End-to-end Management with Grid Control

John AbrahamsTechnology Sales Consultant

Oracle Nederland B.V.

Agenda

� End-to-end management with Grid Control� Database Performance Management

Challenges

� Complexity of applications– Heterogeneous and distributed systems– Expensive and time consuming to manage

� Optimize application service levels– Better availability– Superior performance

� Drive down labor costs – Manage more with less– Eliminate human error

What is Enterprise Manager 10g Grid Control?

� Oracle’s grid-ready framework, allowing IT professionals to manage the entire Oracle eco-system through one integrated management console.

Oracle Eco-System

Application Performance Management

AvailabilityManagement

Oracle Enterprise Manager 10g

NotificationsModeling End-UserCommunities

Root Cause Analysis

Alerts Trending

TransactionPerformance

End-User Performance

Cross-TierTracing

Application Performance Management

SLA Management

Non-Oracle Systems

Impact Analysis

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IntegratedOne Tool Lowers Learning Curve, Improves Quality of Service

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AdministrationMonitoring

ProvisioningSecurity

EnterpriseManager

Managing Groups

� Logical modeling of sets of systems

– Applications, Clusters– Leveraged by all services –

Jobs, Policies, …

� Managed from a single-view– Monitoring and automated

operations

� Membership-based inheritance

Applications

Sets of Systems

Manage Groups of Systems as a Single Unit

Task Automation

� Designed for large number of targets

� Multiple job types– OS command, SQL, …

� Pre-packaged jobs– Backup, startup/shutdown, patch,

clone, …

� Ad hoc job creation – Custom scripts

EM 10g

Job System

Automate Operations Across Large Sets of Systems

Policy-Based Standardization

� Policy Management– Rule definitions

– Violation detection

– Corrective action

� Types– Performance policies

– Security policies

– Configuration policies

Drives Consistency and Automation

Policy

Grid Control

Repository

• Policy Manager

• Job System

• Group Manager

• Configuration Management

• Performance Monitoring

Grid-ready FrameworkManages Large Sets of Systems with Minimal Incremental Cost

Grid-ready Framework

Architecture Goals

� Zero-implementation, Zero time-to-value� Access by Anybody, Anywhere� Open Repository Schema� Easy extensibility and customization� Support of Standards� Scalability, robustness and self-maintenance

Architecture: Overall design

Fire

wal

l

Mobile Device

HTML Console

Portals

HTTP/S

HTTP/S

HTTP/S

HTTP/S

Open Repository

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LiveLink

Oracle.com

Product Updates

Patches

ProductConfiguration

EnterpriseManager

View/Search

Compare/Diff

Change Tracking

ReferenceConfigurations

Analyze

OracleInventory

SoftwareConfigurations

HardwareConfigurations

Discover

Install/Clone

Configure

Patch

Secure

Provision

Deployment Life-Cycle

Provisioning

� Capacity-on-Demand– Automated addition/reallocation of servers– Grid Deployments

� Key operations– Software cloning– Software patching– Cluster configuration management– Security

Software Cloning

� Reduce manual labor in software life-cycle– From hours to minutes

� Automate mass provisioning of reference systems� Intelligent Cloning makes context-specific

adjustments– DB: home, host name, listener– iAS: IP address, host name, web listener

UpdateInventory

Clone to Selected Targets

2

3

Select Software (and Instances) to Clone1

Cloning – Database

� Clone an Entire Database– Including software

� Data+Schema Cloning– Schema and data (sub-

set) cloning– Version and platform

independent

� Add/Remove nodes from RAC clusters

Automated Patch Application

Repository

Enterprise Manager

Patch Published1

DetermineApplicability

2

Apply Patch3

UpdateInventory

4

� Real-time discovery of new patches� Security patch rapid deployment dramatically reduces vulnerabilities

� Grid-wide automated application reduces down-time from human error

Automated Patching

DemonstrationGrid Control

Agenda

� End-to-end management with Grid Control� Database Performance Management

Ongoing System Management

55% of DBA’s time is spent in ongoing management, monitoring and tuning

#1 Cause:Performance Diagnosis & TroubleshootingResource Tuning

Source: IOUG 2001 DBA Survey

Traditional Performance Tuning

� Performance and Workload Data Capture– System Statistics, Wait Information, SQL Statistics, etc.

