Sun Hardware Sizing Guide

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1 Introduction Today s educational institutions increasingly depend on enterprise course management software systems to service the needs of their students, faculty, and administrators. It is important to deliver a high quality of service to this community of users through optimizing an e-learning platform for maximum performance and availability. This sizing guide is designed to help clients of Blackboard achieve high service levels and reduce risk by properly configuring and sizing the implementation of Blackboard Academic Suite software on Sun application and database servers. Blackboard Learn provides the critical enabling technologies to help institutions evolve into Blackboard s vision for the 21st Century Learning Institution, which is unconstrained by time and place, and can operate simultaneously in a local and global context. Blackboard s enterprise course management solutions have been proven at thousands of educational institutions worldwide. As institutions have continued to embrace the need for course management and other enabling technologies for 21st century learning, Blackboard solutions have become a critical part of the IT infrastructure that enables success in today s global marketplace. Blackboard Learn includes Blackboard s course management system, Course Delivery as well as other core applications. Additional modules include Community Engagement, Content Management, and Outcomes Assessment. Recommended s The recommended configuration pictured in Figure 1 is based on a scalable entry-level configuration for the Blackboard Reference Architecture on Sun hardware. The information in this section is based on joint performance testing and benchmarking between Blackboard and Sun in order to achieve maximum performance throughput for each configuration. Figure 1 Blackboard Reference Architecture on Sun Hardware Blackboard Inc 2008 Page 1

2 Methodology Sizing is a three-step process consisting of two modeling exercises and performance testing. The modeling exercises are used to gather statistical evidence regarding how users interact with the system. The data generated from these exercises is subsequently used in a series of performance 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 the past. This form of sampling is called behavior modeling. The objective of this form of sampling is to 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 be collected about a feature that has never been built. Because of this, we hypothesize the expected behavior of users interacting with these new features. The data collected from both modeling exercises is then used for performance testing and benchmarking. Performance benchmarking is conducted by Blackboard with a selected partner of choice such as Sun Microsystems, Dell, Microsoft, or Oracle at the Blackboard Performance Laboratory using a combination of purchased and donated equipment from a partner. Performance testing and benchmark activities focus primarily on the performance (response times exhibited by users) and scalability of the system (utilization of system resources such as CPU, memory, and I/O). HP/Mercury LoadRunner is the simulation tool of choice for generating workload. Sizing Blackboard Learn Sizing the Application Customers that deploy Blackboard on Sun hardware have the flexibility to chose from a variety of server architectures that support Solaris, Linux and Windows. Sun offers hardware models 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 T1000/T2000 server for price performance, the Sun Fire T5120/T5220 for cost and throughput performance, or the Sun Fire T5140/T5240 for overall throughput performance. All six units have the capacity to scale to six or eight cores with a minimum of 8GB of memory. The Sun Fire T5140/T5240 has the capacity of 2 sockets per physical machine. To achieve maximum throughput, each Sun Fire server should run multiple clustered Java Virtual Machines (JVM) of Blackboard Learn to take advantage of all cores available on this configuration. Performance benchmarking has shown that this server can reach 85 percent CPU utilization when running four clustered instances of the Blackboard Learn before user response time degrades. The UltraSPARC servers scale horizontally in a load-balanced configuration and vertically in a clustered JVM configuration. Clustering is a deployment feature introduced in Release 7, Application Pack 2 and included in all subsequent releases. The memory requirements of the server vary depending on the number of clustered instances running. Typically, each JVM is configured for roughly 1.5GB of memory. An additional 1Gb is required for the Apache components of the Blackboard deployment. The remaining 1GB is available for the operating system and trivial applications running on the system such as monitoring agents. Memory can be added to the server for additional clustered instances of Blackboard to run barring CPU Blackboard Inc 2008 Page 2

