Title/subtitle/confidentiality line: 10pt Arial Regular, white Maximum length: 1 line Information separated by vertical strokes, with two spaces on either

1 © 2002 IBM Corporation

Autonomic Computing

Alan G. GanekVice PresidentIBM Autonomic Computing

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


xOn Demand EraOn Demand Era

Responsive in real-time

Variable cost structures

Focused on what’s core and differentiating

Resilient around the world, around the clock

IntegratedOpenVirtuala


CIO’s Speak Out

“Most of my costs are really pure maintenance and operations – keeping the processes running that keep the ship afloat. Our development budget suffers.”

“Y2K and 9/11 have forced us to look at what we have – and we have too much complexity.”


Complex heterogeneous infrastructures are a reality!

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


What Are Some e-business IT Challenges Your Customers Face Today?

WorkloadsWorkloads

PricePrice

Complexity

Skills

Resiliency

Return on Investment

Price performance gains in technology are more than offset by scale and complexity of deployments


Frees your business to focus on business, not

infrastructure

What Is The Autonomic Computing 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


Increased return on IT investment (ROI) Lower administrative costs

Improved utilization of assets

IT alignment with business goals

Increased performance

Improved resiliency: Quality of Service (QoS) Reduced downtime

Improved security

Accelerated implementation of new capabilities: Time to Value (TTV)

Faster / more accurate installation of new capabilities

Reduced test cycles

Autonomic Computing helps CIOs, CTOs, and IT managers to realize:


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


Basic description

HWdetection

Expertheuristics

Configurationmodel

Configurationsettings

Speeds deploymentImproves performanceFrees up resource

Basic description

HWdetection

Expertheuristics

Configurationmodel

Configurationsettings

Per

form

ance

as

Per

cen

tag

e o

f D

BA

tu

ned

So

luti

on

0%

50%

100%

150%

200%

250%

DBA tuned

Advisor as % of tuned

Default configuration

OLTP - 32 OLTP - 64 Cust #2 Cust #1

DB2 Configuration Advisor Results

Self-Configuring Example: DB2 Configuration Advisor


Problem Problem DatabaseDatabase

Electronic Response

Dispatch CEService agent

detects a hardware problem

Voice Support

Sends error symptomsto IBM

Sends Symptoms

for Diagnosis

DataDataCatcherCatcher

AnalysisAnalysis

ofof

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


Self Optimizing: Enterprise Workload Management

InternetInternet

Appliance Appliance ServersServers

Web Web Application Application

ServersServersData and Data and

Transaction Transaction ServersServers

Internet/Internet/ExtranetExtranet

Business Business PartnersPartners

Self-tuning, end-to-end Self-tuning, end-to-end performance managementperformance management

Dynamic allocation of network resourcesDynamic allocation of network resources Workload balancing & routingWorkload balancing & routing Cross platform reportingCross platform reporting Policy-based for various classes of users & Policy-based for various classes of users &

