Citrix Farm Users Test

A value of 0 indicates that the user is not currently connected to the Citrix farm. 

A consistently high latency may be indicative of performance degradations with the Citrix farms. Possible reasons for an increase in latency could be increased network delays, network congestion, Citrix farm slow-down, too many simultaneous users on the Citrix farm etc. 

Ideally, the deviation in latencies over a session should be minimum so as to provide a consistent experience for the user.

This value indicates the percentage of memory resources that are used up by a specific user. By comparing this value across users, an administrator can identify the most heavy users of the Citrix farm. Check the detailed diagnosis to view the offending processes/applications.

This measure serves as a good indicator of CPU usage in load-balanced environments, where the user load is balanced across all processors. Excessive CPU usage by a user can impact performance for other users. This is why, a high value for this measure is a cause for concern. In such cases, check the detailed diagnosis to view the offending processes/applications.

The CPU usage for user’s processes measure averages out the total CPU usage of a user on the basis of the number of processors. For instance, if your Citrix server is using an 8-core processor and the total CPU usage of a user across all his/her sessions amounts to 80%, then the value of the CPU usage for user’s processes measure for that user will be 10 % (80/8 processors = 10). This accurately denotes the extent of CPU usage in an environment where load is uniformly balanced across multiple processors. However, in environments where load is not well-balanced, the CPU usage for user’s processes measure may not be an accurate indicator of CPU usage per user. For instance, if a single processor is used nearly 80% of the time by a user, and other 7 processors in the 8-core processor environment are idle, the CPU usage for user’s processes measure will still report CPU usage as 10%. This may cause administrators to miss out on the fact that the user is actually hogging a particular processor! In such environments therefore, its best to use the CPU time used by user’s sessions measure! By reporting the total CPU usage of a user across all his/her sessions and across all the processors the target Citrix server supports, this measure serves as the true indicator of the level of CPU usage by a user in dynamic environments. For instance, in the example above, the CPU time used by user’s sessions of the user will be 80% (and not 10%, as in the case of the  CPU usage for user’s processes measure). A high value or a consistent increase in the value of this measure is hence serious and demands immediate attention. In such situations, use the detailed diagnosis of this measure to know what CPU-intensive activities are being performed by the user.  

These metrics measure the collective I/O activity (which includes file, network and device I/O's) generated by all the processes being executed by a user. When viewed along with the system I/O metrics reported by the DiskActivity test, these measures help you determine the network I/O. Comparison across users helps identify the user who is running the most I/O-intensive processes. Check the detailed diagnosis for the offending processes/applications.    

Page Faults occur in the threads executing in a process.  A page fault occurs when a thread refers to a virtual memory page that is not in its working set in main memory.  If the page is on the standby list and hence already in main memory, or if the page is in use by another process with whom the page is shared, then the page fault will not cause the page to be fetched from disk. Excessive page faults could result in decreased performance. Compare values across users to figure out which user is causing most page faults.

Comparison across users reveals the user who is being a drain on the virtual memory space.

A consistent increase in the handle count over a period of time is indicative of malfunctioning of programs. Compare this value across users to see which user is using a lot of handles. Check detailed diagnosis for further information. 

Comparing these values across users will reveal which user is sending/receiving bandwidth-intensive sound/audio files over the ICA channel.

To minimize bandwidth consumption, you may want to consider disabling client audio mapping.

Comparing these values across users will reveal which user’s COM port is sending/receiving bandwidth-intensive data over the ICA channel.

Comparing the values of these measures across users will reveal which user is performing bandwidth-intensive file operations over the ICA channel.

If bandwidth consumption is too high, you may want to consider disabling client drive mapping on the client device. Client drive mapping allows users logged on to a virtual desktop from a client device to access their local drives transparently from the ICA session. Alternatively, you can conserve bandwidth by even refraining from accessing large files with client drive mapping over the ICA connection.

Comparing the values of these measures across users will reveal which user is issuing bandwidth-intensive print commands over the ICA channel.

If bandwidth consumption is too high, you may want to consider disabling printing. Alternatively, you can avoid printing large documents over the ICA connection.

Comparing the values of these measures across users will reveal which user and which virtual desktop is performing bandwidth-intensive operations for a session.

Compression reduces the size of the data that is transacted over the ICA channel.

Comparing the values of these measures across users will reveal which client has been configured with a very low and a very high compression ratio.

In the event of high bandwidth usage over an ICA channel, you can set a higher compression ratio for the corresponding client and thus reduce bandwidth consumption.

Comparing the values of these measures across users will reveal which user has been transmitting/receiving bandwidth-intensive data channel traffic.

Comparing the values of these measures across users will reveal which user has been transmitting/receiving bandwidth-intensive multimedia traffic.

Comparing the values of these measures across users will reveal which user has been transmitting/receiving bandwidth-intensive flash data.

Comparing the values of these measures across users will reveal which user has been transmitting/receiving bandwidth-intensive USB traffic.

By comparing the value of this measure across users, you can identify the user who is hogging the resources.

Typically, ICA traffic is comprised of many small packets, as well as a some large packets. Large packets are commonly generated for initial session screen paints and printing jobs, whereas the ongoing user session is principally comprised of many small packets. For the most part, these small packets are the highest priority ICA data called Thinwire. Thinwire incorporates mouse movements and keystrokes. 

Compare the value of these measures across users to know which user’s keystrokes and mouse movements are generating bandwidth-intensive traffic. 

Compare the value of these measures across users to know which user is accessing bandwidth-intensive applications that are not in a session window. 

Compare the value of this measure across users to know which user is consuming the maximum HDX bandwidth.

Compare the value of this measure across users to know which user has been logged in for the longest time.

Ideally, the value of this measure should be 100%.

A low value for this measure denotes a high level of inactivity recently.

A high value for this measure indicates that the user has been idle for a long time. Compare the value of this measure across users to know which user has been idle for the longest time.