SlideShare a Scribd company logo
Oracle Database Strategy  Oracle Database 11g  Charlie Garry, Director, Product Management Oracle Server Technologies
DO MORE WITH LESS
DO MORE WITH MORE
MORE SERVERS
MORE STORAGE
MORE SOFTWARE LICENSES
MORE COST
MORE COMPLEXITY
WHAT MUST BE DONE?
SIMPLIFY
FEWER THINGS TO MANAGE
FEWER KINDS OF THINGS
CURRENT COMPLEXITY DIFFICULT AND EXPENSIVE TO SCALE POOR UTILIZATION EXPENSIVE TO MANAGE RISKY TO CHANGE Middleware Database Storage Dedicated Stacks
THE SHARED INFRASTRUCTURE   Virtualizes and Pools IT Resources Sized for peak load Difficult to Scale Expensive to Manage Pools of shared resources Re-distribute resources as needed Cost efficient
Oracle Database 11g Release 2 Simplified Grid Provisioning New intelligent installer - 40% fewer steps to install RAC SCAN - Single cluster-wide alias for database connections Nodes can be easily repurposed © 2009 Oracle Corporation Back Office Front Office Depart/LOB Free
Consolidating All Your Data Images
Oracle Secure Files Consolidate Unstructured Data On the Grid Read Performance  Write Performance  Mb/Sec Mb/Sec File Size (Mb) File Size (Mb) Secure Files Linux Files Secure Files Linux Files
STORAGE CONSOLIDATION   ASM CLUSTER FILE SYSTEM ASM supports ALL data Database files File systems:  ACFS, 3 rd -party file systems Shared Clusterware files:  OCR and Voting disk now stored in ASM New in  11.2 DB Datafiles OCR and Voting Files Oracle Binaries 3 rd  Party File Systems Automatic Storage Management (ASM) File Systems Applications Databases
IMPROVE UTILIZATION RATES
The Price of Underutilized Servers Average CPU Utilization Rate Actual Software Cost Per CPU Purchase Price: $20K Per Processor Underutilized Premium
Grid Automated Quality of Service Resource (CPU) Sales Pools Most Important Least Important Search Pools BI Pools EMEA NA APAC Response Time Objectives Storage J2EE Web DB
The Price of Underutilized Storage 48 TB of Raw Storage Purchased at $5/GB Storage Utilization Rate
STORAGE UTILIZATION OPTIMAL DISK PLACEMENT AUTOMATIC STORAGE MANAGEMENT DESIGNATE DATA AS  HOT  or  COLD Infrequently  Accessed Data Frequently  Accessed Data © 2009 Oracle Corporation – Proprietary and Confidential New with  11.2
STORAGE UTILIZATION   ASM GROUPS: TIERED STORAGE
Tiered Approach is 83% Cheaper STORAGE UTILIZATION   ASM GROUPS: TIERED STORAGE $215,000 $4.30 50,000 1,250,000 $25 50,000 Totals 30,000 $1 30,000 JBOD TIERED STORAGE High-End STORAGE TYPE NON-TIERED STORAGE 50,000 TOTAL CAPACITY GB $25 PRICE PER GB $122,500 $7 17,500 Mid-Tier $62,500 $25 2,500 High-End 1,250,000 TOTAL PRICE PER GB TOTAL CAPACITY GB STORAGE TYPE TOTAL
Optimize I/O Performance Advanced OLTP Compression Compress large application tables Transaction processing, data warehousing Compress all data types Structured and unstructured data types Improve query performance Cascade storage savings throughout data center Compression 4X Up To © 2009 Oracle Corporation
OLTP Table Compression Process Initially Uncompressed Block Compressed Block Partially Compressed Block Compressed Block Empty  Block Legend Header Data Free Space Uncompressed Data Compressed Data
Block-Level  Batch  Compression Patent pending algorithm minimizes performance overhead and maximizes compression Individual INSERT and UPDATEs do not cause recompression Compression cost is amortized over several DML operations Block-level (Local) compression keeps up with frequent data changes in OLTP environments Others use static, fixed size dictionary table thereby compromising compression benefits Extends industry standard compression algorithm to databases Compression utilities such as GZIP and BZ2 use similar adaptive, block level compression
