Citrix Logins Test

The Citrix Logins test monitors the new logins to the Citrix XenApp server.

Target of the test : Citrix XenApp

Agent deploying the test : An internal agent

Outputs of the test : One set of results for the Citrix XenApp that is to be monitored.

Configurable parameters for the test

Test Period

How often should the test be executed. By default, this is 15 minutes.

Host

The host for which the test is to be configured.

Port

Refers to the port used by the Citrix server .

Report Using Managertime

By default, this flag is set to Yes. This indicates that the user login time displayed in the DETAILED DIAGNOSIS page for this test and in the Thin Client reports will be based on the eG manager's time zone by default. Set this flag to No if you want the login times displayed in the DETAILED DIAGNOSIS page for this test and in the Thin Client reports to be based on the Citrix server’s local time.

Report by Domain Name

By default, this flag is set to Yes. This implies that by default, the detailed diagnosis of this test will display the domainname\username of each user who logged into the Citrix server. This way, administrators will be able to quickly determine which user logged in from which domain. If you want the detailed diagnosis to display the username alone, then set this flag to No

Report by Client Name

By default, this flag is set to No. If set to Yes, this test will report metrics for each client machine from which users logged into the XenApp server - i.e., the host name of the client machines will be the descriptors of this test. In this case therefore, the User name column of the detailed diagnosis of this test will indicate the names of the users who logged into the XenApp server.

DD Frequency

Refers to the frequency with which detailed diagnosis measures are to be generated for this test. The default is 6:1. This indicates that, by default, detailed measures will be generated every time this test runs, and also every time the test detects a problem. You can modify this frequency, if you so desire. Also, if you intend to disable the detailed diagnosis capability for this test, you can do so by specifying none against DD Frequency.

Detailed Diagnosis

To make diagnosis more efficient and accurate, the eG Enterprise embeds an optional detailed diagnostic capability. With this capability, the eG agents can be configured to run detailed, more elaborate tests as and when specific problems are detected. To enable the detailed diagnosis capability of this test for a particular server, choose the On option. To disable the capability, click on the Off option.

The option to selectively enable/disable the detailed diagnosis capability will be available only if the following conditions are fulfilled:

  • The eG manager license should allow the detailed diagnosis capability
  • Both the normal and abnormal frequencies configured for the detailed diagnosis measures should not be 0.
Measurements made by the test
Measurement Description Measurement Unit Interpretation

New logins

Indicates the number of new logins to this Citrix XenApp during the last measurement period.

Number

A consistent zero value could indicate a connection issue.

Using the detailed diagnosis of the New logins measure, you can not only identify the users who logged in recently, but can also figure out when each user logged in and from which client machine.

Percent new logins

Indicates the percentage of current sessions that logged in during the last measurement period.

Percent

 

Sessions logging out

Indicates the number of sessions that logged out.

Number

If all the current sessions suddenly log out, it indicates a problem condition that requires investigation.

With the help of the detailed diagnosis of the Sessions logging out measure, you can identify the users who logged out, when every user logged in and from which client machine, and the duration of each user’s session. In addition, you can also find out the time duration(in minutes) and the percentage of time for which the user was idle during each session. Abnormally long sessions on the server can thus be identified.