3 resources are not saturated. Virtualization at the Application Layer Blackboard has executed over 800 hours of regression testing and benchmarking of Blackboard Learn using virtualization technologies such as Solaris Zones. Overall performance and throughput can be vastly improved through the use of virtualization. Our performance benchmarks have demonstrated 20 percent to 40 percent additional throughput and lowered response times by breaking up a bare metal server into multiple virtualized instances. The application best performs with smaller workloads assigned to virtual instances with one to two virtual CPUs available. The Sun Fire T5140/T5240 provides the best overall performance when deployed in a virtualized configuration. Additional memory would be required for the overall server requirements. We recommend 2 to 4 GB of RAM per virtual instance. Sun Information Description Small Institution Medium Institution Large Institution User Community Size 1,000 to 10,000 10,000 to 25,000 25,000 to 50,000 Sizing Assumptions 500 to 1,000 active courses Up to 1,200 active users with 2 application servers Assumes application layer clustering and hardware load-balancing 1,000 to 5,000 active courses Up to 2,400 active users with four application servers Assumes application layer clustering and hardware load-balancing Candidate for Oracle RAC 5,000 to 25,000 active courses Up to 3,600 active users with 8 application servers Assumes application layer clustering and hardware load-balancing Candidate for Oracle RAC 1 to 2 Sun Fire T1000 Servers 2 to 4 Sun Fire T1000 Servers 4 to 8 Sun Fire T1000 Servers Application Tier 6 Core UltraSPARC T1 Processor 8 Core UltraSPARC T1 Processor 8 Core UltraSPARC T1 Processor 8 to 16GB memory 8 to 16GB memory 8 to 16GB memory Cluster Capacity Calibrated to 3 Java Virtual Machines per 6 core Server Calibrated to 4 Java Virtual Machines per 8 core Server Calibrated to 4 Java Virtual Machines per 8 core Server Virtualization Capacity Sizing the Database Calibrated for 1 virtual instance per 1 to 2 logical cores Calibrated for 1 virtual instance per 1 to 2 logical cores Calibrated for 1 virtual instance per 1 to 2 logical cores The Sun Fire T2000, T5220 or T5240 is ideal for running Oracle 10G for small and medium size institutions. Six and eight core configurations are available for all three systems. We recommend 16GB to 32GB of memory per system. Each of these systems can be used for availability purposes in an Oracle RAC configuration. Contact the Blackboard Professional Services organization for more information about deploying Blackboard on Oracle RAC. For large campus configurations, a Sun Fire T5240 or Sun SPARC Enterprise M5000 server is used instead of the Sun Fire T2000 or T5220 server to provide increased capacity. A high availability option is supported through an optional cluster configuration with a redundant instance of the database running on a second server using Oracle RAC to provide the redundant database functionality. Test results showed that a single Sun Fire T2000 server with 8 processor cores and 16 GB of memory can provide sufficient database server capacity to deliver consistent throughput performance for up to four load balanced application servers configured for application clustering. When virtualized the T2000 will support roughly 2 to 3 load balanced application servers. The Sun Fire T5240 provides the overall best cost performance and throughput performance of all of the Sun Fire systems. Blackboard Inc 2008 Page 3

4 For configurations that require well beyond four application servers to meet the throughput requirements, a larger database server is recommended. The rack mountable Sun SPARC Enterprise M5000 server configured with eight dual-core SPARC64 VI processors and 32 GB of memory delivers enough performance to serve six fully configured application servers. Customers who prefer a desk side server over a rack mount server can substitute a Sun Fire V890 server for the Sun SPARC Enterprise M5000 server. Considerations for the Sun Fire T5240 should be made as well. Sizing Storage Media and Content Storage Blackboard Learn makes use of a non-relational file system for the storage of multimedia and binary files such as text files, images, word processing documents, spreadsheets, and other file types used in teaching and learning. Blackboard recommends clients make use of a network file share (NFS) on Unix platforms or a common internet file system (CIFS) on Windows. Both of these network-based file system protocols allow for simplified management, ease of data expansion and multiple access points from applications servers. Load balanced installations can quickly make use of both file system types. Deploying storage on a local application server can also be implemented, but is not recommended. File system content can range from two to five times database content. File system content from a block perspective is touched less frequently then the database file system. Clients can opt to configure their systems to a lesser performing RAID configuration with slower spindles as I/O performance is less of a concern. The exception would be streaming content and media. Typically, we recommend that clients determine a storage quota per student and faculty member as well as account for passive users that require less storage quota. Assume that faculty will have greater storage requirements. Below is a simple example: Profile Quota Users Storage Needs Faculty 5GB TB Student 500MB 10,000 5TB Observer 20MB 1,000 20GB Sizing the file system is dependent on archival strategies, data management policies, RAID configuration and I/O performance standards. We typically assume that the file system will require about 100 I/O per second per application server at peak. To calculate your I/O per second need, multiply this metric against the number of application servers in your deployment. Database Data File Storage Blackboard Learn makes use of a relational database system (Oracle and SQL Server) for the storage of database content. Clients may make use of a network file share (NFS), ISCSI (networked block-level) or direct attached storage (block-level) on Unix platforms. Windows SQL Server clients may only use ISCSI (networked block-level) or direct attached storage (blocklevel). The database storage requirements of institutions can vary. Typically, database content can range from two to five times less then file system content. Sizing the database is dependent on archival strategies, data management policies, RAID configuration, and, most importantly, I/O performance standards. We typically assume that the file system will require about 500 I/O per second per application server at peak. To calculate your I/O per second need, multiply this metric against the number of application servers in your deployment. The primary driver for database storage should be performance. Blackboard Inc 2008 Page 4

