John Campbell  IBM Distinguished Engineer How to reduce costs, increase capacity and achieve Continuous Availability with ...
John Campbell - Introduction   <ul><li>IBM Distinguished Engineer </li></ul><ul><li>Member of IBM Academy of Technology </...
Agenda <ul><li>What is DB2 Data Sharing ? </li></ul><ul><li>Why Go to DB2 Data Sharing </li></ul><ul><li>Parallel Sysplex ...
DB2 Data Sharing Definitions <ul><li>DB2 data sharing – allows applications running on more than one DB2 subsystem to read...
Why Go to DB2 Data Sharing? <ul><li>General drivers: </li></ul><ul><ul><li>Capacity : outgrow single system size </li></ul...
Parallel Sysplex (PSX) <ul><li>Scalable Capacity  </li></ul><ul><li>Flexible Configuration </li></ul><ul><li>Workload Bala...
DB2 Data Sharing Architecture IRLM Buffer Pools DB2A Coupling Facilities LOCK1 Group Buffer Pools 1 12 2 3 4 5 6 7 8 9 10 ...
Design for Continuous Availability <ul><li>Single points of failure eliminated: </li></ul><ul><ul><ul><li>DB2 subsystem or...
DB2 Member Outage – Planned <ul><li>&quot;Rolling&quot; maintenance </li></ul><ul><li>One DB2 or LPAR can be stopped at a ...
DB2 Member Outage – Unplanned <ul><li>The other &quot;surviving&quot; members  remain up and running </li></ul><ul><li>The...
Dynamic Workload Balancing <ul><li>Workload Manager (WLM) </li></ul><ul><li>CICSPlex System Manager (CPSM) </li></ul><ul><...
Data Sharing Performance Summary <ul><li>CPU cost of data sharing varies based on: </li></ul><ul><ul><li>CF access intensi...
DB2 Data Sharing OLTP Scalability <ul><li>IMS/TM with DB2 V4 OLTP workload </li></ul><ul><li>96.75% of ideal scalability f...
Data Sharing Performance in Production <ul><li>Host CPU effect with primary application involved in data sharing </li></ul...
Application Changes ? <ul><li>SQL interface does not change </li></ul><ul><li>However, locking and commit frequency may im...
Customers using DB2 Data Sharing
Why should you exploit DB2 Data Sharing ? <ul><li>Continuous Availability  for critical applications in terms of infrastru...
Continuous Availability <ul><li>Pain Points </li></ul><ul><ul><li>Individual applications currently boxed and isolated </l...
Enhanced Operational Capability and Return On Investment <ul><li>Have you already invested heavily in system infrastructur...
Low Implementation Risk <ul><li>Well proven technology </li></ul><ul><li>Widespread deployment around WW global banking co...
CheckFree – Real Customer Experience
Summary & Next Steps
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DB2 for z/O S Data Sharing

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How to reduce costs, increase capacity and achieve Continuous Availability with IBM DB2 Data Sharing! The “Ultimate” Data Server !

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DB2 for z/O S Data Sharing

  1. 1. John Campbell IBM Distinguished Engineer How to reduce costs, increase capacity and achieve Continuous Availability with IBM DB2 Data Sharing ! The “Ultimate” Data Server !
