CAS/P value enhanced

Since writing my last blog on here, there has been lots of changes for the better with Citrix Analytics for performance and I wanted to highlight them. For me this further strengthens the value Analytics can bring to the table when looking after your CVAD environment and shows how fast with Citrix Cloud we can bring so many new features to customers.

So this is what happened in the last few weeks? Let me bring your attention to the most notable changes:

Straightaway when we select Citrix Analytics Service for Performance (CAS/P) we can see now at the top of the screen that there has been session count enhancements. We can now view in total the number of unique users/sessions and then the breakdown between HDX, RDP and console. This is a key metric to evaluating all sessions coming into your environment and also brings transparency into the total number of sessions launched versus the number of sessions evaluated with Performance Analytics.

Scrolling down a little on the same page we now see prescriptive failure insights, highlighting if “Black Hole” Machines are a key contributor to poor user experience. Mining this information is tough for us but through Citrix Analytics with ML modelling we make it simple and easy to view. Machines in your environment, maybe registered and seem to be healthy may not allow for session brokering, resulting in failures which mean end users cannot access them. For a machine to be present in this view is because it failed to service four or more consecutive session requests are thus then why we highlight it as a Black hole machine. We will also show recommended steps for you to troubleshoot such as insufficient RDS licenses, intermittent networking issues, or instantaneous load on the machine.

Just below then we see “Communication Error” failure insights. This is here for admins so that you can quickly figure out if communication between the endpoint – gateway or machines. This is excellent as a key contributor to failures and then poor user experience as well as RCA for determining where these failures are coming from.

Going one page down to review User Experience (UX) Factors, previously we just has Session Availability, Session Responsiveness,  Session Logon Duration and Session Resiliency. We can see now that Citrix Analytics is bringing in overloaded machines as a factor leading to UX. With this fifth element, overloaded machines is able to gain insights about machines that have experienced sustained CPU Spikes and/or High Memory Usage. This can be a major cause of poor user experience like failures, high latency, or logon duration.

Continuing on the same page here now we can see that Citrix Analytics has enhanced the ability to be able to provide logon – profile load insights and more important how it affects UX. What’s great about Citrix logon insights is that the Analytics platform does ‘Big Data’ processing and looks into every user profile, group policy object or client side extension (CSE) and provides prescriptive insights on which profiles, GPOs are contributing to poor logon or overall session / user experience. In the below example, the Analytics platform is saying look into specific policies rather than every single GPO and/or Profile which is like finding needle in a haystack.

Coming into the self service search, Infrastructure insights are available with the machines dropdown option to providing visibility on how CPU and Memory affect session failures and more importantly user experience. We also see additional details on the machine OS where we previously listed Linux or Windows we since introduced a little more details about the version.

We now have the ability to query and sort users with poor UX against Location, Latency, Endpoint OS,  App version, Machine and Gateway. Only Citrix Analytics can achieve queries where we corelates data from multiple different sources. The location based insights are particular important right now with much more remote workers, we can now correlate location and WAN latency to determine “home internet” being the issue.  Knowing where are my users coming from and providing precise city, country information needed is important for troubleshooting.

Drill down even further and you can see protocol and connection type so you can filter on all HDX traffic with the connection being internal or external. External or internal connections are sessions based on if the endpoint is directly connected (without access through a gateway) to the machines or a connection goes through a gateway.

In addition to the above, if you would like to rule out the Citrix Gateway ( Cloud or On-prem.) and endpoint location as being a key contributor to poor UX then you can run searches like this. Gateway service insights were recently added so make sure you are running Workspace app version 20.12.0 so you are consuming insights from all gateways.

With all these insights we can also leverage custom reporting capabilities to tell you the UX for users on an older version of Workspace App OR all Windows, Mac, iPhone endpoints for example. You can get as granular as you like with all the insights at hand.

For even more detail on these individual areas please have a look here in our what’s new section:

Thoughts or comments I’m interested to here so let me know what you think of these features and if there is something else you think may even further add to this great service.

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