blackboard learn 9.1 hardware sizing guide for sun deployments

8/2/2019 Blackboard Learn 9.1 Hardware Sizing Guide for Sun Deployments

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2010 Blackboard Inc. Proprietary and Confidential

Release 9.1

Hardware Sizing Guide for

Sun Deployments


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Blackboard Learn Hardware Sizing Guide for Sun Deployments Page 2


Publication Date: June 11, 2010

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Copyright 1997-2010. Blackboard, the Blackboard logo, BbWorld, Blackboard Learn,

Blackboard Transact, Blackboard Connect, the Blackboard Outcomes System, Behind theBlackboard, and Connect-ED are trademarks or registered trademarks of Blackboard Inc. or itssubsidiaries in the United States and other countries. U.S. Patent Numbers: 6,988,138;7,493,396; 6,816,878.

Sun and Java are registered trademarks of Sun Microsystems, Inc. in the United States and othercountries. Microsoft, Windows, and SQL Server are registered trademarks of MicrosoftCorporation in the United States and other countries. Oracle is a registered trademark of OracleCorporation and its affiliates. UNIX is a registered trademark in the United States and othercountries, licensed exclusively through X/Open Company Ltd.

Other product and company names mentioned herein may be the trademarks of their respectiveowners.

No part of the contents of this manual may be reproduced or transmitted in any form or by anymeans without the written permission of the publisher, Blackboard Inc.


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ContentsIntroduction ...................... ......................... ........................ ......................... ........................ ....... 4

About Blackboard Learn ........................................................................................................ 4About this Guide ................................................................................................................... 4

Recommended Configurations ........................ ........................ ......................... ........................ 5Deploying Blackboard Learn ....................... ........................ ......................... ........................ .... 6Sizing the Application Server ...................... ........................ ......................... ........................ .... 7

Sun Configuration Information ............................................................................................... 7Will Tomcat Clustering Make a Difference? ........................................................................... 7Sun Configurations for Blackboard Learn Release 9.1 ........................................................... 9

Sizing the Database ........................... ........................ ......................... ........................ ............ 11Sizing Storage ....................... ......................... ........................ ......................... ........................ 12

Media and Content Storage................................................................................................. 12Database Data File Storage ................................................................................................ 12Storage Performance .......................................................................................................... 13

Appendix A: Sizing Methodology ........................ ......................... ........................ .................. 14


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Introduction



Introduction

A paradigm shift is underway in online learning. Online learning tools that were once usedprimarily to augment classroom learning have matured to support an online model in which theCourse Management System serves as the primary medium for teaching and learning. As theprevalence of high-speed Internet connections and home computer ownership has grown, so too

has the demand for distance learning. Today's learners are turning to web-based distancelearning programs as a means to balance other obligations with the desire to further theireducation, or because they are too far away from the institutions that can best serve their needs.

The movement toward fully online learning models creates new demands for the IT environmentand opens up new opportunities for institutions to use technology as a competitive tool. Demandfor higher performance and faster response times are being driven by two key factors: greaternumbers of users, and increased activity by users. Not only are institutions growing andsupporting greater numbers of online users, but users are also interacting with the system in newways that generate substantially greater system load. Users tend to stay online for much longerperiods of time and have greater interactivity with their online courses. The technology musttherefore support large numbers of users who concurrently access the system and require rapidresponse times so that they can interact without noticeable delays.

When users have consistent and responsive page load times, online learning is easier and moreeffective, new forms of teaching and learning can also evolve when interaction has the feeling ofbeing real-time. Traditional online lectures and online documents can be blended with interactivemedia, allowing students to share experiences with each other across geographical boundaries.

This can increase the effectiveness of the learning environment and expand the available marketthe institution serves. Institutions want their online learning technology infrastructure to supportthese new forms of teaching and learning on a scale that allows many more students than couldtraditionally participate in a classroom approach.

The online learning architecture must therefore be highly scalable as well as cost-effective tomaintain so that institutions can focus on teaching instead of technology. The right technologyinfrastructure for online learning can create a competitive advantage for the institution.

About Blackboard Learn

Blackboard Learn includes Blackboards course management system, Course Delivery, as wellas other core applications. Additional capabilities that can be licensed include communityengagement, content management, and outcomes assessment.

About this Guide

This guide helps Blackboard clients achieve high service levels and reduce risk by properlyconfiguring and sizing the implementation of Blackboard Learn software on Sun applicationand database servers. The information in this guide is based on analysis and benchmarkingmodels from the Blackboard Performance Team in conjunction with Sun.