applicationsapplications

Heterogeneous, distributed Components working together

Open standards based instrumentation


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

Self-Protecting Example: IBM Tivoli Risk Manager

Rapid / automated analysisof complex situations


Manual Autonomic

Ben

efi

tsS

kill

sC

har

acte

rist

ics

ManagedLevel 2

PredictiveLevel 3

AdaptiveLevel 4

AutonomicLevel 5

Evolving to Autonomic Computing

BasicLevel 1

Multiple sources of

system generated data

Requires extensive,

highly skilled IT staff

Basic Requirements

Met


Manual Autonomic

Ben

efi

tsS

kill

sC

har

acte

rist

ics

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 awareness

Improved productivity


Manual Autonomic

Ben

efi

tsS

kill

sC

har

acte

rist

ics

BasicLevel 1

ManagedLevel 2

AdaptiveLevel 4

AutonomicLevel 5


Multiple sources of


Requires extensive,


Basic Requirements

Met


actions through

managementtools




PredictiveLevel 3

Systemmonitors,

correlates and recommends

actions

IT staffapproves and

initiates actions

Reduced dependency on

deep skills

Faster/better decision making


Manual Autonomic

Ben

efi

tsS

kill

sC

har

acte

rist

ics

BasicLevel 1

ManagedLevel 2

PredictiveLevel 3

AutonomicLevel 5


Multiple sources of


Requires extensive,


Basic Requirements

Met


actions through

managementtools




Systemmonitors,


actions


initiates actions


deep skills


AdaptiveLevel 4

System monitors,

correlates and takes action

IT staff manages performance against SLAs

Balanced human/system

interaction

IT agility and resiliency


Manual Autonomic

Ben

efi

tsS

kill

sC

har

acte

rist

ics

BasicLevel 1

ManagedLevel 2

PredictiveLevel 3

AdaptiveLevel 4


Multiple sources of


Requires extensive,


Basic Requirements

Met


actions through

managementtools




Systemmonitors,


actions


initiates actions


deep skills


System monitors,

correlates and takes action

IT staff manages performance against SLAs

Balanced human/system

interaction

IT agility and resiliency

AutonomicLevel 5

Integrated components dynamically managed by

business rules/policies

IT staff focuseson enabling

business needs

Business policy drives IT

management

Business agility and resiliency


Architecture Framework

Common Autonomic construct for all system elements

Distributed components and systems integrated as one virtual operating system

Web Services Interfaces to elements

Web Services

System Mgmt Database

ISVSolutions

Servers Storage Network

Customer Applications

Application Servers

OGSAMeta OS Services

Industry standards arekey to the success of

Autonomic Computing

A Holistic Approach to Autonomic Computing

Architecture Framework


Core Building Blocks for an open architecture

Monitor Execute

Analyze Plan

Knowledge

Element

Sensors Effectors

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


Autonomic Architecture – SLA example

Customer Relationship Solutions

Collect runtime metrics

Monitor

Project SLAViolations

Analyze

Create CorrectiveAction plan

Plan

Execute plan before violations occur

Execute

Sensors EffectorsSLA

Example

An autonomic element is a function in a system that monitors activities and adjusts the system to meeting some goal.

Element

Monitor

Analyze

Sensors

Execute

Plan

Effectors

Knowledge

Autonomic Element

Au

ton

omic

Man

ager

Man

aged

Ele

men

tSensors Effectors


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 InterpreterAnalyze

Execute

Service Dispatcher

Distribution Engine

Scheduler Engine

Workflow Engine

Monitor

Metric Managers

Filters

Simple Correlators

Knowledge

Policy

CalendarTopology

Recent Activity Log

Sensors Effectors

Rules Engines

Analysis Engines

Policy Validations

Policy Resolution


Management and Manageability

Elements

M

AE

P

K

S E

M

AE

P

K

S E

A Touch Point Autonomic Manager is dedicated to a particular elements.

M

AE

P

K

S E M

AE

P

K

S E

M

AE

P

K

S E

Management tools deliver autonomic capability by implementing complete control loops.Management…

Capabilities that perform the work for managing IT resources.

Manageability... Instrumentation that make a particular IT resource manageable.

Risk Management

Workload ManagementConfiguration

Management


Multiple Contexts for Autonomic Behavior

System Elements(Intra-element

self-management)

Groups of Elements

(Inter-elementself-management)

Business Solutions(Business Policies,

Processes, Contracts)

ServerFarm

EnterpriseNetwork

StoragePool

Customer Relationship Management

EnterpriseResourcePlanning

Servers StorageNetworkDevices Middleware Database Applications


Autonomic Computing requires some core, foundational technologies

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 and Security Management

Auto-Detection

Dynamic Provisioning


Integrated Solutions Console for Common System Administration

Value: One consistent user interface across product

portfolio

Common runtime infrastructure and development tools based on industry standards, component reuse

Provides a presentation framework for other autonomic core technologies

...n

Customer pain point:Complexity of operations

Standards-based: J2EE, JSR168


Log and Trace Tool for Problem Determination

Value: Introduces standard interfaces and formats

for logging and tracing, key to building self-healing, self-optimizing autonomic system capabilities

Central point of interaction with multiple data sources

Correlated views of data

Reduced 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


eServer

Log

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 products

Consistent and up-to-date configuration and dependency data, key to building

self-configuring autonomic systems

Reduced deployment time with less errors

Reduced 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

InstallActions

InstallActions

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


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

Adaptation

Definition

Validation

Local Reposit

ory

Distribution

Enforcement

Point

Push or pull

Push or pull

Activate

Implement

MON ITOR

Facts

Analysis

Resource

……

Enforcement

Point

Resource

Resource


Policy is use to configure the system.