Exadata Smart Storage Breaks Data Bandwidth and Random I/O Bottleneck Oracle addresses data bandwidth bottleneck 4 ways Massively parallel storage grid  of high performance Exadata storage servers (cells).  Data bandwidth scales with data volume Data intensive processing  runs in Exadata storage.  Queries run in storage as data streams from disk, offloading database server CPUs Exadata Smart Flash Cache Increase random I/Os by factor of 20X Columnar compression reduces data volume up to 10x Exadata Hybrid Columnar Compression provides 10x lower cost, 10x higher performance Exadata Storage Cells New in  11.2
Oracle Exadata Storage Server Hybrid Columnar Compression Data stored by column and then compressed Useful for data that is  bulk  loaded or moved Query mode  for data warehousing Typical 10X compression ratios Scans improve accordingly Archival mode  for old data Typical 15X up to 50X compression ratios 50X Up To © 2009 Oracle Corporation
Real-World Compression Ratios Oracle Production E-Business Suite Tables Columnar compression ratios Query  = 14.6X Archive = 22.6X Vary by application and table 52
LOWER SUPPORT COSTS
CONSOLIDATED MANAGEMENT ENTERPRISE MANAGER GRID CONTROL RATIONALIZED MANAGEMENT OF A RATIONALIZED PLATFORM IMPROVED PROCESS MATURITY MORE REPEATABILITY MORE AUTOMATION MANAGEMENT COST AMORTIZED OVER MULTIPLE APPLICATIONS
Managing Complexity  Automated Self-management Automated: Storage Memory Statistics SQL tuning Backup and Recovery Advisory: Indexing Partitioning Compression Availability Data Recovery © 2009 Oracle Corporation
IMPROVE AVAILABILITY
Oracle Maximum Availability Architecture Eliminate the cost of planned downtime Add/Remove Storage Redefine and Reorganize Tables Online Production Testing Reporting Add/Remove Nodes and CPUS  Undo  Human Error Online Upgrades Online Patching
ADAPT TO CHANGE
TECHNOLOGIC OR ECONOMIC
FASTER
WITH LESS RISK
Make Change Safe -  Realistic Testing with Database Replay Recreate actual production database workload in test environment No test development required Replay workload in test with production timing Analyze & fix issues before production … … Capture DB Workload Middle   Tier Storage Oracle DB Replay DB Workload Production Test Test migration to RAC Client Client … Client
Make Change Safe –  Find Regressed SQL with SQL Performance Analyzer
SIMPLIFY
The Fastest Way to the Grid
Your IT Information Infrastructure In a Box Consolidation mixes many different workloads in one system Warehouse oriented  bulk data processing OLTP oriented  random updates Multimedia oriented  streaming files The Oracle Database Machine handles any combination of workloads with extreme performance And predictable response times Rationalize and Consolidate on Oracle Grid ERP CRM Warehouse Data Mart HR
Oracle Database Strategy  Oracle Database Oracle Database 11g and Beyond Simplify the information infrastructure Consolidate Rationalize Reduce Cost Improve utilization of the entire infrastructure Reduce operational expense Reduce Risk of Change Provision fixes Accurately test changes Rolling Upgrades
Oracle Database Strategy  Oracle Database 11g  Charlie Garry, Director, Product Management Oracle Server Technologies

