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Architecting the Network for SharePoint

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1 Architecting the Network for SharePoint 20102007
Presented by Michael Koyfman Solution Architect

2 Q110 Gartner ADC Market Share
F5 Continues to be #1 in the WW Application Delivery Controller Market for Q110 Q110 Gartner ADC Market Share Q110 ADC* Market Share Leaders F5 : 44.2% Cisco: 22.4% Citrix: 10.6% Q110 ADC Market Share Revenue Leaders F5: $126.4 Million Cisco: $64 Million Citrix: $30.4 Million Q110 ADC Q/Q Revenue Growth F5: 12.5% Cisco: -8.6% Citrix: -15% Q110 ADC Total Market Numbers Revenue: $285.7 Million Q/Q Revenue Growth: 1% *Application Delivery Controller (ADC) Segment Includes: Server Load Balancing/Layers 4-7 Switching and Advanced (Integrated) Platforms Citrix 10.6% Radware 8.8% Cisco 22.4% Others 13.9% F5 NETWORKS 44.2% SOURCE: Gartner

3 F5 Dominates in Advanced Platform ADC Segment for Q110
Q110 Gartner Advanced Platform ADC Market Share Q110 Advanced Platform ADC* Market Share Leaders F5: 61% Citrix: % Radware: 10.5% Q110 Advanced Platform ADC Market Share Revenue Leaders F5: $126.4 Million Citrix: $30.4 Million Radware: $21.7 Million Q110 Advanced Platform ADC Q/Q Revenue Growth F5: % Citrix: -15% Radware: 2.4% Q110 Advanced Platform ADC Total Market Numbers Revenue: $207.1 Million Q/Q Revenue Growth: 4.3% *Advanced Platform Segment Includes: ADCs that integrate several functions (typically more than four) on a single platform (for example, load balancing, TCP, connection management, SSL offload, compression and caching) Radware 10.5% Others 13.8% Citrix 15.7% F5 NETWORKS 61% SOURCE: Gartner

4 Leadership Position Magic Quadrant for Application Delivery Controllers, 2009 F5 Networks - Strengths F5 Networks has a broad and comprehensive vision with industry-leading understanding of the needs of application development, deployment and management. The vendor has a comprehensive feature set with a full range of extensibility delivered through iRules and iControl, and integration with popular integrated development environments (IDEs), such as Eclipse and .NET/Visual Basic. F5 has developed a very large community of committed users (using F5's DevCentral portal) that helps fuel the use of iRules to solve unique data center application challenges, creating a loyal and engaged user base. F5 has a solid financial position and continued market-leading position. SOURCE Link

5 The Leader in Application Delivery Networking
Users Application Delivery Network Datacenter At Home In the Office On the Road SAP Microsoft Oracle

6 Purpose: How can the Network be Leveraged to achieve:
Scalability Building the Right Infrastructure to Meet the Current User Load, and Also Allow for Future Growth. High Availability Architecting the “Bullet Proof” SharePoint Deployment Eradicating the Single Points of Failure Performance Building a SharePoint Deployment with the Best Possible End User Experience

7 Load Balancing Concepts
User Requests The Typical Single Server Deployment Users connect directly to the open IP:Port of the Server No redundancy, little scalability Single Server

8 Load Balancing Concepts
Introduction of the Load Balancer Hardware Device Different models for capacity Sits in front of the server farm, accepting the user connections, and then dispatching the connection to a chosen server. Most modern LBs are multi-function (caching, compression, rate shaping, firewalling, etc…) Most LBs can load balance multiple types of traffic User Requests Farm of Servers Instead of a single server, a Load Balancer allows you to scale the number of available servers

9 Load Balancing Concepts
How it works: A properly configured Load Balancer is constantly monitoring the health and availability of the servers in the farm. It will use this information to help it make a load balancing decision. Instead of the User making the connection directly to the server, the User makes a connection to the Virtual Server, which resides on the external facing side of the Load Balancer The Load Balancer will send the connection to a specific server based upon The LB algorithm selected Health & Availability of the servers User Requests Farm of Servers

10 Load Balancing Concepts
Load Balancing Methods: Some are static Round Robin Ratio Some are dynamic, and try to take certain network and server characteristics into account Least Connections Fastest Server Trending User Requests Farm of Servers Historically, static methods were preferred, as they tended to have the lightest impact on the Load Balancer, however today’s Load Balancers are capable of handling even complex LB algorithms without any performance degradation. F5 recommends using a dynamic LB method with SharePoint.

