Microsoft SharePoint 2013-Streamlined Topology Model
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Streamlined topologies for SharePoint Server 2013 optimize system resources and maximize performance for users. Topologies scale out by standardizing servers at each tier - front-end, batch processing, and databases. As load increases, identically configured servers are added. Specialized servers may be used for services that impact performance, like search or Excel services. Distributed cache and request management servers are recommended for farms with more than 10,000 users.
Microsoft SharePoint 2013-Streamlined Topology Model
- 1. Streamlined Topologies for SharePoint Server 2013 Topology design guidance for maximizing system resources A new approach to farm design Example farm topologies < 100 users <1,000 users <10,000 users More than 10,000 users As an alternative to the traditional farm design, Microsoft® Scaling out SharePoint® 2013 topologies can be designed to optimize system The front-end, batch processing, and database tiers are standardized. Limited deployment Fault tolerance for simple workloads with Dedicated search servers for up to 10 million items. Additional server types to support large farms. resources and to maximize performance for users. When another server is needed at one of these layers, an identically small volumes of content configured server is added. Three tiers: This farm represents each of the server roles that are recommended. For each server role the servers are One server with all roles: Optimizing each tier Evaluation Two tiers: Front-end servers configured identically. Scale each server role independently. Large farms benefit by adding dedicated servers for Specialized workloads Combined front-end and batch Batch processing servers Distributed Cache and by adding Request Management. Front-end servers — Service applications, services, and components Very light and simple workloads Some service applications can cause spikes in performance, such as processing servers Database servers that serve user requests directly are placed on front-end servers. Excel Calculation Services or PerformancePoint. If an organization Database servers These servers are optimized for fast performance. Scale the number of servers as needed. uses these service applications heavily, the recommendation is to Batch-processing servers — Service applications, services, and Scale the number of servers as needed. Distributed Cache and Request place these on dedicated servers. If these service applications are Management components that process background tasks are placed on a Front end Dedicated search servers used regularly, they can be placed on front-end servers. middle-tier of servers referred to as batch processing servers. Front end and These servers are optimized to maximize system resources. These Search Limited deployments are typically batch processing Query servers can tolerate greater loads because these tasks do not affect The search workload uses a lot of resources. When scaling beyond used for product evaluation, ....... .... performance observed by users. two batch-processing servers, place this role on dedicated servers. For development and testing, or for .... .... Database-servers — guidance for deploying database servers more information about configuring search components, see the environments that have limited remains the same. following model: Enterprise Search Architectures for SharePoint numbers of users and don t require Batch processing Front end Dedicated search servers Specialized workloads Server 2013. fault-tolerance. Databases Crawl In a small farm, server roles can be combined on one or two servers. Query Distributed Cache and Request Management For example, front-end services and batch-processing services can be .... .... .... .... .... combined on a single server or on two or more servers to achieve For small and medium-size architectures, Distributed Cache can remain on the front-end servers. Beyond 10,000 users this service is ....... redundancy. expected to work better on dedicated servers. At this scale, Request Databases Batch processing Management can be added and shared on the same servers with Search databases Crawl Distributed Cache. Request Manager is CPU intensive. Distributed Cache is memory intensive. Important: These example topologies show the progression of adding additional server roles. ....... ....... .... .... Server roles Servers can be virtual or physical. All numbers associated with these topologies are estimates and do not replace the need for adequate capacity planning and management. Databases Search databases Front-end servers — optimize for low latency Distributed Cache and Request Access Services Business Data Connectivity Management Servers — ....... ....... optimize for very high Managed Metadata throughput User Profile Batch-processing servers — optimize for load Specialized workloads (if needed) — optimize Scale guidance for each server role User Profile Synchronization for medium throughput Workflow Search Machine Translation Excel Calculation Work Management PerformancePoint Project Server roles Performance goal Components and services Candidates for dedicated servers Database servers — optimize for throughput Consistent latency: Distributed Cache Distributed Cache and Request Latency — very low (<5 millisecond) Microsoft SharePoint Foundation Web Application Management servers Throughput — very high Request Management Resource utilization — medium ....... Fast response to user requests with consistent Access Services and Access Secure Store Service Excel Calculation Scaling the database layer with storage groups Front-end servers latency: Services 2010 State Performance Point Latency — low (<500 millisecond) Business Data Connectivity Subscription Settings Project Throughput — medium Central Administration User Code Search Query Resource utilization — low-medium ..... Managed Metadata Microsoft SharePoint Foundation User Profile Visio Graphics Web Application Storage groups Storage groups is a concept in which similar types of databases are grouped together and scaled out independent of the rest of the databases based on need. All databases within a storage group are treated the same with backup procedures and restore protocols. The best practice is to include the Batch-processing servers configuration database with the content database group. Maximize resources with high throughput: Crawl Target User Profile Synchronization Search Crawl Latency — high (>1 minute) Machine Translation Word Automation Throughput — high Microsoft SharePoint Foundation Work Management Database group 1 Database group 2 Database group 3 ..... Resource utilization — high to very high Web Application PowerPoint Conversion Workflow timer service Specialized workloads Fairly consistent latency: Excel Calculation Microsoft SharePoint Foundation (if needed) Latency — low (<500 milliseconds) PerformancePoint Web Application Throughput — medium Project ..... Content databases and configuration Search databases All other SharePoint databases Resource utilization — low-high Search database All databases Fast response and consistent latency: For database architectures, Latency — very low (<5 milliseconds) see _____________________ Throughput — very high Resource utilization — low-medium ....... The Microsoft Office Division s SharePoint Server 2013 farm A key part of the Microsoft engineering process is running a production Performance during peak hours environment using pre-release builds of SharePoint 2013. This medium-size farm supports the Microsoft Office Division. Role and hardware Server count Average CPU Memory utilization Notes Workload Distributed cache and 12% 8 GB Two servers for availability. A load 15,000 users Request Management balancer is necessary to balance 2,500 unique users per hour VM, 4 cores, 14 GB RAM requests to these two servers 8,8000 active users per week 1.7 million requests per day Collaboration, social, document management, Project 204,106 profiles Front end 45% 11 GB Three servers allow room for spikes in 1 Web application VM, 4 cores, 14 GB RAM performance. Dataset 1.3 Terabytes total data 1,001,141 documents 10 content databases Batch processing 80% 12 GB These servers run highly utilized to Largest content database—290 Gb VM, 4 cores, 14 GB RAM maximize the hardware. These do not 8,297 site collections process user requests. Largest site collection—275 Gb (tested at larger than recommended limit) Service-level agreement (during peak hours) The SLA is set to 99.9% availability to allow for upgrading from build to build every week during the product development cycle. Database 11% 46 GB SQL Server is deployed to physical 8 cores, 64 GB RAM servers. One server is dedicated to the logging database for collecting information about the farm. Two database servers is sufficient to support the load and provide high availability. © 2013 Microsoft Corporation. All rights reserved. To send feedback about this documentation, please write to us at ITSPdocs@microsoft.com.