autonomic computing - 123seminarsonly.com · dream of pervasive computing … or nightmare! mobile...

Mobile and Pervasive Computing Lecture09: Autonomic Computing

Note 1

CSIE50600: Advanced Database Systems

Mobile and Pervasive Computing

Autonomic Computing Shiow-yang Wu

Department of Computer Science and Information Engineering

National Dong Hwa University

(Part of the Slides are taken from Prof. Chung-Ta King of NTHU and Prof. Friedemann Mattern of ETH Zurich)

Mobile and Pervasive Computing Autonomic Computing 1

ReferencesJeffrey O. Kephart and David M. Chess. “The vision of autonomic computing”, IEEE Computer, Jan 2003.IBM Autonomic Computing Manifesto (http://www.ibm.com/research/autonomic)


Note 2


Trillions of heterogeneous computing devices connected to the Internet

Dream of Pervasive Computing …

or Nightmare!


Core of the ProblemComplexity in systems themselves and in the operating environment

As systems become more interconnected and diverse, architects are less able to anticipate and design interactions among componentspush to runtime, late bindinge.g., hot-plug, JVM, JIT compilation, service discovery, mobile agents, …

Complexity managementhuman intervention and IT costsEven in uncertain economic times, demand for skilled I/T workers is expected to increase by over 100 percent in the next six years.


Note 3


Need Complexity ManagementBut complexity is beyond that human can handleHuman out of the control loop autonomicEven though we are moving along this direction, is there any systematic way of addressing this issue?

Autonomic ComputingComputer systems should ack like our autonomic nervous system that governs our heart rate and body temperature, thus freeing our conscious brain from the burden of dealing with these and many other low-level, yet vital, functions.


Alan G. Ganek, Vice PresidentAutonomic ComputingIBM Software Group

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

Autonomic Computing


Note 4


Directory Directory and Security and Security

ServicesServicesExistingExisting

ApplicationsApplicationsand Dataand Data

BusinessBusinessDataData

DataDataServerServerWebWeb

ApplicationApplicationServerServer

Storage AreaStorage AreaNetworkNetwork

BPs andBPs andExternalExternalServicesServices

WebWebServerServer

DNSDNSServerServer

DataData

Dozens of systems and applications

Hundreds of components

Thousands of tuning

parameters

Complex Heterogeneous Infrastructures Are a Reality!


Industry TrendsAdministration of systems is increasingly difficult

100s of configuration, tuning parameters for DB2

Heterogeneous systems are increasingly connectedIntegration becoming ever more difficult

Architects can't plan interactions among componentsIncreasingly dynamic; frequently with unanticipated components

More burden must be assumed at run timeBut human administrators can't assume the burden

6:1 cost ratio between storage admin and storage40% outages due to operator error

Need self-managing computing systemsBehavior specified by sys admins via high-level policiesSystem and its components figure out how to carry out policiesself-managing, self-diagnostic, and transparent to the user


Note 5


Autonomic Computing Vision“Intelligent” open systems that…

Manage complexity“Know” themselvesContinuously tune themselvesAdapt to unpredictable conditionsPrevent and recover from failuresProvide a safe environment

Self-management:free administrators from details of operationsprovide peak performance 24/7Concentrate on high-level decisions and policies

Flexible, accessible (always on), and transparent


Increase ResponsivenessAdapt to dynamically changing environments

Business ResiliencyDiscover, diagnose, and act to prevent disruptions

Operational EfficiencyTune resources and balance workloads to maximize use of IT resources

Secure Information and ResourcesAnticipate, detect, identify, and protect against attacks

Self-managing Systems That …

Aware/Proactive


Note 6


Self-Configuring Example:DB2 Configuration Advisor

H/Wdetection

Expertheuristics

Basicdescription

Configurationmodel

Configurationsettings


Problem Problem DatabaseDatabase

Electronic Response

Dispatch CEService agent

detects a hardware problem

Voice Support

Sends error symptomsto IBM

Sends Symptoms

for Diagnosis

DataDataCatcherCatcher

AnalysisAnalysisofof

Problem Problem RecordRecord

Fully Automatic

Faster problem resolutionHigher availability/resiliencyLower maintenance cost

""IBM's eService Agent allows me to sleep soundlyknowing the system is being monitored 24x7."

Alex Tambellini, 7-Eleven Stores Pty Ltd.