For information about Blackboards sizing methodology, see Appendix A: Sizing Methodology.

This guide is intended to provide guidance. It is not intended as a service level agreement.Deployments will differ from institution to institution based on a variety of factors including theusage of the application. For more information about systems architecture design and detailedsizing questions, contact your Blackboard Account Manager.


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Recommended Configurations



Recommended Configurations

Blackboards recommended configuration is based on a scalable reference architecture that takesadvantage of todays latest technologies to support a rich online learning or distance learningmodel. In addition, this architecture offers superior performance and scalability as well aspredictable service levels. This information is based on joint performance testing andbenchmarking between Blackboard and Sun to achieve maximum performance throughput foreach configuration.

Blackboard Learn Reference Architecture on Sun Hardware


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Deploying Blackboard Learn



Deploying Blackboard Learn

Customers who deploy Blackboard Learn on Sun hardware have the flexibility to choose from avariety of server architectures that support Solaris, Linux, and Windows. Sun offers hardwaremodels built on UltraSPARC T2/T1, AMD Opteron, and Intel Xeon processor platforms.

The UltraSPARC architecture is well suited for Blackboard Learn. Clients can deploy either the

Sun Fire T5120/T5220 server for price and throughput performance, or the Sun FireT5140/T5240 for overall throughput performance. All 6 units have the capacity to scale to 6 coresor 8 cores with a minimum of 16GB of memory. The Sun Fire T5140/T5240 has the capacity of2 sockets per physical machine.

Blackboard recommends leveraging both physical and virtual configurations. For years, theBlackboard products have been deployed in distributed manner across multiple physical servers.This configuration remains as the primary option for availability and scalability. In recent releases,many Blackboard customers have introduced virtualized configurations within a physical serverusing technology such as Solaris Zones. The combination of both physical and virtualizedconfigurations has introduced resiliency, scalability, and high performance. In Blackboard LearnRelease 9.1, Blackboard introduced a 100% 64-bit offering for all certified and supportedoperating systems (OSs) as an additional deployment approach to integrate with physical and

virtual configurations.


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Sizing the Application Server




Sun Configuration Information

Application tier scalability is achieved using a highly flexible, horizontally scaled infrastructure.

Multiple instances of Blackboard Learn can be deployed on a single Sun server using either avirtualization package or bare-metal configuration to isolate Blackboard application instancesfrom each other and to manage allocation of CPU and memory resources.

Each Sun server in the application tier can run multiple zones each with its own instance of theBlackboard Learn software. To achieve a high volume of concurrent user sessions, thearchitecture employs load balancing to distribute requests across all of the Blackboard Learnapplication instances deployed on the zones.

The architecture takes advantage of 64-bit computing by using Java heap sizes that range from2G to 16GB for each Blackboard application instance. Some customers on rare occasions havedeployed Java Virtual Machines (JVMs) as large as 32GB in size. The Java heap had beenlimited to 1.7GB in a 32-bit environment, but this limitation is overcome in the 64-bit environment.Because this feature is now available for all platforms with Blackboard Learn Release 9.1,

Blackboard strongly recommends that customers adopt 64-bit for their primary deployment OSs.

The architecture includes a recommended 8GB of memory for each VM, leaving up to 2GB forthe Apache Web server, and up to 2GB for the OS and monitoring tools. This assumes a JVMheap size of 4GB. Obviously, a larger JVM heap size will require additional memory for the VM.The larger memory footprint for Blackboard Learn enables each application instance to moreefficiently service a high volume of user requests. In other words, each application instance canscale vertically while the architecture can also be scaled horizontally by deploying additional VMs.

This best of both worlds approach takes advantage of many application threads in theapplication tier to service thousands of requests per minute. The recommended servers for theapplication tier are Sun SPARC Enterprise T5120 and T5140 models, which were chosen for theirsmall footprint, moderate cost, and powerful throughput performance.

The highly flexible and scalable application tier can help customers achieve:

Lower costs: Increased utilization of servers enables good performance on a low-costconsolidated infrastructure.

Increased flexibility: VMs can be moved easily to other physical servers to redistributeworkloads or recover quickly from a hardware failure.

Faster Deployment: With fewer physical systems to setup and configure, less time isrequired for deployment.

Will Tomcat Clustering Make a Difference?