More Related Content

PDF
Upgrade to a Dell EMC PowerEdge R740xd database server that harnesses the pow...
PDF
Performance benchmark results: Amazon Web Services (AWS) SAN in the Cloud vs....
PDF
EDB Postgres Replication Server
 
PPTX
EDB Database Servers and Tools
PPTX
How EDB Postgres helps achieve business continuity for database?
PPTX
Oracle Database Appliance (ODA) X6-2 Portfolio Overview
PPTX
Oracle Database Appliance
PDF
Oracle Database appliance - Value proposition Webcast
Upgrade to a Dell EMC PowerEdge R740xd database server that harnesses the pow...
Performance benchmark results: Amazon Web Services (AWS) SAN in the Cloud vs....
EDB Postgres Replication Server
 
EDB Database Servers and Tools
How EDB Postgres helps achieve business continuity for database?
Oracle Database Appliance (ODA) X6-2 Portfolio Overview
Oracle Database Appliance
Oracle Database appliance - Value proposition Webcast

What's hot (20)

PDF
Die 10 besten PostgreSQL-Replikationsstrategien für Ihr Unternehmen
 
PDF
Optimizing the Upstreaming Workflow: Flexibly Scale Storage for Seismic Proce...
PPT
Exadata
PDF
DBaaS with EDB Postgres on AWS
 
PDF
ODA X6-2 family
PDF
Panasas® activestor® and ansys
PDF
PanasasActiveStor
PDF
ActiveStor Performance at Scale
PDF
Cloud Migration Paths: Kubernetes, IaaS, or DBaaS
 
PDF
FAQ on Dedupe NetApp
PDF
A4 oracle's application engineered storage your application advantage
PPTX
Oracle Database Appliance X5-2
PPTX
Oracle 11gR2 plain servers vs Exadata - 2013
PPTX
Using SAS GRID v 9 with Isilon F810
PPTX
Data protection for oracle backup & recovery for oracle databases
PDF
20+ Million Records a Second - Running Kafka on Isilon F800
PPTX
ODA solution in-a-box
PDF
Panasas ® California Institute of Technology Success Story
PPT
How Data Instant Replay and Data Progression Work Together
PDF
Oracle Cloud Infrastructure – Compute
Die 10 besten PostgreSQL-Replikationsstrategien für Ihr Unternehmen
 
Optimizing the Upstreaming Workflow: Flexibly Scale Storage for Seismic Proce...
Exadata
DBaaS with EDB Postgres on AWS
 
ODA X6-2 family
Panasas® activestor® and ansys
PanasasActiveStor
ActiveStor Performance at Scale
Cloud Migration Paths: Kubernetes, IaaS, or DBaaS
 
FAQ on Dedupe NetApp
A4 oracle's application engineered storage your application advantage
Oracle Database Appliance X5-2
Oracle 11gR2 plain servers vs Exadata - 2013
Using SAS GRID v 9 with Isilon F810
Data protection for oracle backup & recovery for oracle databases
20+ Million Records a Second - Running Kafka on Isilon F800
ODA solution in-a-box
Panasas ® California Institute of Technology Success Story
How Data Instant Replay and Data Progression Work Together
Oracle Cloud Infrastructure – Compute
Ad

Similar to Frb Briefing Database (20)

PPT
11g R2
PPT
Oracle Database 11g Lower Your Costs
PPT
Oracle Exec Summary 7000 Unified Storage
PPTX
Tendencias Storage
PPTX
Exadata
PDF
3 storage innovations for improving performance, efficiency, and manageability
PPT
EMC IT's Best Practices
PDF
4 facing explosive data growth five ways to optimize storage for oracle datab...
PPTX
Advanced equal logic customer presentation
PPTX
Systems oracle overview_hardware
PPTX
Oracle-12c Online Training by Quontra Solutions
PPTX
ZFS appliance
PDF
Session 307 ravi pendekanti engineered systems
PPT
Présentation Oracle DataBase 11g
PDF
Revolutionary Storage for Modern Databases, Applications and Infrastrcture
PDF
MT47 Modernize infrastructure for a modern data center
PDF
Red hat Storage Day LA - Designing Ceph Clusters Using Intel-Based Hardware
PDF
32992 lam ebc storage overview3
PDF
OOW09 EBS Tech Essentials
PPTX
Oracle & sql server comparison 2
11g R2
Oracle Database 11g Lower Your Costs
Oracle Exec Summary 7000 Unified Storage
Tendencias Storage
Exadata
3 storage innovations for improving performance, efficiency, and manageability
EMC IT's Best Practices
4 facing explosive data growth five ways to optimize storage for oracle datab...
Advanced equal logic customer presentation
Systems oracle overview_hardware
Oracle-12c Online Training by Quontra Solutions
ZFS appliance
Session 307 ravi pendekanti engineered systems
Présentation Oracle DataBase 11g
Revolutionary Storage for Modern Databases, Applications and Infrastrcture
MT47 Modernize infrastructure for a modern data center
Red hat Storage Day LA - Designing Ceph Clusters Using Intel-Based Hardware
32992 lam ebc storage overview3
OOW09 EBS Tech Essentials
Oracle & sql server comparison 2
Ad