11 Load Balancing Concepts
Persistence: Once a user is sent to a specific server, do follow on connections/requests need to be sent to the same server? Common Persistence Methods: Source IP Based Cookie Based SSL ID Custom Methods User Requests Farm of Servers Most SharePoint deployments do not require persistence, however since a SharePoint front end can build an object cache, there is benefit to enabling it. It’s recommended to use a combination of Cookie & Source IP based persistence.

12 Load Balancing Concepts
Leveraging a Load Balancer to Eliminate the Single Points of Failure Redundant Load Balancers Instant failover Share state Redundant & Meshed Switch Architecture No single path out to the next hop Spanning Tree support Multihomed Networks Multiple ISP links into the Data Center Multiple Data Centers “Global” load balancing User Requests Farm of Servers Is it possible to eliminate all the Single Points of Failure? Is ‘5 9s of uptime’ achievable? Realistic?

13 What Else Can My Load Balancer Do?
*Differs by vendor, but most include technologies to alleviate server load, accelerate traffic, and minimize bandwidth utilization. User Requests SSL termination Compression Content Spooling TCP multiplexing TCP optimizations Browser optimizations Rate shaping Intelligent Browser Referencing (caching at the browser) Results from using these features with SharePoint 2007 can be found here Farm of Servers

14 Real-World Performance
350 Million Page Hits in 1 Week 1/3 Reduction in Servers 1/3 Reduction in Licenses 1/3 Reduction in Management Time 114.8 Million 5 95% Fewer Connections 1.87 Terabyte 621 Gigabytes 66% Reduction in Bandwidth 3 Seconds 1 200% Faster End-to-End Page Load Time 14

15 On to SharePoint………

16 The Single SharePoint Server Deployment
User Requests No Redundancy Complete failure with any piece No Scalability Measurable maximum capacity 50 to 75 Requests per second max Performance Concerns Early performance degradation Single Server: Web Server Application Server Database No Direct Upgrade from a stand alone to a farm MSFT – SSD is good for evaluation, deployments with minimal number of sites and you want to minimize overhead Microsoft on the Single Server Deployment Good for evaluation Good for very small deployments Benefit of minimal overhead

17 Scaling Out The Deployment
“The Small Server Farm” Common initial deployment Database split from Front End Servers Meets requirements for HA Allows for future scalability 175 to 250 RPS Maximum Front End Servers are responsible for Servicing web requests Application Services, such as Searching Indexing User Requests Each Server Running Web Server Application Roles Clustered or Mirrored SQL Database Source :

18 Scaling Out The Deployment
“The Medium Server Farm” Same as the Small Server Farm, however the Application Server has been split from the Web Servers 175 to 250 RPS Maximum Allows the Application Server’s CPU intensive functionality (search, excel services, etc) to have dedicated CPU cycles User Requests Web Servers Application Server Clustered or Mirrored SQL Database Source:

19 Scaling Out The Deployment
“The Large Server Farm” All Servers, including Web, Application, and DB are scaled to meet demand Can scale to support “Hundreds of thousands of users” Availability Work Sheet from Microsoft User Requests Web Servers Load Balancing of Application Servers is also possible Application Servers Clustered or Mirrored SQL Database Source:

20 Scalability – The Art of Sizing
The Challenge is to size the deployment appropriately How many servers are needed? How are the server roles split? What type of hardware should be used? The 2 Sided Sizing Dilemma Microsoft can’t give precise sizing guidelines Customers can’t precisely profile their user base Fortunately, the amount of accurate and reliable sizing information is dramatically increasing