Customers should begin migrating from Tomcat clusters. Tomcat clustering was introduced forscalability purposes when the Blackboard Learn architecture was 32-bit and customers wantedthe ability to increase their memory usage on a single server. With the option to virtualize on both32-bit and 64-bit, Blackboards benchmarking efforts have moved away from Tomcat clusterdeployments. Customers can achieve similar performance in a virtual environment on the samephysical server with multiple virtual instances as with a bare metal configuration with manyTomcat cluster instances. The difference in configurations is a smaller demand on the Apache orIIS web server fronting the Tomcat instance(s). The option to deploy a 64-bit JVM with largerheap sizes has suppressed the need for customers to run in a cluster option.


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Blackboard recommends that customers consider a deployment approach consisting of larger64-bit JVMs that are distributed across physical servers with the option to virtualize the hardwareto take advantage of the CPU and Memory capacity of these systems.


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Blackboard Learn Hardware Sizing Guide for Sun Deployments Pag2010 Blackboard Inc. Proprietary and Confidential

Sun Configurations for Blackboard Learn Release 9.1

Sizing Category Standard Advanced Complex

Description The Standard sizing configuration is designed foravailability and performance. Options exist forboth physical distributions of application serversand/or virtualized instances of the application. Theinstitution has minimal deployment of distancelearning or connected classroom initiatives (lessthan 5%).

The Advanced sizing configuration is designed forhigh-availability and high-performance. The modelis designed for heavy adoption of the productacross institutions of varying sizes. Customersdeploying distance learning programs or haveconnected classroom initiatives to a portion of thecommunity fall into this category.

The Complex sizing configuration is designed formassive adoption, high-availability and high-performance. Customers deploying predominateldistance learning programs or have connectedclassroom initiatives fall into this category.Customers with larger community sizes (greaterthan 250,000 users) fall into this category.

Appl i cat ion Server Conf igurat ion

Number of OS Instances(Physical or Virtual)

2 to 4 4 to 8 8 to 16

Minimum CPU ConfigurationPer OS Instance

1 x 8-Core

1.2 GHz UltraSPARC T2

64 Threads

1 x 8-Core


64 Threads

2 x 8-Core

1.4 GHz UltraSPARC T2 Plus

128 Threads

Minimum CPU Collapse Ratio(Zone to Physical Server)

4:1 (Zone Configuration) 4:1 ( Zone Configuration ) 6:1 ( Zone Configuration )

Ideal CPU ConfigurationPer OS Instance

1 x 8-Core


64 Threads

2 x 8-Core


128 Threads

2 x 8-Core


128 Threads

Ideal CPU Virtualization CollapseRatio (Zone to Physical Server)

4:1 (Zone Configuration) 6:1 ( Zone Configuration ) 6:1 ( Zone Configuration )

64-bit Memory RequirementsPer OS Instance

8GB to 16GB recommended 8GB to 16GB recommended 8GB to 16GB recommended

I/O Workload at Peak Hour 300 to 500 I/Os 500 to 1000 I/Os 1000 to 2000 I/Os

Hits/Hour at Peak Hour Up to 4 Million Hits/Hour Up to 8 Million Hits/Hour Up to 12 Million Hits/Hour

Characteristics With 8 CPU threads per instance and a 64-bitdeployment across 4 instances, this configurationwill support as many as 20,000 concurrentsessions for a peak hour. A concurrent session isa user who has logged into the application withinthe last hour.

Results will vary depending on the use of memoryintensive areas of the application such asAssessment and Grade Center. Memory has thegreatest impact on the session concurrency andresponsiveness of the application, followed byCPU capacity. Consider a larger memory footprintfor even smaller workloads to deliver faster pageresponsiveness.

With 16 to 20 CPU threads per instance and a64-bit deployment across 6 instances, thisconfiguration will support as many as 40,000concurrent sessions for a peak hour.A concurrent session is a user who has loggedinto the application within the last hour.

Results will vary depending on the use of memoryintensive areas of the application such asAssessment and Grade Center. Memory has thegreatest impact on the session concurrency andresponsiveness of the application, followed byCPU capacity. Consider a larger memory footprintfor even smaller workloads to deliver faster pageresponsiveness.

With 16 to 20 CPU threads per instance and a64-bit deployment across 6 instances, thisconfiguration will support as many as 80,000concurrent sessions for a peak hour.A concurrent session is a user who has loggedinto the application within the last hour.

Results will vary depending on the use of memorintensive areas of the application such asAssessment and Grade Center. Memory has thegreatest impact on the session concurrency andresponsiveness of the application, followed byCPU capacity. Consider a larger memory footprinfor even smaller workloads to deliver faster pageresponsiveness.