Recently uploaded (20)

PPTX
Detection-First SIEM: Rule Types, Dashboards, and Threat-Informed Strategy
PPTX
Understanding_Digital_Forensics_Presentation.pptx
PDF
Empathic Computing: Creating Shared Understanding
PPTX
PA Analog/Digital System: The Backbone of Modern Surveillance and Communication
PDF
Blue Purple Modern Animated Computer Science Presentation.pdf.pdf
PDF
Agricultural_Statistics_at_a_Glance_2022_0.pdf
PDF
cuic standard and advanced reporting.pdf
PPTX
20250228 LYD VKU AI Blended-Learning.pptx
PDF
Unlocking AI with Model Context Protocol (MCP)
PDF
TokAI - TikTok AI Agent : The First AI Application That Analyzes 10,000+ Vira...
PDF
Chapter 3 Spatial Domain Image Processing.pdf
PDF
The Rise and Fall of 3GPP – Time for a Sabbatical?
PPTX
Digital-Transformation-Roadmap-for-Companies.pptx
PDF
Architecting across the Boundaries of two Complex Domains - Healthcare & Tech...
PPTX
MYSQL Presentation for SQL database connectivity
PDF
Mobile App Security Testing_ A Comprehensive Guide.pdf
PDF
7 ChatGPT Prompts to Help You Define Your Ideal Customer Profile.pdf
PDF
Reach Out and Touch Someone: Haptics and Empathic Computing
PPT
Teaching material agriculture food technology
PDF
KodekX | Application Modernization Development
Detection-First SIEM: Rule Types, Dashboards, and Threat-Informed Strategy
Understanding_Digital_Forensics_Presentation.pptx
Empathic Computing: Creating Shared Understanding
PA Analog/Digital System: The Backbone of Modern Surveillance and Communication
Blue Purple Modern Animated Computer Science Presentation.pdf.pdf
Agricultural_Statistics_at_a_Glance_2022_0.pdf
cuic standard and advanced reporting.pdf
20250228 LYD VKU AI Blended-Learning.pptx
Unlocking AI with Model Context Protocol (MCP)
TokAI - TikTok AI Agent : The First AI Application That Analyzes 10,000+ Vira...
Chapter 3 Spatial Domain Image Processing.pdf
The Rise and Fall of 3GPP – Time for a Sabbatical?
Digital-Transformation-Roadmap-for-Companies.pptx
Architecting across the Boundaries of two Complex Domains - Healthcare & Tech...
MYSQL Presentation for SQL database connectivity
Mobile App Security Testing_ A Comprehensive Guide.pdf
7 ChatGPT Prompts to Help You Define Your Ideal Customer Profile.pdf
Reach Out and Touch Someone: Haptics and Empathic Computing
Teaching material agriculture food technology
KodekX | Application Modernization Development

