Best Practices for Optimizing Blackboard Learn

1. Best Practices for Optimizing Blackboard Learn Steve Feldman, sfeldman@blackboard.com

3. What We’ll Cover • A deployment approach for the ages. • How to make use of the new sizing guide. • Optimizing the platform components.

4. Flexible and Scalable Application Deployment

5. Flexible and Scalable Application Deployment • An ideal deployment will contain… • Availability at every edge of the application environment • Strategy: Physical distribution of load-balanced systems • Strategy: Minimum DB recovery, not necessarily 0 downtime • Consumption of every possible machine resource • Strategy: Virtualization provisioning • Techniques for improving user experience • Strategy: Techniques and tools for achieving page-level SLAs • Large addressable memory spaces • Strategy: 64-bit and large OS process space allocations

6. Flexible and Scalable Application Deployment • An ideal deployment will contain… • Minimum Storage Recovery Time • Strategy: Enterprise storage with Snapshot capabilities • Advanced monitoring for operations and planning • Strategy: Measurement tools and analytics • Automation…Automation…Automation • Strategy: Investment in repeatable, reliable automated processes.

7. Deployment: Availability • VLEs are different beasts today then in the past. • Communities are bigger • Sessions last longer • Content is richer • Key point: Adoption is greater and users expect their sites up 24 x 7 x 365 • Architecture is designed for many parallel instances of the product scaled in a horizontal fashion. • Distributed physical deployments • Virtualization is a key element • Database failover more important than horizontal database scalability. • Emphasis on vertical database scalability

9. Deployment: Resource Utilization • Moore’s law is in full effect • CPUs are getting faster with more cores • Memory is in abundance and cheap • Storage is grossly abundant • Massive systems can be obtained at low cost, but cannot be saturated in stand-alone configurations. • Virtualization offers the opportunity… • Deploy with availability in mind • Saturate system resources

10. Deployment: Improving Page Responsiveness • Gzip…Gzip…Gzip… • All of our supported browsers handle gzip? • Reduces payload • Improves lower latency connections like Cable, DSL and Dial-up • Minor overhead on the application layer (~2% to ~5%) • Have the option to perform at the load-balancer layer • Most Bb deployments do not enable Gzip at all • Even when enabled, some proxies and software packages mess-up the Accept Encoding Header • Optimize your images • Page size really does matter • Reduce the size without reducing the quality

11. Deployment: Large Address Space • As of Blackboard Learn™ Release 9.1 all supported/certified configurations include a 64-bit option. • Pushing more processing to client and DB over the last few releases, but major memory management technique is to use more application caches. • Memory stays persistent longer • Less wasteful from a creation/destruction perspective, but puts greater demands on larger spaces. • Most of our application testing focused on 4GB and 8GB JVM deployments on 6GB and 10GB OS spaces. • Limited testing at 16GB and 32GB

13. Deployment: Storage MTTR • Reference architecture pushes for “diskless” boots in which ISCSI or NFS partition resides on an enterprise storage system. • Both OS/VM partition and data partition served up from remote storage deployment designed for performance and scalability. • Make your hardware work from a CPU, Memory and Network perspective…save the Disk for the experts. • Consider scenarios for reducing “Mean Time to Recovery or Repair” • Snapshot technology offering minutes for recovery

14. Deployment: Advanced Monitoring • Measurement is the secret sauce for successful deployments. • Most reliable and scalable deployments measure beyond the server infrastructure • Different types of measurements • System/Environmental measurements • Business measurements • Synthetic measurements • Collecting is only part of the prize • Need to analyze the data to drive business decisions from the data.

15. Deployment: Automation • Goal of moving to 100% unattended and fully automated deployment. • Reduce MTTR and prevent disasters • Automation requires intimacy…intimacy requires knowledge • Use automation for • Configuration Management and Deployment • Maintenance • Repeatable tasks • Adaptive tuning • Minimize possibility of human error • http://dev2ops.org/storage/downloads/FullyAutomatedProvisioning_Whitepaper.pdf

17. Sizing the Application: To Hyper-Thread or Not • Applies to Intel deployments only • “..delivers thread-level parallelism on each processor resulting in more efficient use of processor resources—higher processing throughput—and improved performance on multi-threaded software.” –Intel Corporation • Greatly improved in series 5500+ processor • Provides double worker thread capacity • If it’s not turned on, stop what you are doing and enable it ASAP!

