The Login Experience Dashboard provides IT administrators with an in-depth analysis of Average connection time, Average Resume Time and Average Posture Check. IT administrators can easily identify bottlenecks for connection times, resume times with respect to users and desktop pools. Login Experience is available under User tabs.
Graphs Overview
Avg. Connection Time (sec):
Graphical comparison of average connection times for one or more users across desktop pools. Example: Identify users or pools with unusually high connection times. For example, if Pool A shows a consistent spike compared to others, it may indicate a configuration or network issue specific to that pool.
Avg. Resume Time (sec):
Trendline highlighting avg. time it takes for users to resume their desktop sessions. Example: Detect trends in slow resume times. For instance, if resume times spike every Monday morning, this could indicate cloud related performance issues.
Avg. Posture Check Time (sec):
Trendline of the avg. time taken for posture checks during user logins. Example: Admins can monitor and minimize posture check delays. If posture check times are high for users, this might indicate stricter security policies which might include application checks like antivirus and other like these which might take longer time to pass checks.
Details Table Overview
The Details Table complements the graphs as it provides granular login performance details, making it easy to drill down into session experience.
Use Cases for Troubleshooting:
Identify Slow Login Stages: If Posture Check times are consistently high, IT admins can check the policy configurations like the number of steps defined in the posture check setting, type of posture applied for the users.
Address Geographic or Network Issues: Extended Connection Times for a specific location or IP range may indicate network latency or server capacity issues.
Authentication Failures: High Gateway Auth. Times could indicate a misconfigured authentication server, issues with RAP and CAP Policies.
Track Trends Over Time: Comparing historical Total Times helps identify patterns, such as performance downgrade during peak business hours.