Frb Briefing Database

  • 1. Oracle Database Strategy Oracle Database 11g Charlie Garry, Director, Product Management Oracle Server Technologies
  • 9. WHAT MUST BE DONE?
  • 11. FEWER THINGS TO MANAGE
  • 12. FEWER KINDS OF THINGS
  • 13. CURRENT COMPLEXITY DIFFICULT AND EXPENSIVE TO SCALE POOR UTILIZATION EXPENSIVE TO MANAGE RISKY TO CHANGE Middleware Database Storage Dedicated Stacks
  • 14. THE SHARED INFRASTRUCTURE Virtualizes and Pools IT Resources Sized for peak load Difficult to Scale Expensive to Manage Pools of shared resources Re-distribute resources as needed Cost efficient
  • 15. Oracle Database 11g Release 2 Simplified Grid Provisioning New intelligent installer - 40% fewer steps to install RAC SCAN - Single cluster-wide alias for database connections Nodes can be easily repurposed © 2009 Oracle Corporation Back Office Front Office Depart/LOB Free
  • 16. Consolidating All Your Data Images
  • 17. Oracle Secure Files Consolidate Unstructured Data On the Grid Read Performance Write Performance Mb/Sec Mb/Sec File Size (Mb) File Size (Mb) Secure Files Linux Files Secure Files Linux Files
  • 18. STORAGE CONSOLIDATION ASM CLUSTER FILE SYSTEM ASM supports ALL data Database files File systems: ACFS, 3 rd -party file systems Shared Clusterware files: OCR and Voting disk now stored in ASM New in 11.2 DB Datafiles OCR and Voting Files Oracle Binaries 3 rd Party File Systems Automatic Storage Management (ASM) File Systems Applications Databases
  • 20. The Price of Underutilized Servers Average CPU Utilization Rate Actual Software Cost Per CPU Purchase Price: $20K Per Processor Underutilized Premium
  • 21. Grid Automated Quality of Service Resource (CPU) Sales Pools Most Important Least Important Search Pools BI Pools EMEA NA APAC Response Time Objectives Storage J2EE Web DB
  • 22. The Price of Underutilized Storage 48 TB of Raw Storage Purchased at $5/GB Storage Utilization Rate
  • 23. STORAGE UTILIZATION OPTIMAL DISK PLACEMENT AUTOMATIC STORAGE MANAGEMENT DESIGNATE DATA AS HOT or COLD Infrequently Accessed Data Frequently Accessed Data © 2009 Oracle Corporation – Proprietary and Confidential New with 11.2
  • 24. STORAGE UTILIZATION ASM GROUPS: TIERED STORAGE
  • 25. Tiered Approach is 83% Cheaper STORAGE UTILIZATION ASM GROUPS: TIERED STORAGE $215,000 $4.30 50,000 1,250,000 $25 50,000 Totals 30,000 $1 30,000 JBOD TIERED STORAGE High-End STORAGE TYPE NON-TIERED STORAGE 50,000 TOTAL CAPACITY GB $25 PRICE PER GB $122,500 $7 17,500 Mid-Tier $62,500 $25 2,500 High-End 1,250,000 TOTAL PRICE PER GB TOTAL CAPACITY GB STORAGE TYPE TOTAL
  • 26. Optimize I/O Performance Advanced OLTP Compression Compress large application tables Transaction processing, data warehousing Compress all data types Structured and unstructured data types Improve query performance Cascade storage savings throughout data center Compression 4X Up To © 2009 Oracle Corporation
  • 27. OLTP Table Compression Process Initially Uncompressed Block Compressed Block Partially Compressed Block Compressed Block Empty Block Legend Header Data Free Space Uncompressed Data Compressed Data
  • 28. Block-Level Batch Compression Patent pending algorithm minimizes performance overhead and maximizes compression Individual INSERT and UPDATEs do not cause recompression Compression cost is amortized over several DML operations Block-level (Local) compression keeps up with frequent data changes in OLTP environments Others use static, fixed size dictionary table thereby compromising compression benefits Extends industry standard compression algorithm to databases Compression utilities such as GZIP and BZ2 use similar adaptive, block level compression