  2. 2. John Campbell - Introduction <ul><li>IBM Distinguished Engineer </li></ul><ul><li>Member of IBM Academy of Technology </li></ul><ul><li>Provide leadership to WW customers in high-end database, transaction, and application systems - consultancy, design, performance and benchmarking </li></ul><ul><li>Based on customer experience drives direction of DB2 product and associated products across IBM Corporation </li></ul><ul><li>Performance Team Leader for release of DB2 Data Sharing </li></ul>
  3. 3. Agenda <ul><li>What is DB2 Data Sharing ? </li></ul><ul><li>Why Go to DB2 Data Sharing </li></ul><ul><li>Parallel Sysplex and Data Sharing Architecture </li></ul><ul><li>DB2 Data Sharing </li></ul><ul><ul><li>Continuous Availability </li></ul></ul><ul><ul><li>Dynamic Workload Balancing </li></ul></ul><ul><ul><li>What about Performance and Scaling? </li></ul></ul><ul><ul><li>What about Application Changes? </li></ul></ul><ul><li>Real Customer Scenarios </li></ul><ul><li>Next Steps </li></ul>
  4. 4. DB2 Data Sharing Definitions <ul><li>DB2 data sharing – allows applications running on more than one DB2 subsystem to read and write to the same set of data concurrently . </li></ul><ul><li>DB2 data sharing – allows customers to provide highest level of scalability, performance and continuous availability to enterprise applications that use DB2 data. </li></ul>DB2A DB2B DB2n . . . Coupling Facilities
  5. 5. Why Go to DB2 Data Sharing? <ul><li>General drivers: </li></ul><ul><ul><li>Capacity : outgrow single system size </li></ul></ul><ul><ul><ul><li>Avoid splitting the databases </li></ul></ul></ul><ul><ul><li>Continuous availability requirements </li></ul></ul><ul><ul><ul><li>Protect against planned and unplanned outages </li></ul></ul></ul><ul><ul><li>Easier growth accommodation and cost effectiveness </li></ul></ul><ul><ul><ul><li>Need scalable, non-disruptive growth </li></ul></ul></ul><ul><ul><li>Dynamic workload balancing </li></ul></ul><ul><ul><ul><li>Effective utilization of available MIPS for mixed workloads </li></ul></ul></ul><ul><ul><ul><li>Handle unpredictable workload spikes </li></ul></ul></ul><ul><ul><li>System consolidation for easier systems management </li></ul></ul><ul><li>Application Investment Protection </li></ul><ul><ul><li>SQL interface is unchanged for data sharing </li></ul></ul><ul><ul><li>Applications do not need to become &quot;cluster aware&quot; </li></ul></ul><ul><ul><li>“ Turbo Charger” for existing applications </li></ul></ul><ul><ul><li>Most known DB2 members: 17-way </li></ul></ul>
  6. 6. Parallel Sysplex (PSX) <ul><li>Scalable Capacity </li></ul><ul><li>Flexible Configuration </li></ul><ul><li>Workload Balancing </li></ul><ul><li>7x24 Availability </li></ul><ul><li>Single System Image </li></ul><ul><li>PSX Components: </li></ul><ul><ul><li>Sysplex Timers </li></ul></ul><ul><ul><li>Coupling Facility (CF) - LPARs </li></ul></ul><ul><ul><ul><li>High-speed shared memory </li></ul></ul></ul><ul><ul><ul><li>CF Control Code (CFCC) </li></ul></ul></ul><ul><ul><ul><li>Structures (Lock, Cache, List) </li></ul></ul></ul><ul><ul><li>CF Links </li></ul></ul><ul><ul><li>CF Resource Management (CFRM) Policy </li></ul></ul><ul><ul><li>Cross-System Extended Services (XES), part of z/OS </li></ul></ul>
  7. 7. DB2 Data Sharing Architecture IRLM Buffer Pools DB2A Coupling Facilities LOCK1 Group Buffer Pools 1 12 2 3 4 5 6 7 8 9 10 11 SCA Sysplex timers 1 12 2 3 4 5 6 7 8 9 10 11 DB2A Log IRLM Buffer Pools DB2B IRLM Buffer Pools DB2n . . . Shared DASD DB2B Log DB2n Log . . . DB2 Cat/Dir DB2 DBs
  8. 8. Design for Continuous Availability <ul><li>Single points of failure eliminated: </li></ul><ul><ul><ul><li>DB2 subsystem or z/OS system (LPAR) </li></ul></ul></ul><ul><ul><ul><li>CPC (or CEC) </li></ul></ul></ul><ul><li>Goal: Continuous Availability across planned or unplanned outage of any single hardware or software element </li></ul><ul><li>Strategy: </li></ul><ul><ul><li>Remove all causes for planned outages </li></ul></ul><ul><ul><li>Build on legacy of robust, fault tolerant MVS components </li></ul></ul><ul><ul><li>On a failure: </li></ul></ul><ul><ul><ul><li>Isolate failure to lowest granularity possible </li></ul></ul></ul><ul><ul><ul><li>Automate recovery and recover fast </li></ul></ul></ul>DB2A DB2B DB2n . . . Coupling Facilities
  9. 9. DB2 Member Outage – Planned <ul><li>&quot;Rolling&quot; maintenance </li></ul><ul><li>One DB2 or LPAR can be stopped at a time </li></ul><ul><li>DB2 data continuously available via the N-1 members </li></ul><ul><li>Other members temporarily pick up the work of the member that is down </li></ul><ul><li>Batch work can be offloaded to another member with more available capacity to reduce the batch window </li></ul><ul><li>Applies to hardware and operating system changes, too </li></ul><ul><ul><li>Rolling IPLs </li></ul></ul>DB2B . … .. . DB2A DB2n X DB2 Group KEY TO SUCCESS: Applications must be able to run on more than oneDB2 member – several apps are identified as candidates.
