Top 7 Mistakes when Building Scalable SharePoint

Applications

Talbott CrowellThirdM.com

@talbott

http://www.freeimages.com/photo/858598

Mistake #1

Conflating Performance and Scalability

Terminology

PerformanceBehavior and response time for a single user or multiple users under load

ScalabilityBehavior and response time for a growing number of users and volume under load

Performance

A Lamborghini performs well

Ferrari is a high performance vehicle

http://www.freeimages.com/photo/46549

ScalabilityA Greyhound bus performs even better than a Ferrari

when transporting 100 passengers from Boston to San Francisco

https://www.greyhound.com

Example

• The application is built on developer machines and performs great (single user)

• The application is tested by the QA (quality assurance) team, and they find the performance great (single user)

• The application gets deployed into a pilot group of 10 people, the application is still fine because the 10 people don’t use it simultaneously (still effectively single user)

• The application is launched and thousands of users start using it and concurrency issues arise

Solution

• Add load testing to your SDLC (software development lifecycle)• The earlier the better

• Many large Fortune 500 companies have a mandatory stage in their SDLC for volume testing

• Adding it into a continuous integration environment is even better• Better catch it early than right before scheduled

deployment to production

Mitigation

• Strategic•Make sure scalability goals are set

early on• Build scalabilty goals into your

SDLC• Tactical• Testing tools

Mistake #2

Using SharePoint lists as an OLTP database

Solution Architecture• SharePoint stores data in lists

• Lists are abstractions that are physically represented as records in the content database

• If you are building an application in SharePoint, consider the options in storing the data in its own database

SQL

Design for the Future

Office 365 standard design for Provider Hosted Apps is to use a custom SQL database for your application purposes and to write back to SharePoint lists only when needed

SharePoint 2013 Provider Hosted

• Custom Database

• ASP.NET development model

• Connect to SharePoint using CSOM

• Required security token and framework

Mitigation

• Strategic• Education on SharePoint Provider

Hosteted Apps• Tactical• Build POC’s• Make sure custom DB’s are

considered when laying out architecture

Mistake #3

Iterating through SPList

Don’t loop through Lists

• Instead use a CAML Query• SPQuery properties:• Query• RowLimit• ViewFields

Demo

Mitigation

• Strategic• Add volume testing to all stages of

SDLC

• Tactical• Code reviews• Education

Mistake #4

Forgetting about Caching

Types of Caching

• BLOB caching

• Page output cache profiles

•Object cache

• Anonymous search results cache

• Custom code: ASP.NET cache

Caching Consideratins

•What can be cached

•What is heavily used

•What takes up the most time

• How long can you cache those items

Multi-server Farm Considerations

• If you implement custom ASP.NET caching, and need to “clear” the cache

•Make sure there if the same user hits another server it doesn’t still have data cached

Mitigation

• Strategic•Make sure caching is part of the

SDLC

• Tactical• Evaluate different caching

mechanisms

Mistake #5

Failing to estimate and test for concurrent user load

Estimate User Load

• Document Most Common Use Cases

•Weight each Use Case in percentage

• Determine Peak User Count

• Run load tests on use cases weighted by percentage

When should load test be run?

• Answer: the earlier the better

•Waterfall:Requirements, Design, Develop, Functional Testing, Load Testing (sometimes too late), Production

• Agile: build load test into continuous integration

Test Cases

Know BEFORE you start designing, even before you are laying out the solution architecture what a real world scenario will look like

1. Use cases2. Number of users3. Volume of data

Mitigation

• Strategic• Make load and scalability part of the

vision or mission statement for each project

• Tactical• Keep a catalog of non-functional

requirements• Add this to the checklist so every

project requires load estimates

Mistake #6

Failing to account for data growth

Volume of Data

• Application might perform just fine with one to ten Purchase Orders, but what happens when there are hundreds of thousands?

• Know your target volume• Simulate that volume using scripts• Make sure at every step of the way,

volume is considered:• envisioning, designing, implementing,

testing…

Estimate Volume of Data

• After you design your solution estimate what the volume might look like after a year• Load a year’s worth of dummy data•Use PowerShell or C# code

•Make sure developer, testers, and pilot users have volume pre-loaded

Mitigation

• Strategic• Make load and scalability part of the

vision or mission statement for each project

• Tactical• Keep a catalog of non-functional

requirements• Add this to the checklist so every

project requires load estimates

Mistake #7

Not Leveraging Search

Search is very scalable

• Very fast response for indexed data• Tune your crawls, best bets, managed properties•Not fast for immediate feedback•Not right solution for all situations• Crawls can sometime take

hours/days

Mitigation

• Strategic• Increase awareness

• Tactical• POC some functionality leveraging

search•Make sure to understand indexing

and volume time

Final Tip:Know SharePoint Limitations

• Web Applications per farm• Site Collections per Web App• Sites per Collection• Lists per Site• Items per List• SharePoint Limitations• http://bit.ly/limits2013

Review

1. Performance vs Scalabilty2. SharePoint lists not always a good

substitute for transactional database3. For each item in SPList vs CAML Query4. Caching (many flavors)5. Concurrent User Load6. Data volume and growth7. Make sure to leverage Search

Resources• Office Dev Patterns and Practices on GitHub:

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Talbott CrowellThirdM.com

@talbott