21 Scaling the Network vs. Scaling the Servers
What needs to be considered when sizing? Is scaling a server infrastructure linear with scaling the network? Considerations for server sizing include How many total users? How many concurrent users on average? Typical behavior of users? Posting, searching…. Etc. How many page views per person? How many users at peak times? How many sites are planned? What hardware architecture is being used? Considerations for network sizing include What are the peak new connections per second? What is the peak number of users/connections? What is the peak bandwidth being consumed? How many servers is the Load Balancer responsible for monitoring? What else will the Load Balancer be doing? Caching, Compression……etc

22 BIG-IP Hardware Line-up
2 x Hex core CPU 16 10/100/ x 10 SFP+ 10Gbps 2x 320 GB HD (S/W RAID) + 8GB CF 32 GB memory 100K TPS / 15Gb bulk 12 Gbps max software compression 40 Gbps Traffic BIG-IP 8950 BIG-IP 8900 2 x Quad core CPU 16 10/100/ x 1GB SFP + 2x 10Gb SFP+ 2x 320 GB HD (S/W RAID) + 8GB CF ? 16 GB memory 56K TPS / 9.6Gb bulk 8 Gbps max software compression 20 Gbps Traffic BIG-IP 6900 2 x Quad core CPU 16 10/100/ x 1Gb SFP + 2x 10Gb SFP+ 2x 320 GB HD (S/W RAID) + 8GB CF 16 GB memory 58K TPS / 9.6Gb bulk 8 Gbps max hardware compression 12 Gbps Traffic BIG-IP 3900 2 x Dual core CPU 16 10/100/ x 1Gb SFP 2x 320 GB HD (S/W RAID) + 8GB CF 8 GB memory 25K TPS / 4 Gb bulk 5 Gbps max hardware compression 6 Gbps Traffic Quad core CPU 8 10/100/ x 1Gb SFP 1x 300 GB HD + 8GB CF 8 GB memory 15K TPS / 3.8 Gb bulk 3.8 Gbps max software compression 4 Gbps Traffic BIG-IP 3600 Dual core CPU 8 10/100/ x 1Gb SFP 1x 160 GB HD + 8GB CF 4 GB memory 10K TPS / 2 Gb bulk 1 Gbps max software compression 2 Gbps Traffic BIG-IP 1600 Dual core CPU 4 10/100/ x 1Gb SFP 1x 160GB HD 4 GB memory 5K TPS / 1 Gb Bulk 1 Gbps max software compression 1 Gbps Traffic

23 Sizing – Rough Guidelines
A single server deployment can handle between 50 to 75 RPS. When scaling out Web Front Ends, assume each one can handle roughly 100 RPS. Assume 85 RPS if Query Search is running on the WFE. According to Microsoft, use the following to determine how many RPS a user will make Light user, access every 180 secs (20/hr), 1 RPS = 180 active users Typical user, access every 100 secs (36/hr), 1 RPS = 100 active users Heavy user, access every 60 secs (60/hr), 1 RPS = 60 active users Extreme user, access every 30 secs (120/hr), 1 RPS = 30 active users References:

24 Sizing Resources Microsoft SharePoint 2007 Development
Hoffman, Foster. Sams Publishing Part I dives into some sizing exercises Microsoft Office SharePoint Server 2007 Administrator’s Companion Bill English. Microsoft Press. Chapters 2 & 3 discusses sizing in detail Microsoft Technet Good information with sizing worksheets Microsoft SharePoint Products and Technologies Team Blog Joel Oleson & Mike Watson’s Blog Entries – MS IT Case Study

25 Sizing Resources HP Sizing and Configuration Tool for Microsoft Office SharePoint Server 2007 Plug in various information about user base, and it returns a full suggested hardware package One of the most comprehensive sizing guides out there.

26 Sizing Guidelines Sizing the SQL cluster for Performance and Availability Is there a strategy to maintaining a certain maximum size to a specific SP database? Should I create separate DB’s or SQL instances for different SP sites? There is a strategy for SP DB implementation, but it has more to do with making administration (i.e. backups & restores) easier than performance. Database Clustering High Availability and Scalability of SQL back end is achieved via SQL clustering technology. No Load Balancer needed. For replication, both data mirroring and log shipping is supported.

