This article describes how you can deploy to SharePoint Online without performing traditional load testing since it is not permitted.
Although active load testing on SharePoint Online is strongly discouraged, there are other ways you can make sure that a site will not produce a poor user experience when you launch the site.
With SharePoint Online you don't have to do capacity planning, as this is done for you as part of our service offering. With on-premises environments, load testing is used to validate scale assumption and ultimately find the breaking point of a farm; by saturating it with load. With SharePoint Online we need to do things differently. Being a multi-tenant environment, we have to protect all tenants in the same farm, so we will automatically throttle any load tests. This means you will receive disappointing and potentially misleading results if you attempt to load test your environment.
One of the main benefits of SharePoint Online over an on-premises deployment is the elasticity of the cloud. Our large scale environment is set up to service millions of users on a daily basis so it is important that we handle capacity effectively by automatically expanding farms, as and when needed. This article explains how we plan for capacity growth and scale out in place. The article also covers approaches for you to use that don’t involve load testing.
How Office 365 predicts load and expands capacity
SharePoint Online server capacity management work is done through two methods:
Load-balancing on single server farms
Unlike planning for an on-premises environment, for capacity forecasting in SharePoint Online, we are able to compile statistics and graph potential requirements in any given server group. The aggregate demand might look something like the Requests in zone (where a zone is a group of SharePoint farms) growth line in the image below:
While the growth is unpredictable in any one farm, the aggregated sum of requests in a zone is predictable. By identifying the growth trends in SharePoint Online, we can plan for future expansion.
In order to efficiently use capacity and deal with unexpected growth, in any farm, we have automation that tracks front-end load and scales up in place, when needed. The main metric we use as a signal to scale up front ends is CPU load. Our goal is to keep peak CPU load under 40%. This is in order to have enough buffer to absorb unexpected spikes. As load approaches 40% in steady state, we add front ends to farms.
Additional servers can be quickly added to a farm, using those which have been previously added to the zone through the usage forecast.
How do I plan for a site launch?
You should expect that the farm on which your new site launches will automatically be monitored so that new front-end servers are added, as described above. For this reason, we don’t need any notification for your new site launch.
Following other best practices for a single page on SharePoint Online it is unlikely that a new site launch to even 100,000 users will have any impact to the farm.
There are a few strategies to plan for a release of a new SharePoint Online site. As shown in the following image, often the amount of users that are invited is significantly higher than those that actually use the site. This image shows a strategy about how to roll out a release. This method not only helps with performance loading but also can help identify ways to improve the SharePoint site before the large majority of the users see it.
In the pilot phase, it is good to get feedback from users that the organization trusts and knows will be engaged. This way it is possible to gauge how the system is being used, as well as how it is performing.
After this, begins a roll out to all users in waves; getting feedback and reviewing the performance regularly. This has the advantage of slowly introducing the system and making improvements as the system gets more use. This also allows us to react to the increased load as the site is rolled out to more and more users.
Finally, while load tests are prohibited, customers may want to set up periodical pings to the service to measure availability and latency. This will identify a baseline for their site. However, these must be kept to low frequency to avoid throttling issues previously described.