� Analysis– What types of operations database is spending most time

on?– Which resources is the database bottlenecked on?– What is causing these bottlenecks?– What can be done to resolve the problem?

� Problem Resolution– If multiple problems identified, which is most critical?– How much performance gain expected if is solution

implemented?Oracle10g Database and Diagnostics Pack Automates All Steps

and Addresses All Issues & Challenges!

..and a lot moreAutomatic Backup

Management

Oracle 10g Manageability Out of Box

InstallationFast, lightweight install

including Automated Pre and Post Install Steps

Installation Media Optimization

Easy, fast client installEnhanced silent install

for ISVs

Simplified Creation & Configuration

Pre-configured Database

90% Reduction in Configuration parameters

Automatic setup of common tasks, backups, stats gathering etc

Out of of Box Database ConsoleData Load

Data PumpCross-Platform

Transportable TSRestartable Data Load

Ongoing System ManagementAutomatic Storage ManagementAutomatic Shared Memory TuningAdvisors Out of the Box

Segment AdvisorUndo AdvisorRedo Log file Size AdvisorAutomatic Undo Retention

Alert generation, out of the box thresholds

Resource Manager

* Not a comprehensive list

� Automatic Performance Diagnosis– Self Diagnostic engine built into core database kernel,

Automatic Database Diagnostic Monitor (ADDM) – Automatic Workload Capture and Historical Performance

Analysis (Automatic Workload Repository)– Comprehensive System (Database & OS) Performance

Monitoring– Advanced Event Management

� When Used With Grid Control– Manages Large Sets of Databases and other Oracle

infrastructure– Cross-system Performance and Availability aggregation– Seamlessly Integrates With Application Server Diagnostic

Pack

Database Diagnostics PackKey Features

� Requires and Seamlessly Integrates with Database Diagnostic Pack

� Tuning pack solutions include– SQL Tuning Advisor– SQL Access Advisor– Object Reorganization Wizard

� Provides comprehensive, automatic, and cost-effective solution for application tuning

Database Tuning PackKey Features

Intelligent Infrastructure Overview

� Automatic Workload Repository – “Data Warehouse” of Database– Code instrumentation

� Automatic Maintenance Tasks– Pre-packaged, resource

controlled� Server-generated Alerts

– Push vs. Pull, Just-in-time, Out-of-the-box

� Advisory Infrastructure– Integrated, uniformity– ADDM, SQL Tuning and other

Advisors

Intelligent Infrastructure

Application & SQLManagement

System ResourceManagement

SpaceManagement

Backup & RecoveryManagement

StorageManagement

Database Manageme

ntAutomatic Workload Repository

Automatic Maintenance Task Infrastructure

Server-generated Alert Infrastructure

Advisory Infrastructure

� Built-in Workload and Performance Statistics Repository Within Database

� Part of Oracle Database 10g Intelligent Self-Management Infrastructure

� Automatically Captures Workload Data• Every 60 minutes, or manually, saves data for 7 days by default

• Resides in Newly Introduced SYSAUX Tablespace• Server Automatically Manages Space Requirements

• Old Data is automatically purged• Stores different classes of data:

– BASE STATISTICS e.g. physical reads– SQL STATISTICS e.g. disk reads (per sql stmt)– METRICS e.g. physical reads / sec– ACTIVE SESSION HISTORY

Automatic Workload Repository (AWR)

Intelligent Infrastructure: New Base Statistics Extensive code instrumentation

� Time Model (v$sys_time_model)– Automatic Tracking of Operation Times– DB time– Connection Management (logon, logoff)– Parse (hard, soft, failed,..)– SQL, PLSQL and Java execution times

� Wait Model (v$system_event)– Wait Events Categorized Based On Solution Area– 800+ different wait events =>12 wait classes (Appln, Concurrency..)