5 Description Small Institution Medium Institution Large Institution Database Tier Storage Performance 1 Sun Fire T2000, T5220 ot T5240 Server 6 to 8 Core UltraSPARC T2 Processor 1.2 GHz 8 to 32GB memory 1 Sun Fire T5240 Server 8 Core UltraSPARC T2 Processor 1.4 GHz 16 to 32GB memory 1 Sun T5240 or Sun SPARC Enterprise M5000 Server 2 x 8 Core UltraSPARC T2 Process 1.4 GHz or 8 x 2 Core SPARC64 VI Processors (~2.15GHz) 16 to 32GB memory The database tier requires very high I/O performance and thus utilizes fibre channel drives with 10,000 to 15,000 RPMs. In order to deliver adequate I/O throughput, it also should make use of smaller capacity drives so that there will be more spindles to reduce seek times and improve data transfer rates. The configurations defined in this guide have been validated to support adequate I/O throughput for the user loads defined for each configuration. When sizing storage, please be sure to first determine how much storage your institution will need. Second, determine how this storage can be spread across multiple trays and disks to optimize performance throughput. Remember that the shared file system can require upwards of five times the storage of the database, however the database can utilize five times the number of I/O operations per second than the file system. Description Small Institution Medium Institution Large Institution Content Storage Tier Network Attached Storage Architecture or ZFS for Solaris Up to 2.2 TB of usable storage Network Attached Storage Architecture or ZFS for Solaris Up to 5 TB of usable storage Network Attached Storage Architecture or ZFS for Solaris Up to 10 TB of usable storage 7.2k to 10k RPM SATA or FC 7.2k to 10k RPM SATA or FC 7.2k to 10k RPM SATA or FC Database Storage Tier Network Attached Storage Architecture, ISCSI or FC-SAN Up to 300 GB of usable storage Network Attached Storage Architecture, ISCSI or FC-SAN Up to 600 GB of usable storage Network Attached Storage Architecture, ISCSI or FC-SAN Up to 1 TB of usable storage 10k to 15k RPM FC 10k to 15k RPM FC 10k to 15k RPM FC Blackboard Inc 2008 Page 5

6 Conclusion The information in this sizing guide is based on analysis and benchmarking models from the Blackboard Performance Team. It is indended to provide guidance. It is not intended as a service level agreement. Deployments will differ from institution to institution based on a vartiey of factors including the usage of the application. Contact Blackboard Technical Solutions Engineering for more informaiton on systems architecture design and detailed sizing questions. Worldwide Headquarters 650 Massachusetts Avenue NW Sixth Floor Washington D.C Blackboard, the Blackboard logo, Blackboard Perfomance Lab, Blackboard Learn, Blackboard Academic Suite, Blackboard Learning System, Blackboard Community System, Blackboard Content System, Blackboard Outcomes System, and Blackboard Portfolio System are either registered trademarks or trademarks of Blackboard Inc. in the United States and/or other countries. Dell and PowerEdge are registerd trademarkes of Dell Inc. Intel and Xeon are registered trademarks of Intel Corporation. Microsoft, Windows, and SQL Server are registered trademarks of Microsoft Corporation in the United States and/or other countries. Java is a registered trademark of Sun Microsystems, Inc. in the United States and/or other countries. Oracle is a registered trademark of Oracle Corporation in the United States and/or other countries. Red Hat is a registered trademark of Red Hat, Inc. in the United States and/or other countries. Linux is a registered trademark of Linus Torvalds in the United States and/or other countries. Apache is a trademark of The Apache Software Foundation in the United States and/or other countries. Quest, Quest Toad, Quest Spotlight, and Quest LiteSpeed are either registered trademarks or trademarks of Quest Software in the United States and/or other countries. Coradiant and Coradiant TrueSight are registered trademarks of Coradiant, Inc. Other product and company names mentioned herein may be the trademarks of their respective owners. Patents pending. Blackboard Inc 2008 Page 6

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