  • 29. Exadata Smart Storage Breaks Data Bandwidth and Random I/O Bottleneck Oracle addresses data bandwidth bottleneck 4 ways Massively parallel storage grid of high performance Exadata storage servers (cells). Data bandwidth scales with data volume Data intensive processing runs in Exadata storage. Queries run in storage as data streams from disk, offloading database server CPUs Exadata Smart Flash Cache Increase random I/Os by factor of 20X Columnar compression reduces data volume up to 10x Exadata Hybrid Columnar Compression provides 10x lower cost, 10x higher performance Exadata Storage Cells New in 11.2
  • 30. Oracle Exadata Storage Server Hybrid Columnar Compression Data stored by column and then compressed Useful for data that is bulk loaded or moved Query mode for data warehousing Typical 10X compression ratios Scans improve accordingly Archival mode for old data Typical 15X up to 50X compression ratios 50X Up To © 2009 Oracle Corporation
  • 31. Real-World Compression Ratios Oracle Production E-Business Suite Tables Columnar compression ratios Query = 14.6X Archive = 22.6X Vary by application and table 52
  • 33. CONSOLIDATED MANAGEMENT ENTERPRISE MANAGER GRID CONTROL RATIONALIZED MANAGEMENT OF A RATIONALIZED PLATFORM IMPROVED PROCESS MATURITY MORE REPEATABILITY MORE AUTOMATION MANAGEMENT COST AMORTIZED OVER MULTIPLE APPLICATIONS
  • 34. Managing Complexity Automated Self-management Automated: Storage Memory Statistics SQL tuning Backup and Recovery Advisory: Indexing Partitioning Compression Availability Data Recovery © 2009 Oracle Corporation
  • 36. Oracle Maximum Availability Architecture Eliminate the cost of planned downtime Add/Remove Storage Redefine and Reorganize Tables Online Production Testing Reporting Add/Remove Nodes and CPUS Undo Human Error Online Upgrades Online Patching
  • 41. Make Change Safe - Realistic Testing with Database Replay Recreate actual production database workload in test environment No test development required Replay workload in test with production timing Analyze & fix issues before production … … Capture DB Workload Middle Tier Storage Oracle DB Replay DB Workload Production Test Test migration to RAC Client Client … Client
  • 42. Make Change Safe – Find Regressed SQL with SQL Performance Analyzer
  • 44. The Fastest Way to the Grid
  • 45. Your IT Information Infrastructure In a Box Consolidation mixes many different workloads in one system Warehouse oriented bulk data processing OLTP oriented random updates Multimedia oriented streaming files The Oracle Database Machine handles any combination of workloads with extreme performance And predictable response times Rationalize and Consolidate on Oracle Grid ERP CRM Warehouse Data Mart HR
  • 46. Oracle Database Strategy Oracle Database Oracle Database 11g and Beyond Simplify the information infrastructure Consolidate Rationalize Reduce Cost Improve utilization of the entire infrastructure Reduce operational expense Reduce Risk of Change Provision fixes Accurately test changes Rolling Upgrades
  • 47. Oracle Database Strategy Oracle Database 11g Charlie Garry, Director, Product Management Oracle Server Technologies