� OS Stats (v$osstat)– CPU + Memory

� SQL statement statistics– Wait class: PLSQL, Java, etc time– Sampled bind values (v$sql_bind_capture)– Efficient Top SQL identification using �s in the kernel, by dimensions

SQL Exec

PLSQL Exec

Conn MgmtParse

Java Exec

Intelligent Infrastructure: Active Session History (ASH)

Sampled history of Active Sessions (v$session_wait)

• Samples active sessions every second into memory (v$active_session_history)

• Direct access to kernel structures• Selected samples flushed to AWR• Data captured includes:

– SID – SQL ID– Program, Module, Action – Wait event# – Object, File, Block– actual wait time (if captured while waiting)

DB Time

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Active Session History (ASH)

DB Time

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WAITING

Statedb file sequential readqa324jffritcf2137:38:26

EventSQL IDModuleSIDTime

CPUaferv5desfzs5Get review id2137:42:35

WAITING log file syncabngldf95f4deOne click2137:52:33

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Active Session History (ASH)

Fine Grained Activity History

Automatic Database Diagnostic Monitor (ADDM)

� Self-Diagnostic Engine In the Database

� Integrate all components together

� Automatically provides database-wide performance diagnostic, including RAC

� Real-time results using the Time Model

� Provides impact and benefit analysis, non problem areas

� Provides Information vs. raw data

� Runs proactively out of the box, reactively when required

Intelligent Infrastructure

Application & SQLManagement

System ResourceManagement

SpaceManagement

Backup & RecoveryManagement

StorageManagement

Database Management

SQLAdvisor

High-load SQL

IO / CPU issues RAC issues

Automatic Diagnostic Engine

Snapshots inAutomatic Workload

Repository

Self-Diagnostic Engine

System Resource

Advice

Network + DB config

Advice

� Top Down Analysis Using AWR Snapshots

� Throughput centric - Focus on reducing time ‘DB time’

� Classification Tree - based on decades of Oracle performance tuning expertise

� Real-time results – Don’t need to wait hours to

see the results)

� Pinpoints root cause– Distinguishes symptoms

from the root cause

� Reports non-problem areas– E.g. I/O is not a problem

How Does ADDM Work?

Top Performance Issues Automatically Diagnosed by ADDM

� Not Rocket Science Any More– Top SQL– I/O Issues

� Hot Files, Bandwidth– Parsing

� Hard, Soft, Failed– Configuration Issues

� Log File Sizing� Log Buffer Sizing� Archiving� MTTR Setting

– Application Usage

� Not Diagnosable by Statspack– Excessive Logon/Logoff– Undersized Memory

� SGA, PGA– Hot Blocks and Objects

� Buffer Busy Waits� Cache Buffer Chain

Latches– RAC Service Issues

� Network, LMS, Remote Instance

– Locks & ITL contention– Checkpoint causes– PL/SQL, Java Time

Intelligent Infrastructure: Performance Overhead

� 2-3% Overhead for the Overall Infrastructure enabled by default

– Validated with real world customers for large, busy databases in production

– Most real-world system are not tuned generally and hence can benefit significantly

“New Age” Performance Tuning Methodology

� Start at the EM Performance Page– Assess the nature of the problem (transient or

otherwise)

� For non-transient problems, look at the relevant ADDM findings

� For transient problems, or for pre-Oracle10g databases

– Use EM Drill downs

Oracle 10g Automates the SQL Tuning Process

I can do it for you !