Measurable Intent

Specifications to describe observable behavior or objective.

Scope Specifications to identify what is or is not subject to the intent.

Pre-Conditions

Specifications to express when a policy is to be applied or is active.

BusinessValue

Specifications to express utility functions to make economic trade offs

Policy is a set of behavioral constraints and preferences that influences the decisions made by an autonomic manager.

Element

M

A

S

E

P

E

K

S E

“Plan” is the primary consumer of policy. It configures “M”, “A”, and “E” to meet objectives.

“Analyze” determine whether a policy is met or not.

Bus

ines

s V

alue

Pre

-C

ondi

tion

Scope

Measurable Intent


Business Workload Manager for Heterogeneous Workload Mgmt

Value:Response time measurement and

reporting of transaction processing segments

Dynamic learning of transaction workflow topology through servers and middleware

Drill-down through service class reporting to identify bottleneck processes

Tivoli Management ServereWLM integratedAll platforms (except OS/400)

Tivoli UIWeb Browser / ISCAll UI platforms

Coarse-Grained ManagementWindowsLinux / IntelSolarisLinux / z

Tivoli Agent - Detailed ReportingAIXz/OSOS/400WindowsLinux / IntelSolarisLinux / z

Customer pain point: Unable to definitively determine cause of bottleneck in system Standards-based:

ARM 4.0


Technologies for Implementing Autonomic Managers

Value: Components to simplify the incorporation of autonomic functions

into applications Building blocks for self-management

Monitoring, analysis, planning and execution components

Including autonomic computing technologies, grid tools, and services

PluggableDefines interfaces and provides implementations for each major toolkit component

Detailed examples and documentation for all components A complete implementation of a null autonomic manager which

can be extended through inheritance

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

Standards-based:OGSA, W3C


Putting It All Together – Technology Preview

Problem addressed: IT usage today has moved from static planned systems to e-business dynamic load

Provide dynamic surge protection: Monitors the response time of current users

Detects a rising response time in real time

Identifies type of extra load, validates surge or even predicts seasonal type peak

Adds capacity when it reasonably (intelligently) thinks it has to sustain « something bigger »

Releases capacity when the peak is over

Demo


Few minutes later…

An important scenario: Workload surge

Systems can go from steady state … Systems can go from steady state …

Internet

to overloaded without to overloaded without warning warning


Autonomic Computing: Dynamic Surge Protection

DatabaseWAS

Driver (simulates Internet in/out)

Surge Button

MonitoringConfiguration management

Sensor Effector

ControllerForecaster

Performance Modeler

Statistics /Knowledge

Element

Monitor

Analyze (Forecaster)

Sensors

Execute(Controller)

Plan(Perf Modeler)

Effectors

Knowledge


Response Time

Actual BOPS

Predicted BOPS

#Active Servers

#Requested Servers

11. Steady State


2. Monitor, Detect Surge

Response Time

Actual BOPS

Predicted BOPS

#Active Servers

#Requested Servers

1 2


3. Forecast, Provision Servers

Response Time

Actual BOPS

Predicted BOPS

#Active Servers

#Requested Servers

1 21 2 3


Response Time

Actual BOPS

Predicted BOPS

#Active Servers

#Requested Servers

4. Monitor, Remove Servers1 2 43


Homework

Autonomic computing systems are self managing and always available, analogous to the human autonomic nervous system depicted abstractly on the cover. Papers in this issue describe a variety of research projects in which the concepts of autonomic computing are being developed.

http://www.research.ibm.com/journal/sj42-1.html


Continuing the evolution of e-business

The journey has started... IBM is leading the way

The roadmap has been defined

Products and services are available today

Exciting new technologies based on open standards will increase the momentum

IBM customer and partner collaboration is key

Watch this space....!

Freeing customers to focus on their business instead of

their infrastructure


Autonomic Computing

Alan G. GanekVice PresidentIBM Autonomic Computing

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

Documents

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