18. Moving Away from Clusters • Tomcat clusters were introduced back in Blackboard Learn 7.X prior to the transcendence of server virtualization. • Only supported 32-bit configurations at the time, but systems were being shipped with 8GB, 16GB and 32+GB of RAM. • Needed a way to take advantage of memory, but were limited to a 1.7GB address space. • Recommending “distributed” deployment approaches as well. • Still applies, but can be achieved differently. • Clustering has its advantages, but also has its penalties. • Failover not as ideal as one would desire. • Best approach is to scale up with 64-bit spaces and distributed JVMs across both virtual and physical configs

19. Sizing Using P.A.Rs • PAR = Performance Archetype Ratios • Methodology for sizing based on units of work that can be applied to “unit of configuration” • PARs assume a world of linear units • Add units of configuration to meet growing demands of unit of work. • PARs based on (4) key resources: CPU, Memory, Disk and I/O and application interfaces (threads and connections). • Used for making capacity decisions for sizing both virtual and physical components.

20. Optimizing the Web Server • The web server in the Blackboard Learn configuration is nothing more than a gateway to the application container. • When clusters were more relevent, the web server acted as a pseudo load-balancer. • Not many opportunities for optimization other than • KeepAlives • Interfaces • Compression • It can become a bottleneck if not properly optimized • Better to have high ceilings from an interface perspective

21. Optimizing the JVM • Java hotspot offers standard –X and non-standard –XX options for performance and behavior. • -X options are always guaranteed across releases and patches of Java. • -XX options must be used with caution as they are subject to change with any release of Java. • -XX options should be tested and measured using the production safe arguments. • Read the release notes of Java for “performance” updates • http://java.sun.com/javase/6/webnotes/ReleaseNotes.html

22. Optimizing the JVM • Cross-platform recommendation for using Concurrent Mark Sweep Collector • Best optimized for 64-bit address • Combine –XX:+UseConcMarkSweepGCwith –XX:+UseParNewGC • Manually size New Space using –XX:NewSize and –XX:MaxNewSize options (1/4 to 1/3 total heap). • Consider Survivor Space ratios 4 or lower. • Be careful about sharing –XX non-standard options across customers. • If you don’t understand what the option does and it’s not recommended by Blackboard, best choice is to not use it.

23. Optimizing the Database: SQL Server • # of data files makes no difference on SQL Server for Data and Transaction • Allow the data/transaction files to grow as big as they want within reason. • What’s reason: 64GB • http://msdn.microsoft.com/en-us/library/ms143432(sql.90).aspx • TempDB is completely different story • # of files = # of DB Threads • Set first X files to a uniform size, set last file to same size with auto-extension ON • Determine size need over time • Separate volume for paging file

24. Optimizing the Database: SQL Server • Be aware of MDOP: Max Degree of Parallelism • Setting to unlimited can have a negative affect on query performance unintentionally. • AWE can and does work on 64-bit systems • Configure READ_COMMITTED_SNAPSHOT • Two nuggets of information: • Learn How to Use SQL DMVs • Study SQL Server Wait Events and Tuning

25. Optimizing the Database: Oracle • Balance I/Os across multiple data files (~2 to 8GB per file). • REDO is critical to performance a session/query level. • Be aware of how much REDO is being used over time. • NOLOGGING will disable, be we rarely use NOLOGGING • TEMP is very complex and used for managing transient data. • One TEMP file is adequate • If latency exists on TEMP, consider introducing TEMP file groups • SGA is important, but PGA can be your best friend or your worst enemy with high concurrency.

26. Optimizing the Database: Oracle • Oracle DBO can be your friend • Must understand optimizer behavior • Willingness to read Cost Execution Plans • Using Wait Events and Cost Execution Plans for tuning initiatives • Wait events are at a system, session and query level • Importance of Statistics and Histograms • CBO is just guessing without properly set statistics and histograms. • CBO is dependent on your data.

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