1. The Power of Platform Solutions to Transform Higher Education
100,000 Students on Banner - Exceptional Performance
Presented by: Scott Howe and Seth Sites Liberty University
Oct 1, 2014

2. Background- Intense Growth
Liberty IT has been challenged to support the growth of both residential and online programs.
Connie
Session ID xxxx

3. Connie
Session ID xxxx

4. April 2006 – Performance issues and the need for high availability drive Blackboard from Microsoft SQL server to a 4 node 10g Oracle RAC split between campuses.
July 2006 – First Banner module goes live to replace AS400 for ERP. Initial system consisted of AIX on IBM p570 infrastructure.
Dec 2007 – Performance and high availability requirements drive Banner migration onto dedicated 4 node RedHat RACs.
2009 – Both clusters are upgraded from Oracle 10g to Oracle 11g and a hardware refresh to increase system capacity and provide the smallest downtime window for the upgrade. Blackboard inherits the older Banner hardware.
2012 – Migration from the dell 4 node RACs to new hardware (UCS blades) and consolidated into solitary datacenter to eliminate interconnect latency.
RAC licensing and hardware resources require multiple tier 0 services (dotcms, degreeworks, bbts) to be configured on nodes without any form of redundancy.
Connie
Session ID xxxx

5. 2013+ Database sprawl, anticipation of growth, environment complexity, and reliance on shared storage drive evaluation of Exadata.
April 2006 – Performance issues and the need for high availability drive Blackboard from Microsoft SQL server to a 4 node 10g Oracle RAC split between campuses.
July 2006 – First Banner module goes live to replace AS400 for ERP. Initial system consisted of AIX on IBM p570 infrastructure.
Dec 2007 – Performance and high availability requirements drive Banner migration onto dedicated 4 node RedHat RACs.
2009 – Both clusters are upgraded from Oracle 10g to Oracle 11g and a hardware refresh to increase system capacity and provide the smallest downtime window for the upgrade. Blackboard inherits the older Banner hardware.
2012 – Migration from the dell 4 node RACs to new hardware (UCS blades) and consolidated into solitary datacenter to eliminate interconnect latency.
RAC licensing and hardware resources require multiple tier 0 services (dotcms, degreeworks, bbts) to be configured on nodes without any form of redundancy.
2013+ Database sprawl, anticipation of growth, environment complexity, and reliance on shared storage drive evaluation of Exadata.
Connie
Session ID xxxx

6. Problem
40+ database servers (production, stage, test, and development)
Blackboard, BbTS, DegreeWorks, Banner, In house, etc
Interconnect proximity and speed
Nonproduction instances and snapshotting
Disk I/O
Inconsistency
Administrative hurdles due to deviations in
Database software versions
Patch levels
Hardware
Firmware
OS versions/patches
Jay
Session ID xxxx

7. The Next Step IT Needs Business Needs Capacity on demand
Reduced turn around for projects needing new databases
More accurate performance testing for deployments
Reduction in patching efforts
Support structure (one throat to choke)
Business Needs
Improve end user/student performance
Improve Business Intelligence Office reporting capabilities
Increase redundancy/high availability
Jay
Session ID xxxx

8. Exadata-Overall Goals
High availability of production systems (Redundancy)
Performance
Manageability
Ease of use
Centralized administration
Simplicity of the environment
Jay
Session ID xxxx

9. To persuade a skeptic… Development Instances on 1/8 rack
POC-Summer 2013
To persuade a skeptic…
Development Instances on 1/8 rack
Scott
Session ID xxxx

10. Proof of Concept Points of evaluation I/O throughput
Hybrid Columnar Compression
Business Case Tests
Backups/Cloning
Scott
Session ID xxxx

11. POC Results #1 Evaluation of I/O intensive queries
Differences between X2 and X3 make Exadata great for OLTP
Scott
Session ID xxxx

12. POC Results #2 Evaluation of Hybrid Columnar Compression claims.
What kind of compression could we realistically expect to see?
How would it impact performance?
Can it be used in an OLTP setting?
Scott
Session ID xxxx

13. POC Results #3
Several business critical reports were identified as test cases.
Without any Exadata specific optimization, on an instance that was imported from a dump, how would they perform?
query runtime was reduced by 30% on the Exadata.
Expecting further gains
1/2 vs. 1/8 rack
Additional tweaking such as degrees of parallelism
Scott
Session ID xxxx

14. POC Results #4
Development practices expect production identical sandboxes.
Critical to be able to provide a clone from production during the work day as quickly as possible.
How fast can we perform a full backup of our ERP instance (Banner)?
Scott
Session ID xxxx

15. Full Implementation- Fall 2013
90% of all instances migrated to Exadata in under 2 months
Scott
Session ID xxxx

16. Cross Campus Redundancy

17. Performance-ERP Nominal load on production Banner
Around active waiting sessions
Traffic comprised of application, commit, user I/O, and CPU wait
Post exadata migration ~6 active waiting sessions (95% of which is just CPU)
Scott
Session ID xxxx

18. Performance-LMS
In Bb implementation we’re seeing between 1-2 million calls per minute
Average response times less than 10 milliseconds
Average active waiting sessions went from to 2!
Scott
Session ID xxxx

19. 85% reduction in overall active and waiting sessions

20. Wait Classes

21. Wait Classes Continued

22. Large Job Runtimes

23. Data Warehouse Results
Pre-Exadata
97% full 4Tb directed attached disk array
256Gb of memory
64 cores
Post Migration
Performance – 81% of the 123 ETL jobs running under the DBMS_SCHEDULER run faster with no tuning whatsoever. There will continue to be some tuning opportunities associated with the migration but overall queries simply run faster.
Disk Space – Consumes a 1/4 of the disk space that was required on the non-Exadata platform. This is due to leveraging HCC for tables in the Archive partition.

24. Post Implementation Results
Conversion to RAC
Creation of Data Guard instances
Claim validation (bored databases)
Already met two unforeseen crucial business need for database resources (CAS and Liferay)
Reduction in efforts required for quarterly patching cycle
Performance
job runtimes
storage cell offloading streamed data warehouse
DBAs taking fewer after hours calls
Scott
Session ID xxxx

25. Q&A

26. © 2014 Ellucian. All rights reserved.
Thank You!
Kevin Roebuck Scott Howe Seth Sites .
© 2014 Ellucian. All rights reserved.