With Catchpoint, we can instantly appear as an end user in any part of the world even if we don’t have technical resources on demand and replicate the user experience. We can increase time to resolution and solve problem cases on our own in minutes.
Given the need to get an outside view of the customer experience as opposed to just the view from within their own network, the Zscaler operations team uses Catchpoint’s active testing platform to emulate what the end user is seeing, with customized alerts set up to notify them of any degradations in the performance of the applications that they’re protecting.
When comparing this functionality to other monitoring tools on the market, Zscaler found that Catchpoint provided much more depth and insight into the performance of network and infrastructure components that aﬀect the end user experience.
With Catchpoint becoming a key part of Zscaler’s operations toolbox, any time a new data center is integrated into their portfolio, they ﬁnd the closest appropriate node from Catchpoint’s expansive global infrastructure, and immediately begin running tests with alerts to which their NOC can respond.
This expansive node coverage is critical, because depending on where the data center is or where their clients are accessing it from, Zscaler must be able to observe from as close as possible to that location.
To validate that Zscaler’s services are not aﬀecting the performance of the applications that they’re protecting, they rely on Catchpoint’s graphing capabilities to show their client’s direct performance versus through Zscaler. In doing so, they can prove through third-party data that they are not having an adverse eﬀect on the end user experience, and more often, quite the contrary.
Because the Catchpoint nodes are static, Zscaler can ﬁlter out extraneous noise over which they have no control, such as congested WiFi networks and small oﬃce/home oﬃce variability. This way, the Zscaler operations team can zero in on actionable performance data and not get bogged down by trying to ﬁgure out what they can and cannot act upon. This greatly improves their time to resolution and problem isolation, particularly in locations such as China and other parts of Asia.
In addition to having accurate and reliable third-party data to prove that they are meeting their SLA requirements, Zscaler has been able to discover performance issues that their own internal observability has not uncovered because the problem didn’t lie directly with their own network or service.
The operations team has also been able to improve their mean time to resolution (MTTR) thanks to Catchpoint’s ability to emulate a customer-facing browser or application, and report in-depth metrics that the team can act on.
"With Catchpoint, we can instantly appear as an end user in any part of the world even if we don’t have technical resources on demand and replicate the user experience. It’s a huge value because it saves us time and removes the dependency on end users, and provides data that can be shared with the customer, network partners, or other parties. We can reduce time to resolution and solve problem cases on our own in minutes," concludes Misha Kuperman, VP of Cloud Operations, Zscaler.