End-to-end Management with Grid Control. John Abrahams Technology Sales Consultant Oracle Nederland B.V.

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2 End-to-end Management with Grid Control John Abrahams Technology Sales Consultant Oracle Nederland B.V.

3 Agenda End-to-end management with Grid Control Database Performance Management

4 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

5 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.

6 Application Performance Management Availability Management Oracle Enterprise Manager 10g Application Performance Management Transaction Performance End-User Performance Cross-Tier Tracing SLA Management Modeling End-User Communities Alerts Notifications Root Cause Analysis Trending Impact Analysis Oracle Eco-System Non-Oracle Systems

7 Integrated One Tool Lowers Learning Curve, Improves Quality of Service Administration Monitoring Provisioning Security Enterprise Manager

8 Managing Groups Manage Groups of Systems as a Single Unit Applications Sets of Systems 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

9 Task Automation Automate Operations Across Large Sets of Systems Job System EM 10g 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

10 Policy-Based Standardization Drives Consistency and Automation Policy Policy Management Types Rule definitions Violation detection Corrective action Performance policies Security policies Configuration policies

11 Grid-ready Framework Manages Large Sets of Systems with Minimal Incremental Cost Policy Manager Job System Group Manager Configuration Management Performance Monitoring Grid Control Repository

12 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

13 Architecture: Overall design HTML Console HTTP/S HTTP/S Mobile Device HTTP/S Firewall Portals HTTP/S Open Repository

14 Deployment Life-Cycle Oracle Inventory Software Configurations Hardware Configurations Discover Enterprise Manager Analyze View/Search Compare/Diff Change Tracking Reference Configurations Install/Clone Configure Provision LiveLink Oracle.com Product Updates Patch Patches Secure Product Configuration

15 Provisioning Capacity-on-Demand Automated addition/reallocation of servers Grid Deployments Key operations Software cloning Software patching Cluster configuration management Security

16 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 1 Select Software (and Instances) to Clone 2 Clone to Selected Targets 3 Update Inventory

17 Cloning Database Clone an Entire Database Including software Data+Schema Cloning Schema and data (subset) cloning Version and platform independent Add/Remove nodes from RAC clusters

18 Automated Patch Application Real-time discovery of new patches Security patch rapid deployment dramatically reduces vulnerabilities Grid-wide automated application reduces down-time from human error 2 Determine Applicability Enterprise Manager 1 Patch Published 3 Apply Patch 4 Repository Update Inventory

19 Automated Patching

20 Demonstration Grid Control

21 Agenda End-to-end management with Grid Control Database Performance Management

22 Ongoing System Management 55% of DBA s time is spent in ongoing management, monitoring and tuning #1 Cause: Performance Diagnosis & Troubleshooting Resource Tuning Source: IOUG 2001 DBA Survey

23 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!

24 Oracle 10g Manageability Out of Box Installation Fast, lightweight install including Automated Pre and Post Install Steps Installation Media Optimization Easy, fast client install Enhanced silent install for ISVs Data Load Data Pump Cross-Platform Transportable TS Restartable Data Load Ongoing System Management Automatic Storage Management Automatic Shared Memory Tuning Advisors Out of the Box Segment Advisor Undo Advisor Redo Log file Size Advisor Automatic Undo Retention Alert generation, out of the box thresholds Resource Manager 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 Console..and a lot more Automatic Backup Management * Not a comprehensive list

25 Database Diagnostics Pack Key Features 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

26 Database Tuning Pack Key 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 costeffective solution for application tuning

27 Intelligent Infrastructure Overview Storage Management Advisory Infrastructure Application & SQL Management Server-generated Alert Infrastructure System Resource Management Automatic Maintenance Task Infrastructure Backup & Recovery Space Management Database Management Manageme Automatic Intelligent Workload Infrastructure Repository 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, Outof-the-box Advisory Infrastructure Integrated, uniformity ADDM, SQL Tuning and other Advisors

28 Automatic Workload Repository (AWR) 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

29 Intelligent Infrastructure: New Base Statistics Extensive code instrumentation Time Model (v$sys_time_model) Java Exec Automatic Tracking of Operation Times DB time Connection Management (logon, logoff) SQL Exec Parse (hard, soft, failed,..) SQL, PLSQL and Java execution times Wait Model (v$system_event) Wait Events Categorized Based On Solution Area 800+ different wait events =>12 wait classes (Appln, Concurrency..) OS Stats (v$osstat) CPU + Memory SQL statement statistics Parse Conn Mgmt PLSQL Exec Wait class: PLSQL, Java, etc time Sampled bind values (v$sql_bind_capture) Efficient Top SQL identification using s in the kernel, by dimensions

30 Intelligent Infrastructure: Active Session History (ASH) Samples active sessions every second into memory (v$active_session_history) Direct access to kernel structures Selected samples flushed to AWR Data captured includes: SID SQL ID Program, Module, Action Wait event# Object, File, Block actual wait time (if captured while waiting) Sampled history of Active Sessions (v$session_wait)

31 Active Session History (ASH) Query for Melanie Craft Novels Browse and Read Reviews Add item to cart Checkout using one-click DB Time

32 Active Session History (ASH) Query for Melanie Craft Novels Browse and Read Reviews Add item to cart Checkout using one-click DB Time Time 7:38:26 7:42:35 7:50:59 7:52:33 SID Module SQL ID State Book by author Get review id qa324jffritcf aferv5desfzs5 WAITING CPU Fine Grained Activity History Add to cart hk32pekfcbdfr WAITING One click abngldf95f4de WAITING Event db file sequential read buffer busy wait log file sync

33 Automatic Database Diagnostic Monitor (ADDM) Storage Management Backup & Recovery Management Application & SQL Management Database Management Intelligent Infrastructure System Resource Management Space Management 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

34 How Does ADDM Work? High-load SQL SQL Advisor Snapshots in Automatic Workload Repository Automatic Self-Diagnostic Diagnostic Engine Engine IO / CPU issues System Resource Advice RAC issues 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

35 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

36 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

37 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

38 Oracle 10g Automates the SQL Tuning Process I can do it for you! ADDM High-Load SQL DBA SQL Workload SQL Tuning Advisor

39 Automatic SQL Tuning Overview Automatic Tuning Optimizer Statistics Analysis SQL Tuning Advisor SQL Tuning Recommendations Gather Missing or Stale Statistics SQL Profiling Create a SQL Profile Access Path Analysis Add Missing Indexes DBA SQL Structure Analysis Modify SQL Constructs

40 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

41 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

42 SQL Profiling Flow SQL Profiling SQL Tuning Advisor submit Optimizer (Tuning Mode) create use SQL Profile After Database Users submit Optimizer (Normal Mode) output Well-Tuned Plan

43 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

44 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

45 SQL Access Advisor Workload SQL Access Advisor Indexes Materialized Views Materialized View Logs

46 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

47 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

48 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

49 SQL Access Advisor Workload SQL Access Advisor Indexes Materialized Views Materialized View Logs

50 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

51 Usage Scenarios Filter Options Cursor Cache User Defined Hypothetical Workload STS SQL Access Advisor

52 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

53 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

54 Demo Database Performance Tuning

55 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

56 Q U E S T I O N S A N S W E R S

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