What’s new

A goal of Citrix is to deliver new features and product updates to customers as and when they are available. New releases provide more value, so there’s no reason to delay updates.

To you, the customer, this process is transparent. Initial updates are applied to Citrix internal sites only, and are then applied to customer environments gradually. Delivering updates incrementally helps to ensure product quality and to maximize the availability.

Oct 19, 2020

A Machines based self-service search is now added to the existing Users and Sessions based self-service views in Citrix Analytics for Performance.

The machines based self-service view displays key performance indicators of your Virtual Apps and Desktops machines. The metrics include the machine downtime, the latest consecutive failures, performance indicators of the machine resources (CPU and memory) - the peak usage, and the number of peaks for the selected time period. Overloaded resources can cause session failures, high latency, or high logon duration resulting in poor user experience. This view helps easily troubleshoot the performance issues related to machine resource utilization.

You can access the Machines based self-service view from the Search menu in your CAS service. In the list of services on the Search tab, under the Performance section, select Machines. The Machines based self-service view is also available when you drilldown from black hole machines. To access the view, on the User experience dashboard, in the Failure Insights section, click the Black hole machines number.

For more information on the Machines based self-service view, see Self-service search for Machines.

Machine Statistics view

Citrix Analytics for Performance provides a Machine Statistics view. This view displays a correlation between the resource load and the session experience on the selected machine for the selected time period. This information helps you understand if high CPU or memory usage is related to session failures. You can then explain a poor experience in your Virtual Apps and Desktops environment.

To access the Machine statistics page, in the Machines self-service view, click the machine name link.

Key data points available on this page are:

  • Relevant machine attributes, such as the OS, Site, Delivery Group, and downtime of the machine during the last 24 hours.
  • Machine performance statistics related to resource usage, such as CPU and memory peaks, and the number of spikes over the last 24 hours. Also displayed is a trend of the CPU and memory consumption.
  • Session performance statistics, such as the number of session failures, and peak concurrent session count over the last 24 hours. Also displayed are trends of session failures and session classification.

You can choose to view machine statistics for any 24-hour duration from the last 14 days. The charts are displayed for a default 4-hour time period. A time navigator helps change this time period and also zoom into any duration within the chosen 24-hour time period.

The machine and session performance statistics displayed in the same view help analyze machine resources, their usage pattern and understand if the machine resources have been a possible bottleneck for poor performance.

For more information about this feature, see the Machine Statistics article.

Failure Insights - Black hole machines

Failure Insights in Citrix Analytics for Performance provides insights into session failures that occurred during the chosen time period. This feature is important in helping troubleshoot and resolve session failures faster. It eases the task of admins who need to troubleshoot session failures to improve session availability and thereby, the user experience. In this release, Citrix Analytics for Performance provides insights into Black hole machines as a part of Failure Insights.

Some machines in your environment, though registered and appearing healthy might not service sessions brokered to the them, resulting in failures. Machines that have failed to service four or more consecutive session requests are termed as Black hole machines. The reasons for these failures are related to various factors that might affect the machine, such as, insufficient RDS licenses, intermittent networking issues, or instantaneous load on the machine.

The Black hole machines section of Failure Insights shows the number of black hole machines identified in your environment during the selected time period. The presence of black hole machines in the environment impacts session availability. Suggestions to reduce the number of black hole machines in your environment are provided. Clicking the number of black hole machines opens the Machines based self-service view that is filtered to show the black hole machines in your environment during the selected time period. For more information, see Black hole machines.

July 21, 2020

GPO Insights

GPO Insights displays client-side extensions (CSEs) taking the longest processing time during the selected time period. GPO Insights are available in the Session Logon Duration subfactor table. Click the Possible Reasons link in the GPOs row, Insights column.

GPO Insights are based on the analysis of user sessions having high GPO execution times. Increased GPO execution times are due to CSEs with long processing time. Optimizing CSE processing improves the overall session logon experience of the user. Average CSE execution time depends on the number and type of policies applied with it. Review and tune policies associated with CSEs taking the longest processing time as indicated in the GPO insights. Further, consider deleting the ones that are not required. For more pointers to improve the processing time of CSEs, see GPO Insights.

June 16, 2020

Improved User Experience Score algorithm

The User Experience score calculation algorithm has been improved. The method for quantifying the experience based on the factors - Session Availability, Session Logon Duration, Session Responsiveness, and Session Resiliency has been optimized. Now, more emphasis is laid on the in-session experience factors.

This update results in a more appropriate classification of users having an excellent, a fair, or a poor experience. You might notice more users being classified as having a fair or a poor experience now. The improved score algorithm enables you to correctly identify poor sessions and resolve issues to improve the user experience. Starting June 2020, the new user classification data appears on your User Experience trend. This change does not affect any classification done earlier.

For more information on the User Experience Score calculation, see the User Experience article.

April 23, 2020

Now, you can search events based on the Endpoint Country or City in the self-service view for User and Session performance data. The self-service view for Session performance data also has filters based on the Session Endpoint OS and Endpoint Version.

This information helps analyze if performance issues are localized to a specific geography, endpoint OS, or version. These filters are available for the Citrix Workspace app for Windows version 1912 and later.

For more information about the usage of these filters in self-service search, see Self-Service Search for Performance.

January 10, 2020

Citrix Analytics for Performance Generally Available

The Citrix Analytics for Performance is a new subscription based offering from the Citrix Analytics service. It allows you to track, aggregate, and visualize key performance indicators of your Citrix Virtual Apps and Desktops environment. You can use it to analyze performance issues of Citrix Virtual Apps and Desktops Sites both on-premises and on Cloud. For more information, see Performance Analytics.

What’s new