  10. 10. DB2 Member Outage – Unplanned <ul><li>The other &quot;surviving&quot; members remain up and running </li></ul><ul><li>The architecture allows all members to access all portions of the databases </li></ul><ul><li>Work can be dynamically routed away from the failed DB2 member </li></ul><ul><li>The failed member holds &quot;retained locks&quot; to protect inconsistent data from being accessed by other members </li></ul><ul><li>MVS Automatic Restart Manager (ARM) can automatically restart failed DB2 members </li></ul><ul><li>Restart ‘Light’ minimizes impact of LPAR failures </li></ul>DB2A DB2B DB2n . . . Coupling Facilities
  11. 11. Dynamic Workload Balancing <ul><li>Workload Manager (WLM) </li></ul><ul><li>CICSPlex System Manager (CPSM) </li></ul><ul><ul><li>Route workload between CICS TORs and AORs </li></ul></ul><ul><li>WebSphere </li></ul><ul><ul><li>Connection pooling </li></ul></ul><ul><ul><li>Connection concentration </li></ul></ul><ul><li>Distributed access (DDF) </li></ul><ul><ul><li>Dynamic Virtual I/P Addressing (DVIPA) </li></ul></ul><ul><li>Sysplex Distributor </li></ul>Appl Appl Appl Appl Appl Transaction Managers CICS IMS TM DB2 data sharing group z/OS Parallel Sysplex Network DDF WAS
  12. 12. Data Sharing Performance Summary <ul><li>CPU cost of data sharing varies based on: </li></ul><ul><ul><li>CF access intensity for locking and caching. This varies based on: </li></ul></ul><ul><ul><ul><li>Percentage of CPU time in DB2 </li></ul></ul></ul><ul><ul><ul><li>Degree of read/write sharing </li></ul></ul></ul><ul><ul><ul><li>Number of locks obtained </li></ul></ul></ul><ul><ul><ul><li>Access rate to shared data </li></ul></ul></ul><ul><ul><ul><li>Insert/delete intensity </li></ul></ul></ul><ul><ul><ul><li>Release of DB2 </li></ul></ul></ul><ul><ul><li>Hardware configuration </li></ul></ul><ul><ul><li>Lock contention rates </li></ul></ul><ul><li>Data sharing cost varies from one workload to another </li></ul><ul><ul><li>'Typical' 2-way data sharing overhead about 10% </li></ul></ul><ul><ul><li>Individual jobs/transactions may have higher overhead </li></ul></ul><ul><ul><li>< 0.5% added cost per member past 2-way </li></ul></ul>
  13. 13. DB2 Data Sharing OLTP Scalability <ul><li>IMS/TM with DB2 V4 OLTP workload </li></ul><ul><li>96.75% of ideal scalability from 2 to 8 nodes demonstrated </li></ul>
  14. 14. Data Sharing Performance in Production <ul><li>Host CPU effect with primary application involved in data sharing </li></ul><ul><ul><li>10% is a typical average </li></ul></ul><ul><ul><li>Scalability and performance for real life customer workloads </li></ul></ul>Note: “Mi” stands for ‘million instructions’ Industry Trx Mgr / DB Mgr z/OS Images CF access per Mi % of used capacity Pharmacy CICS/DB2 3 8 10% Insurance CICS/IMS+DB2 9 9 10% Banking IMS/IMS+DB2 4 8 11% Transportation CICS/DB2 3 6 8% Banking IMS/IMS+DB2 2 7 9% Retail CICS/DB2+IMS 3 4 5% Shipping CICS/DB2+IMS 2 8 9%