SQL Tuning Advisor

DBAHigh-Load

SQL

ADDM

SQLWorkload

Automatic SQL Tuning Overview

Add Missing Indexes

Modify SQL Constructs

Create a SQL Profile

Automatic Tuning Optimizer

SQL Structure Analysis

Access Path Analysis

SQL Profiling

Statistics Analysis

Gather Missing or Stale Statistics

DBA

SQL TuningRecommendations

SQL Tuning Advisor

Automatic Tuning Optimizer (ATO)

� It is the query optimizer running in tuning mode– Uses same plan generation process but performs

additional steps that require lot more time

� It performs verification steps– To validate statistics and its own estimates

� Uses dynamic sampling and partial executions to validate

� It performs exploratory steps– To investigate the use of new indexes that could

provide significant speed-up– To analyze SQL constructs that led to expensive

plan operators

SQL Profiling� Motivation

– Empower query optimizer to find better plan by gathering additional information on query behavior

� The query optimizer has time constraints– Makes compromises while finding right plan

� The ATO is allowed a lot more time– Uses the time to gather customized information

about the SQL statement, known as SQL Profile– Builds a SQL Profile and recommends it– Once implemented, SQL Profile is used by the

query optimizer to generate a well-tuned plan

SQL Profiling Flow

Optimizer(Tuning Mode)

createsubmit

SQL Profiling

Optimizer(Normal Mode)

outputsubmit

SQL Profile

SQL TuningAdvisor

DatabaseUsers

Well-TunedPlan

After …

use

SQL Tuning Set (STS)

� Motivation– Enable user to tune custom set of SQL statements

� New object in Oracle10g for capturing and managing SQL workload

� Stores SQL statements along with:– Execution context: parsing user, bind values, etc.– Execution statistics: buffer gets, CPU time, elapse

time, number of executions, etc.

� Created from any SQL source– Sources: AWR, cursor cache, user-defined SQL

workload, another STS

SQL Tuning Set Benefits

� Allows selective, on-demand, custom SQL workload tuning

� Simplifies tuning of large number of SQL statements

� Is persistent� Provides a common infrastructure for dealing

with SQL workloads– Can be used as a source for different tuning tasks

SQL Access Advisor

Workload

Indexes Materialized ViewsMaterialized View Logs

SQL Access Advisor

SQL Access Advisor Features

� De-mystifies access structure design for optimal application performance

� Recommends indexes, materialized views, and materialized view logs to create and/or drop for faster performance

� Analyzes entire workload and not just independent SQL statements

� Takes into account impact of new access structures on DML operations

� Considers storage, creation and maintenance costs

SQL Tuning Set (STS)

� Motivation– Enable user to tune custom set of SQL statements

� New object in Oracle10g for capturing and managing SQL workload

� Stores SQL statements along with:– Execution context: parsing user, bind values, etc.– Execution statistics: buffer gets, CPU time, elapse

time, number of executions, etc.

� Created from any SQL source– Sources: AWR, cursor cache, user-defined SQL

workload, another STS

SQL Tuning Set Benefits

� Allows selective, on-demand, custom SQL workload tuning

� Simplifies tuning of large number of SQL statements

� Is persistent� Provides a common infrastructure for dealing

with SQL workloads– Can be used as a source for different tuning tasks

SQL Access Advisor

Workload

Indexes Materialized ViewsMaterialized View Logs

SQL Access Advisor

SQL Access Advisor Features

� De-mystifies access structure design for optimal application performance

� Recommends indexes, materialized views, and materialized view logs to create and/or drop for faster performance

� Analyzes entire workload and not just independent SQL statements

� Takes into account impact of new access structures on DML operations

� Considers storage, creation and maintenance costs

Usage Scenarios

WorkloadUser Defined

Hypothetical

Cursor Cache

Filter Options

STS

SQL Access Advisor

Filter Options

� Don’t have to use the entire workload� Filter by

– Application or module name– Number of SQL statements– Queries during a specified time window– Username– Tables

� must be in this list� not in this list

Filter Options

� Don’t have to use the entire workload� Filter by

– Application or module name– Number of SQL statements– Queries during a specified time window– Username– Tables

� must be in this list� not in this list

Demo Database Performance Tuning

Conclusion� Automates management of performance issues for

the Oracle Database– Automatic Performance Diagnosis– Guided problem resolution– Graphical, intuitive and easy to use – “Point & Click”

� Adds significant business value– Eliminates Fire drills – Enables higher QoS– Enhances DBA’s quality of life and productivity – Makes available more resources to focus on strategic

initiatives

Q U E S T I O N SQ U E S T I O N SA N S W E R SA N S W E R S