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Blackboard Learn Hardware Sizing Guide for Sun Deployments Page2010 Blackboard Inc. Proprietary and Confidential

Sun Configurations for Blackboard Learn Release 9.1

Sizing Category Standard Advanced Complex

Description The Standard sizing configuration is designed foravailability and performance. Options exist forboth physical distributions of application serversand/or virtualized instances of the application. Theinstitution has minimal deployment of distancelearning or connected classroom initiatives (lessthan 5%).

The Advanced sizing configuration is designed forhigh-availability and high-performance. The modelis designed for heavy adoption of the productacross institutions of varying sizes. Customersdeploying distance learning programs or haveconnected classroom initiatives to a portion of thecommunity fall into this category.

The Complex sizing configuration is designed formassive adoption, high-availability and high-performance. Customers deploying predominateldistance learning programs or have connectedclassroom initiatives fall into this category.Customers with larger community sizes (greaterthan 250,000 users) fall into this category.

Database Server Conf igurat ion

Minimum CPU Configuration 1 x 8-Core


64 Threads

2 x 8-Core


128 Threads

2 x 8-Core


128 Threads

Ideal CPU Configuration 1 x 8-Core


64 Threads

8 x 2.53 GHz SPARC64 VII

on 4 Boards

4 x 8-Core


256 Threads

Memory Requirements 8GB to 16GB 16GB to 64GB 48GB to 128GB

I/O Workload at Peak Hour 600 to 1,200 I/Os 1,500 to 3,000 I/Os 4,500 to 10,000 I/Os

Availability Approach Failover clustering approaches that leverageActive/Passive database configurations should beconsidered for this deployment.

Failover clustering approaches that leverageActive/Passive database configurations should beconsidered for this deployment. Solarisdeployments may consider Oracle RealApplication Clusters (Oracle RAC)

Failover clustering approaches that leverageActive/Passive database configurations should beconsidered for this deployment. Solarisdeployments should consider Oracle RealApplication Clusters (Oracle RAC)

O racle Mem ory Requ i rem ents

Estimated SGA Size 1GB to 4GB 4GB to 16GB 16GB to 32GB

Processes 600 to 1,200 2,000 to 4,000 5,000 to 10,000

Estimated Process Size 3M to 7M 3M to 7M 3M to 7M

Estimated PGA Memory 2GB to 8GB 10GB to 20GB 25GB to 50GB


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Sizing the Database



Sizing the Database

The Sun Fire T5220 and T5240 are ideal for running Oracle 10gR2 or 11gR1 in small andmedium size institutions. Both systems have 6-core and 8-core configurations available. Memoryrequirements will vary depending on deployment within a 32-bit or 64-bit configuration. Each ofthese systems can be used for availability purposes in an Oracle Real Application Clusters(Oracle RAC)configuration. Blackboard offers support for RAC with all versions of Oraclesupported by Blackboard. For information about running Blackboard Learn with RAC, see theBlackboard Learn Server Administrator Guideavailable onBehind the Blackboard.

For large campus configurations, a Sun Fire T5440 or Sun SPARC Enterprise M5000 serveris used instead of the Sun Fire T5220 or T5240 server to provide increased capacity. A highavailability option is supported through an optional cluster configuration with a redundant instanceof the database running on a second server using Oracle RAC to provide the redundant databasefunctionality.

Sizing for memory is absolutely critical for ensuring a high-performing and reliable configuration.Oracle configurations require a set of inputs to calculate the SGA and PGA spaces of memory.The SGA will contain both the SQL area for caching statements, as well as the buffer cache forstoring blocks of data in memory. The PGA space will maintain the process memory

requirements, as well as hash and sorting space for query execution. The combination of thesetwo regions makes up the requirements of Oracle memory.
https://behind.blackboard.com/https://behind.blackboard.com/https://behind.blackboard.com/https://behind.blackboard.com/


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Sizing Storage



Sizing Storage

Media and Content Storage

Blackboard Learn uses a non-relational file system for the storage of multi-media and binary files

such as text files, images, word processing documents, spreadsheets, and other file types usedin teaching and learning.

Blackboard recommends that clients on UNIX platforms use a network file share (NFS).

Blackboard recommends that clients on Windows use a common internet file system (CIFS).

Both of these network-based file system protocols allow for simplified management, ease of dataexpansion, and multiple access points from applications servers. Load balanced installations canuse both file system types. Deploying storage on a local application server can also beimplemented, but Blackboard does not recommend doing so.

