software tools Testing, verification, robustness Policies and SLA’s Availability, fault tolerance andamp; recovery Continuous operations Problem determination Optimization andamp; prediction End to end security Research Challenges Innovation Required!! Distributed resource management andamp; scaling Peer system interaction Context awareness Human computer interface Metering, monitoring andamp; control Cultural change andamp; trust . . . . The journey has started……:  The journey has started…… Products, services available today Architecture and core technologies emerging IBM is working with business partners and standards organizations to develop open standards for self-managing systems Broad IT industry participation is needed – this is an industry-wide initiative Innovation is required!! Aggressive research is essential!! Freeing people to focus on their business instead of their infrastructure Copyright:  Copyright : © Copyright IBM Corporation 2003. All rights reserved. IBM, the IBM logo, the e-business logo and other IBM products and services are trademarks or registered trademarks of the International Business Machines Corporation, in the United States, other countries or both. References in this publication to IBM products, programs, or services do not imply that they will be available in all countries in which IBM operates. Product release dates and/or capabilities referenced in this publication may change at any time at IBM’s sole discretion based on market opportunities or other factors, and are not intended to be a commitment to future product or feature availability in any way.  Java and all Java-based trademarks are trademarks of Sun Microsystems, Inc. in the United States, other countries or both.  Microsoft, Windows, Windows NT and the Windows logo are trademarks of Microsoft Corporation in the United States, other countries or both.   All other trademarks, company, products or service names may be trademarks, registered trademarks or service marks of others. QUESTIONS?

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