27 Sizing Guidelines Sizing the SQL cluster for Performance and Availability As a guideline, what is the recommended number of Web Front Ends to SQL servers? Best Practices HA Minimum of 2 Authenticated Traffic “4:1”* Anonymous Traffic “6:1”* Suggested Limit “8:1”** Database Clustering High Availability and Scalability of SQL back end is achieved via SQL clustering technology. No Load Balancer needed. For replication, both data mirroring and log shipping is supported. *Source **Source

28 Sizing vs. Performance Docs
2 Great Resources that compare how sizing affects performance Microsoft Office SharePoint Server 2007 on HP ProLiant servers – performance summary Discusses when to scale up vs. out (more cores vs. more servers) Plan for performance and capacity (Office SharePoint Server) Discusses acceptable performance limits

29 High Availability Health Monitoring: How does the appliance determine if the servers are up/down? Load Balancing: How does the appliance distribute traffic to the Front Ends? Persistence: Can (and should) the appliance keep a user attached to the same Front End that they initially attached to?

30 Multiple Data Center Challenge
Client Site 1 Site 2 Router Router BIG-IP LTM BIG-IP LTM SharePoint Farm SQL DB SharePoint Farm SQL DB Can I deploy SharePoint in Active/Active Redundant DataCenters?

31 Multiple DataCenter Challenge
Router BIG-IP LTM SharePoint Farm SQL DB Site 1 Client SharePoint Farm SQL DB Site 2 Can SharePoint be deployed with Active/Active Redundant DataCenters? Not in any way supported by Microsoft. Reasoning: SQL replication engine (mirroring/log shipping) just isn’t ready to handle real time replication with concurrent SharePoint user access

32 Multiple Data Center Challenge
Strategies to replace the Active/Active Deployment Active/Standby Data Centers Splitting SharePoint Sites, using both Data Centers Data Center Multihoming

33 Multiple Data Center Challenge
Router BIG-IP LTM SharePoint Farm Site 1 (Active) Client SharePoint Farm SQL DB Site 2 (Standby) Solution 1: Active/Standby DataCenter All users sent to DC1, unless it is no longer accessible. Then all users will be sent to mirrored instanced in DC2 Good solution, the main drawback is the expense.

34 Multiple DataCenter Challenge
Client Solution 2: Multiple SharePoint Sites DC 1 (Active for Site A) (Standby for Site B) DC 2 (Active for site B) (Standy for site A) SharePoint split into multiple sites, each using different SQL instances Site A uses Data Center 1 as its primary DC, and Data Center 2 as its backup Router Router BIG-IP LTM BIG-IP LTM SharePoint Farm SharePoint Farm SQL DB Site A = Site B = Multiple Benefits, including no ‘dark fiber’.

35 Multiple Data Center Challenge
Strategy 3: Multihoming the Data Center Clustered or Mirrored SQL Database Application Server Web Servers ISP (Link) Load Balancing Routing (BGP) Solution

36 Multihoming the Data Center BGP Solution
Use 2 or more separate ISPs to peer with each other, creating a single ‘virtual’ ISP link. Benefits: ISP Links share IP space, so DNS caching not an issue Drawbacks: Convergence time can be long. Difficult to fully leverage all available bandwidth Web Servers Application Server Clustered or Mirrored SQL Database Routing (BGP) Solution

37 Multiple Data Center Challenge
ISP Load Balancing Multiple ISP links are used. DNS used to direct users in via ISP1, ISP2, ISP3, etc.. Benefits: Performance based usage of ISP links Better Bandwidth Utilization Drawbacks: DNS caching Web Servers Application Server Clustered or Mirrored SQL Database ISP (Link) Load Balancing

38 Performance Problem: How Can The Content Be Delivered To The End User In The Most Efficient Way Possible? Combination of Technologies

39 SSL Acceleration SSL/TLS Encrypted Clear Text HTTP
SSL Connections to a server can eat up as much as 30% of available CPU cycles. SSL on NT/IIS means up to 37x fewer connections/second SSL Acceleration Devices typically have specialized ASIC processors for terminating SSL. SharePoint officially supports SSL offloading SSL/TLS Encrypted Clear Text HTTP * Source: Networkshop Scaling eCommerce Infrastructure