  15. 15. Application Changes ? <ul><li>SQL interface does not change </li></ul><ul><li>However, locking and commit frequency may impact data sharing performance </li></ul><ul><ul><li>Commit frequently – long-time recommendation </li></ul></ul><ul><ul><li>Take advantage of lock avoidance </li></ul></ul><ul><ul><ul><li>ISO(CS) </li></ul></ul></ul><ul><ul><ul><li>CURRENTDATA NO </li></ul></ul></ul><ul><li>New messages and return codes </li></ul><ul><li>Applications should be able to run on more than one DB2 member for high availability </li></ul><ul><li>Summary: “Turbo Charger” for existing applications </li></ul>
  16. 16. Customers using DB2 Data Sharing
  17. 17. Why should you exploit DB2 Data Sharing ? <ul><li>Continuous Availability for critical applications in terms of infrastructure. </li></ul><ul><li>Enhanced Operational Capability and Return On Investment – better leverage of investment in the mainframe. </li></ul><ul><li>Low Risk Implementation – as technology is proven. </li></ul><ul><li>Low cost or high cost implementation choices available – there are many options – see later slides for a cost effective option. </li></ul>
  18. 18. Continuous Availability <ul><li>Pain Points </li></ul><ul><ul><li>Individual applications currently boxed and isolated </li></ul></ul><ul><ul><li>Applications becoming interdependent </li></ul></ul><ul><ul><li>Application interdependency creates single points of failure </li></ul></ul><ul><ul><li>No in-site local failover for applications </li></ul></ul><ul><li>Data Sharing </li></ul><ul><ul><li>Allows data to be shared directly without message passing </li></ul></ul><ul><ul><li>Can eliminate certain service outages </li></ul></ul><ul><ul><li>Can reduce the duration of remaining outages </li></ul></ul><ul><ul><li>Could have avoided some past outages or reduced the outage duration </li></ul></ul>
  19. 19. Enhanced Operational Capability and Return On Investment <ul><li>Have you already invested heavily in system infrastructure ? </li></ul><ul><li>Not getting full value from that investment </li></ul><ul><li>Leverage existing investment and achieve step change in operational capability </li></ul><ul><li>Significant improvement to in-site operational recovery capability </li></ul><ul><li>New model for in-site failover can be enabled </li></ul><ul><ul><li>vs. full DR invocation </li></ul></ul><ul><li>Better utilisation of existing system resources through workload balancing </li></ul><ul><li>Removing scaling factors that might inhibit M&A activity </li></ul>
  20. 20. Low Implementation Risk <ul><li>Well proven technology </li></ul><ul><li>Widespread deployment around WW global banking community </li></ul><ul><li>Global experience and skills </li></ul><ul><li>Evolve to target environment with incremental change </li></ul><ul><li>Target applications – as identified in the High Availability Workshops </li></ul><ul><ul><li>Procis </li></ul></ul><ul><ul><li>MSP </li></ul></ul><ul><ul><li>CBS </li></ul></ul><ul><ul><li>Huon </li></ul></ul><ul><ul><li>TD01 </li></ul></ul><ul><ul><li>Others … </li></ul></ul>
  21. 21. CheckFree – Real Customer Experience
  22. 22. Summary & Next Steps

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