Editor's Notes

  • #2: Reduce capital costs by factor of 5x Reduce storage costs by factor of 4x Improve performance by at least 10x Eliminate redundancy And much more….
  • #14: This simplified schematic is still representative of most enterprise data centers today. It is characterized by multiple networks, multiple storage technologies and hardware platforms, multiple operating systems and software technologies in a silo environment. For large enterprises this picture is duplicated across multiple data centers and it isn’t unusual for large enterprises to have 1000s servers and for even medium-sized enterprises to have 100s. Just keeping all these individual machines running is a mammoth task, but is made far more complex when multiple versions of operating systems are taken into account. Infrastructure Complexity arises from heterogeneous infrastructure + multiple OSs and S/W stack. This greatly complicates configuration management Infrastructure is inefficient because it is sized for peak loading, with redundancy and provision for failover. The single shot budget process means that IT wants to buy for the worst scenario based on estimated growth over a 3-5 year period. Typically each server only runs 1 or 2 applications. Requires multiple skill sets to manage and maintain Apps Monolithic – consequence of best-of-breed policies which also contributes to infrastructure heterogeneity Customisation and integration – impact on complexity and cost of ownership, retest everything when a change occurs Consequences Cost and effort involved in maintaining stability Inefficient and slow to react to changing needs in an increasingly unpredictable business world The silo approach created an isolated, static, expensive monolithic SMP and storage environment. While providing application owners greater control, they consume financial, human and environmental resources in a wasteful fashion compared to the alternative Oracle’s Grid Architecture offers. For large enterprises this picture is duplicated across multiple data centers and it isn’t unusual for large enterprises to have thousands of heterogeneous servers and for medium-sized enterprises to have hundreds. Just keeping all these individual machines running is a mammoth task, but is made far more complex when multiple versions of different operating systems are taken into account. The silo’d infrastructure is inefficient because it is sized for peak loading, with redundancy and provisioning of additional, often idle, resources for fail over. This results in the enterprise provisioning hardware and software for the worst-case scenario based on estimated workload growth over a 3-5 year period – an inefficient use of capital that in the early years generates little or no return. These heterogeneous environments also create problems when it’s time to upgrade or patch various system components. Invariably, multiple long outages are required to maintain these environments. Also, with the number of applications and organizations that comprise today’s businesses, it is hard to define, prioritize measure and ultimately maintain service level agreements. As the overall systems become stressed, what applications or users should give way to higher priority workloads? Does this happen in a predictable, disciplined way or is every occasion a fire drill? Oftentimes, these organizations are caught by surprise because of a slowly growing and unnoticeable change in workload volumes that all of the sudden emerges as a significant performance problem.
  • #15: On the right is a depiction of the Grid Computing Infrastructure Grid Computing is a technology architecture that virtualizes and pools IT resources, such as compute power, storage and network capacity into a set of shared services that can be distributed and re-distributed as needed. It is applicable for database, system, and storage administrators who seek a high performance, scalable, manageable systems infrastructure that offers industry-leading cost savings.
  • #22: Slide Goal: To provide a virtual demonstration of the product in action. SLIDE IS ANIMATED Modern application performance is made up of several interlocking pieces that span the technology stack. Much effort has been focused on delivering and deploying an application. However, this is not ultimately what an end-user sees. The end-user experience is defined by the runtime performance of an application. While many tools allow for monitoring an application’s this, it is not enough. What is required is Active runtime quality of service management that can both identify bottlenecks and adjust resources to ensure the most important applications maintain their required levels across ever-changing demand. Here we have an RTI datacenter with 3-tier and 2-tier systems operating within their response time objectives. We have 3 Pools in each of the top three tiers and a common storage pool for a total of 10 managed pools. <CLICK> Demand for the EMEA Sales application rises the SLO is violated. 2. <CLICK> The QoS system compensates by adjusting a resource such as CPU shares while still meeting objectives. 3. <CLICK>Suddenly our most important DB server pool goes red for all Sales apps. 4. <CLICK>Resources, such as a server, are reallocated from our least important DB server group to restore performance We are instrumenting the entire Oracle stack to enable us to provide true QoS management thereby allowing you in the end to effectively run your applications on “cruise control”.
  • #24: Leverage disk performance regions on disk drives 50% performance difference from outer to inner tracks Mark an ASM file to be HOT/COLD Alter diskgroup dgname modify file ‘xxx’ attributes HOT/COLD or based on a template at creation time Rebalance to migrate the ‘file’ to HOT/COLD ODP region ODP regions are dynamic New V$ASMFILE recording IO stats The ODP feature better leveraged when ASM disks are whole disks Dynamic, fast, space efficient, “point in time” copies of ASM file system files captures ASM FS file block/extent updates An enabler for: On-line backups On-line, disk-based, file backup model using snapshots and individual file recoveries Up to 64 snapshot images per ASM file system Policy based snapshots: Schedule snapshots on an interval basis: every 5 seconds, every 30 minutes, daily, … with recycling (using EM) ACFS CLIs support creation and removal of snapshots ACFS Snapshot functions integrated with EM
  • #32: Compression ratios based on Hybrid Columnar Compression “Query Default” and “Archive High”
  • #35: Automated:
  • #48: Reduce capital costs by factor of 5x Reduce storage costs by factor of 4x Improve performance by at least 10x Eliminate redundancy And much more….