Monitoring and Improving Employee Experience In Virtual Desktop (DaaS/VDI) Environments (Part 2)

User Experiences

In our last blog post on monitoring employee experience, we discussed the challenges most organizations face when trying to ensure optimal end user experience in Daas/VDI environments. We also discussed how the Catchpoint platform is uniquely positioned to help our customers monitor employee experience efficiently -  

  • Monitoring from the end user perspective.
  • Monitoring from several different vantage points.  
  • End-to-end visibility into the service delivery chain.
  • Using both proactive and reactive monitoring.

In the second part of the series, we discuss a real customer use case. The customer, a global enterprise, was looking to gain visibility into virtual workspaces used by their remote workforce.

Monitoring AWS Workspace

To understand DaaS monitoring for end-to-end visibility, let’s discuss the example of a popular enterprise customer leveraging Catchpoint to monitor deployment of virtual workspaces in their organization.

This customer has a large footprint with AWS Workspaces and due to regulatory requirements, these desktops must remain in the United States, so they are deployed specifically in the US East and US West regions. These virtual workspaces act as a method of accessing a mix of critical SaaS services and on-premise applications available within the enterprise’s private network.  

However, the end users accessing these AWS Workspaces are distributed globally, with large remote workforces concentrated in India, Australia, Amsterdam, and the United States. The distributed workforce presented a challenge when it came to understanding connectivity and performance issues of these workspaces and applications.  

To make things even more complicated the customer leverages a zero-trust solution from ZScaler to manage security and access requirements from end user devices. As a result, there can be a lot of potential points of failure when diagnosing end user experience issues and lots of time wasted finger-pointing when end user IT tickets are raised.

Solving this end-to-end visibility and complexity problem required the use of deploying Catchpoint’s endpoint agent. These agents where installed on physical and virtual desktop environments and the data captured was mapped in such a way that it can be easily interpreted by the enterprise IT support organization.

With the endpoints agents deployed, we then developed purpose-built reports that detail the end-to-end experience. For instance, click here to view a dashboard detailing the same RTT that AWS provides in their Health Connection Dashboard.

From this information, we immediately know the overall availability of the service, geolocation of the users, and the performance of each individual end user accessing the US East and US West workspace regions as their traffic routes through the various global ZScaler PoPs.

The customer was particularly interested in understanding the performance difference between users in India who are routed through the Zscaler Mumbai, Chennai, and New Delhi PoPs. They wanted visibility of individual users who were within the AWS ‘degraded’ or ‘poor’ experience range.

The example dashboard (Figure 1) highlights ‘User B’ accessing the US West AWS workspace region having a much higher response time than other users within India. The user is dealing with qualitatively a poor experience compared to domestic US users routed through the San Francisco ZScaler region.

Figure 1: Dashboard for AWS Workspace performance and availability from end users.

The drill-down capabilities of the solution allow us to truly understand the differences within specific user populations. For instance, a single click into this dashboard reveals the qualitative difference in the network connectivity within India for ‘User B’ routed through the Mumbai region versus comparative users routed through the Chennai region.

Figure 2: Packet loss and latency on network layer for ‘User B’ propagating through Zscaler Mumbai region and toward US West.
Figure 3: Packet loss and latency for sample users ‘D-H’ propagating through Zscaler Mumbai region and toward US West.

The flexible analytics layer of the Catchpoint service provides proactive and on-demand visibility. It allows pinpointing the exact timestamp when the user experienced issues. For instance, highlighting that ‘User B’ experience issues reaching the AWS Workspace environment at exactly 8:21 am in the morning.  

The analytical layer also carries the same granularity over long periods. The historical data will help the customer understand the DaaS user experience and compare each Workspace region, ZScaler PoP or direct access on each end user network provider.

Figure 4: Long term trends by user location, AWS Workspace regions alongside granular timestamp of individual employees' performance.

The main outcome from this Catchpoint deployment was that it immediately simplified the troubleshooting process, prevented finger-pointing between IT teams, improved the relationship with the DaaS provider, and ultimately allowed the business to continue leveraging the flexibility, security, operation benefits of the DaaS solution without compromising the user experience.

Learn more about monitoring employee experience and improving productivity in a remote/hybrid workspace, download our ebook on employee experience monitoring.

This blog post was co-authored by Shreedhar Shirgurkar and Zachary Henderson.
Published on
Jul 14, 2021
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updated on
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Team Lead, Pre Sales Solution Engineering