Editing Thin client (section)

===Limitations===
To achieve such simplicity, thin clients sometimes lag behind desktop PCs in terms of extensibility. For example, if a local software utility or set of device drivers are needed in order to support a locally attached peripheral device (e.g. printer, scanner, [[biometric security device]]), the thin client operating system may lack the resources needed to fully integrate the required dependencies (although dependencies can sometimes be added if they can be identified). Modern thin clients address this limitation via port mapping or USB redirection software. However, these methods cannot address all scenarios. Therefore, it is good practice to perform validation tests of locally attached peripherals in advance to ensure compatibility. Further, in large distributed desktop environments, printers are often networked, negating the need for device drivers on every desktop.

While running local productivity applications goes beyond the normal scope of a thin client, it is sometimes needed in rare use cases. License restrictions that apply to thin clients can sometimes prevent them from supporting these applications. Local storage constraints may also limit the space required to install large applications or application suites.

It is also important to acknowledge that network bandwidth and performance is more critical in any type of cloud-based computing model. IT organizations must ensure that their network can accommodate the number of users that they need to serve. If demand for bandwidth exceeds network limits, it could result in a major loss of end user productivity.

A similar risk exists inside the data center. Servers must be sized correctly in order to deliver adequate performance to end users. In a cloud-based computing model, the servers can also represent a single point of failure risk. If a server fails, end users lose access to all of the resources supported by that server. This risk can be mitigated by building redundancies, fail-over processes, backups, and [[Load balancing (computing)|load balancing]] utilities into the system. Redundancy provides reliable host availability but it can add cost to smaller user populations that lack scale.