File system content can range from 5100 times the size of database content. File systemcontent from a block perspective is touched less frequently than the database file system. Clientscan opt to configure their systems to a lesser performing RAID configuration with slower spindlesbecause I/O performance is less of a concern.

Blackboard recommends that clients determine a storage quota per student and faculty memberas well as account for passive users that require less storage quota. Assume that faculty will havegreater storage requirements. Following is a simple example:

Profi le Quota Users Storage Needs

Faculty 5GB 500 2.5 TB + RAID Considerations

Student 500MB 10,000 5TB + RAID Considerations

Other 20MB 1,000 20GB + RAID Considerations

Sizing the file system depends on archival strategies, data management policies, RAIDconfiguration, and I/O performance standards. Blackboard typically assumes that the file systemwill require about 100+ I/O per second per application server at peak. To calculate your I/O persecond needs, multiply this metric against the number of application servers in your deployment.Database Data File Storage

Blackboard Learn uses a relational database system (Oracle and SQL Server) for the storage ofdatabase content.

Clients on UNIX platforms may use one of the following:

A network file share (NFS) ISCSI (networked block-level)

Direct attached storage (block-level)

Clients on Windows SQL Server may use one of the following:

ISCSI (networked block-level)

Direct attached storage (block-level)


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Sizing Storage



The database storage requirements of institutions can vary. Typically, database content canrange from 5100 times less than file system content. Sizing the database depends on archivalstrategies, data management policies, RAID configuration, and, most importantly, I/Operformance standards. Blackboard typically assumes that the file system will require between350 to 600 I/O per second per application server at peak. To calculate your I/O per secondneeds, multiply this metric against the number of application servers in your deployment. Theprimary driver for database storage should be performance.

Storage Performance

The database tier has variable I/O performance needs, therefore, Blackboard recommends usingfibre channel drives with 10,000 to 15,000 RPM capacity. To deliver adequate I/O throughput,Blackboard also recommends using smaller capacity drives so that there will be more spindles toreduce seek times and improve data transfer rates.

The I/O performance requirements are not the same for the shared file system. Slower,condensed storage options using SATA or SAS disks in the range of 7,200 or 10,000 RPM aremore than adequate. The configurations defined in this guide have been validated to supportadequate I/O throughput for the user loads defined for each configuration. When sizing storage,

be sure to do the following:

1. Determine how much storage your institution will need.

2. Determine how this storage can be spread across multiple trays and disks to optimizeperformance throughput.

Remember that the shared file system can require upwards of 5100 times the amount of storageof the database. However, the database can use 520 times the number of I/O operations persecond than the shared file system.

Description Standard Advanced Complex

ContentStorageTier

UNIX: Network AttachedStorage Architecture orZFS for Solaris only

Windows: CIFSArchitecture

Up to 2.2 TB of usablestorage

7.2k to 10k RPM SATA orSAS disks



Up to 5 TB of usablestorage






DatabaseStorageTier

UNIX: Network AttachedStorage Architecture,ISCSI, or FC-SAN

Windows: ISCSI orFC-SAN

Up to 500 GB of usablestorage

10k to 15k RPM FC




10k to 15k RPM FC




10k to 15k RPM FC


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Appendix A: Sizing Methodology


Appendix A: Sizing Methodology

Sizing is a three-step process consisting of two modeling exercises and performance testing. Themodeling exercises are used to gather statistical evidence about how users interact with thesystem. The data generated from these exercises is subsequently used in a series ofperformance tests. Performance tests help quantify what the system will look like under

hypothesized workloads and scenarios.

The process begins with understanding how Blackboard clients have used the product in thepast. This form of sampling is called behavior modeling. The objective of this form of sampling isto gather meaningful data representing the following:

Who is using the system?

What is being done?

Where are they performing their operations?

When are they performing their operations?

How long are users spending performing their operations?

Predictive modeling is used for new performance testing new features. Little information can becollected about a feature that has not been built. Because of this, Blackboard hypothesizes userinteractions with these new features.

The data collected from both modeling exercises is then used for performance testing andbenchmarking. Performance benchmarking is conducted by Blackboard with a selected partner ofchoice (such as Sun Microsystems, Dell, Microsoft, or Oracle) at the Blackboard PerformanceLaboratory using a combination of purchased and donated equipment from a partner.Performance testing and benchmark activities focus primarily on the performance (responsetimes exhibited by users) and scalability of the system (utilization of system resources such asCPU, memory, and I/O). HP/Mercury LoadRunner is the simulation tool of choice for generatingworkload.

blackboard learn 9.1 hardware sizing guide for sun deployments

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