Self-Healing Example: IBM Electronic Service Agent


Note 7


InternetInternet

Appliance Appliance ServersServers

Web Web Application Application

ServersServersData and Data and

Transaction Transaction ServersServers

Internet/Internet/ExtranetExtranet

Business Business PartnersPartners

SelfSelf--tuning, endtuning, end--toto--end performance end performance managementmanagement

Dynamic allocation of network resourcesDynamic allocation of network resourcesWorkload balancing & routingWorkload balancing & routingCross platform reportingCross platform reportingPolicyPolicy--based for various classes of users & applicationsbased for various classes of users & applications

Heterogeneous, distributed components working together

Self Optimizing: Enterprise Workload Management


Automate incident responseProtect systems and dataHelp prevent service disruptions

Risk MgrIDS Rules

Event Database

CorrelationEngine

Intrusion Detection System (IDS)

RouterWebServer

Firewall

ApplicationServer Intrusion

Detection

InternetIntranet

RiskManagerSecurity Event

ApplicationServer

"The Tivoli security management software portfolio is helping our clients extend their businesses to the

Internet while providing security and privacy..."Mark Ford, Principal

Deloitte & Touche

Rapid / automated analysisof complex situations

Self-Protecting Example: IBM Tivoli Risk Manager


Note 8


Evolving towards Self-management


THE 8 ELEMENTSSystem needs to "know itself“Configure and reconfigure itself under varying (and in the future, even unpredictable) conditionsNever settles for the status quo - it always looks for ways to optimize its workingsMust perform something akin to healing (self-healing)Must be an expert in self-protectionMust know its environment and the context surrounding its activity, and act accordinglyMust function in a heterogeneous world and implement open standardsAnticipate the optimized resources needed while keeping its complexity hidden


Note 9


Manual Autonomic

Ben

efits

Skill

sC

hara

cter

istic

s

ManagedLevel 2

PredictiveLevel 3

AdaptiveLevel 4

AutonomicLevel 5

BasicLevel 1

Multiple sources of

system generated data

Requires extensive,

highly skilledIT staff

Basic Requirements

Met

Evolving to Autonomic Computing


Manual Autonomic

Ben

efits

Skill

sC

hara

cter

istic

s

BasicLevel 1

PredictiveLevel 3

AdaptiveLevel 4

AutonomicLevel 5

Multiple sources of


Requires extensive,


Basic Requirements

Met

ManagedLevel 2

Consolidationof data and

actions through

managementtools

IT staffanalyzes andtakes actions

Greater system

awarenessImproved

productivity



Note 10


Manual Autonomic

Ben

efits

Skill

sC

hara

cter

istic

s

BasicLevel 1

ManagedLevel 2

AdaptiveLevel 4

AutonomicLevel 5

Multiple sources of


Requires extensive,


Basic Requirements

Met


actions through

managementtools


Greater system

awarenessImproved

productivity

PredictiveLevel 3

Systemmonitors,

correlates and recommends

actions

IT staffapproves and

initiates actions

Reduced dependency on

deep skillsFaster/better

decision making



Manual Autonomic

Ben

efits

Skill

sC

hara

cter

istic

s

BasicLevel 1

ManagedLevel 2

PredictiveLevel 3

AutonomicLevel 5


Multiple sources of


Requires extensive,


Basic Requirements

Met


actions through

managementtools


Greater system

awarenessImproved

productivity

Systemmonitors,


actions


initiates actions



decision making

AdaptiveLevel 4

System monitors,

correlates and takes action

IT staff manages

performance against SLAs

Balanced human/system

interactionIT agility and

resiliency


Note 11


Manual Autonomic

Ben

efits

Skill

sC

hara

cter

istic

s

BasicLevel 1

ManagedLevel 2

PredictiveLevel 3

AdaptiveLevel 4

Multiple sources of


Requires extensive,


Basic Requirements

Met


actions through

managementtools


Greater system

awarenessImproved

productivity

Systemmonitors,


actions


initiates actions



decision making

System monitors,

correlates and takes action

IT staff manages

performance against SLAs

Balanced human/system

interactionIT agility and

resiliency

AutonomicLevel 5

Integrated components dynamically managed by

business rules/policies

IT staff focuseson enabling

business needs

Business policy drives IT

managementBusiness agility and resiliency



IBM’s Architecture ModelIntelligent control loop:

Implementing self-managing attributes involves an intelligent control loop


Note 12


Control Loops Delivered in 2 Ways

Combinations of Management Tools

Recourse Provider


3 Layers of Control Loop Management

Composite resources tied to business decision-making

Composite resources decision-making, e.g., cluster servers

Resource elements managing themselves


Note 13


Autonomic Element -StructureFundamental atom of the architecture

Managed element(s)Database, storage

Autonomic managerResponsible for:

Providing its serviceManaging ownbehavior inaccordance withpoliciesInteracting with other autonomic elements

An Autonomic Element

Monitor

Analyze

Sensors

Execute

Plan

Effectors

Knowledge

Aut

onom

icM

anag

erM

anag

edE

lem

ent

Sensors Effectors


Alerts, events & problem analysis request interface

SLA/Policy interface, interprets & translates into "control logic"

PlanPolicy Transforms

Plan Generators

Policy InterpreterAnalyze

Execute

Service Dispatcher

Distribution Engine

Scheduler Engine

Workflow Engine

Monitor

Metric Managers

Filters

Simple CorrelatorsKnowledge

Policy

CalendarTopology

Recent Activity Log

Sensors Effectors

Rules Engines

Analysis Engines

Policy Validations

Policy Resolution

Autonomic Manager -Substructure


Note 14


Autonomic Elements -InteractionRelationships

Dynamic, ephemeralFormed by agreement

May be negotiated

Full spectrumPeer-to-peerHierarchical

Subject to policies


Engineering ChallengesLife cycle of an autonomic element

Design, test, and verification.Installation and configuration.Monitoring and problem determination.Upgrading.Managing the life cycle.

