Best Practices for Optimizing Blackboard Learn Steve Feldman, [email protected]

What We’ll Cover

• A deployment approach for the ages.

• How to make use of the new sizing guide.

• Optimizing the platform components.

Flexible and Scalable Application Deployment

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

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.

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

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

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

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

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

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.

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/FullyAutomatedProv isioning_Whitepaper.pdf

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!

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

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.

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

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

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.

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

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

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.

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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