40 Control Bandwidth Usage
The F5 Solution Business Benefit Control bandwidth usage and spending Minimize impact on business-critical applications Get more bandwidth from the same size pipe Control traffic spikes Rate Shaping + iRules - Bandwidth management to prioritize high-priority applications over P2P traffic and other low-priority applications Packet Filtering - Selective filtering of P2P sites based on protocol, addresses, and/or ports KaZaa & Video Conferencing Oracle HTTP Traffic 4x 3x 2x 1x Client The Rate Shaping Module allows for per-application, per-protocol and per-user basis to help determine what’s actually on the network and how it is behaving and affecting other traffic. Based on this information, administrators can classify, queue, shape, and rate-control traffic with policies to ensure better application response time for priority traffic, by eliminating bandwidth congestion and competition for their priority applications. The Rate Shaping module: Ensures that critical applications are not impacted by non-priority traffic Delivers optimal application performance by allocating more bandwidth for higher priority applications Eliminates special purpose Rate Shaping products for simplified, centralized traffic management capabilities Provides flexible bandwidth limits, bandwidth borrowing, and traffic queuing Controls rate classes based on any traffic variable Enables application bandwidth to be shared across similar priority applications for better resource sharing Ensures that specific types of application traffic stay within authorized boundaries At a high level, the Rate Shaping feature allows for traffic limiting, prioritization and borrowing, for maintaining enough bandwidth and fast service for high priority applications and traffic. BIG-IP users can define traffic and application limits, control the rate at which those resources are allowed to spike or burst, provide queuing to prioritize traffic types, and define relationships where certain traffic types can borrow from other traffic types. Control per application, per protocol, per user 40

41 Fast Cache Unmatched Flexibility Provides Superior Application Offloading
Intelligent memory based cache Full support for static and dynamic content Exclusive “Multi-Store” caching for prioritized application service Superior caching of pre-compressed content Most advanced cache controls - iRules 41

42 HP / F5 Joint SharePoint 2007 Best Practices & Deployment Guide
Joint performance testing to determine best practices for accelerating SharePoint 2007 & 2010 Over 100 separate tests ran & recorded, with varying network conditions, such as latency, packet loss, & bandwidth Whitepaper (results) posted:

43 HP Results Internet – asymmetric BIG-IP LTM with WebAccelerator solution While not able to provide all the capabilities and benefits of a symmetric solution, results show that deploying a single BIG-IP LTM with WebAccelerator appliance in this scenario will have measurable benefits in terms of increased throughput and in providing users with an improved experience. • Typical throughput improvements for the 6Mbps and 1536Kbps tests approached a factor of 2 (double the throughput). Again, it was not possible to emulate sufficient load for the 44Mbps tests to drive the accelerated WAN to capacity, but the trends are similar to the 6Mbps tests and the same degree of improvement should be expected. • The hits-per-page ratio dropped from 3:1 (un-accelerated) to about 1.2:1 (accelerated) showing a good degree of protocol optimization. • Average page (response) times showed improvements ranging from factors of between 3 and 5 (that is, some functions took one fifth of the time). • Client LAN traffic was reduced to 75% of the un-accelerated cases. • A good level of compression was achieved, but note that the users’ browsers are used to un-compress the data and need to be set to do so.

44 Branch Office Scenario Results
Average time for a Document Open decreased 12x Average time for a Page Open decreased by over 6x

45 Internet Scenario Results
Average Page Open Time decreased by over 60% Average Search Time decreased by over 40%

46 Questions to ask ANY vendor
Give me your SharePoint Story What testing have you done with SharePoint? What SharePoint specific development efforts have you undertaken?

47 Questions to ask ANY vendor
How do you determine server availability and health? What’s the recommended method of distributing traffic? What methods does the appliance have for persisting users?

48 F5 Resources F5 SharePoint 2010 Deployment Guide
HP F5 SharePoint Acceleration Doc F5 Microsoft Business Development Team Jeff Bellamy–Business Development Director for the Microsoft Partnership – – Ryan Korock – Senior Solutions Architect – – James Hendergart – Business Development Manager – – Helen Johnson – Solutions Engineer – –


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