Relationships among autonomic elementsSpecification.Location.Negotiation.Provision.Operation.Termination.


Note 15


Scientific ChallengesBehavioral abstractions and modelsRobustness theoryLearning and optimization theoryNegotiation theoryAutomated statistical modeling


Multiple Contexts for Autonomic Behavior

System Elements

(Intra-elementself-management)

Groups of Elements

(Inter-elementself-

management)

Business Solutions

(Business Policies, Processes, Contracts)

ServerFarm

EnterpriseNetwork

StoragePool

Customer Relationship Management

EnterpriseResourcePlanning

Servers Storage NetworkDevices Middleware

DatabaseApplications


Note 16


Mapping to IT Processes


Levels of Maturity


Note 17


Enabled capabilities

Core technologies

Administrative Console

Policy Infrastructure

Data Collection (Logging/Tracing)

Infrastructure Provisioning

Install/Dependency Management

Heterogeneous Workload Management

Solution Management

Policy-based Management

End-to-end Problem Determination

Automated Root Cause AnalysisAuto-Update

Identity/Security ManagementAuto-Detection

Dynamic Provisioning

Autonomic Computing Requires Core Technologies


Integrated Solutions Console for Common Sys Administration

Value:One consistent interface across product portfolioCommon runtime infrastructure and development tools basedon industry standards, component reuseProvides a presentation framework for other autonomic core technologies

...n

Customer pain point:Complexity of operations

Standards-based: J2EE, JSR168


Note 18


Log and Trace Tool for Problem Determination

Value:Introduces standard interfaces and formats for logging and tracingCentral point of interaction with multiple data sourcesCorrelated views of dataReduced time spent in problem analysis

Analysis Engine

Data Exploiters

Data Producers

ISC

StandardInterface

LoggingAgent

Common situations and data model

BLog

Embedded adapter

....

Data Store

LoggingAgent


eServerLog

Embedded adapter

LoggingAgent


ALog

Embedded adapter

Collector Collector....

Parser

Parser

Parser

Viewer....

Customer pain point:Difficulty in analyzing problems in multi-component systems

Standards-based:JSR47, Apache


Install/Config Package for Solution Install

Value:One consistent software installation technology across all productsConsistent and up-to-date configuration and dependency data, key to building self-configuring autonomic systemsReduced deployment time with less errorsReduced software maintenance time, improved analysis of failed system components Component-based install for IBM and non-IBM products

Install package developer

Meta-DataNameUUIDVendorVersion

Configuration PropertiesInstall InputRuntime Attributes

DependenciesHW, SW, OS, ConfigurationExtensions

Install ActionsExtensions

Verification ActionsExtensions

Configuration ActionsExtensions

Package Structure

Product Files (binaries, etc.)Product Files (binaries, etc.)

Deployment Descriptor

Deployment Descriptor

Verification Actions

Verification Actions

DependencyCheckers

DependencyCheckers

Custom Extensions

InstallActionsInstallActions

Configuration Actions

Configuration Actions

GUI Interface

GUI Interface

Customer pain point:Difficulty of deployment in complex systems

Standards-based:OGSA, Web Services

Partnering with InstallShield


Note 19


Policy Tools for Policy-based Management

Value:Uniform cross-product policy definition and management infrastructure, needed for delivering system-wide self-management capabilitiesSimplifies management of multiple products; reduced TCOEasier to dynamically change configuration in on-demand environment

Customer pain point:Complexity of product and systems management

Standards-based:DMTF, OASIS, OGSA

Adaptation

Definition

ValidationLocal

Repository

Distribution

EnforcementPoint

Push or pull

Push or pull

Activate

Implement

MONI

TOR

Facts

Analysis

Resource

…

…

EnforcementPoint

Resource Resource


Implementing Autonomic Managers

Value:Components to simplify the incorporation of autonomic functions into applications

Building blocks for self-managementMonitoring, analysis, planning and execution components Including autonomic computing technologies, grid tools, and services

PluggableDefines interfaces and provides implementations for each major toolkit component

Customer pain point: How to implement end-to-end autonomic solutions

Standards-based:OGSA, W3C


Note 20


Summary of Autonomic Computing ArchitectureBased on a distributed, service-oriented architectural approach, e.g., OGSA

Every component provides or consumes servicesPolicy-based management

Autonomic elementsMake every component resilient, robust, self-managingBehavior is specified and driven by policies

Relationships between autonomic elements Based on agreements established and maintained by autonomic elementsGoverned by policiesGive rise to resiliency, robustness, self-management of system


Summary"Civilization advances by extending the number of important operations which we can perform without thinking about them."

- Alfred North Whitehead

autonomic computing - 123seminarsonly.com · dream of pervasive computing … or nightmare! mobile...

Documents