Retail digital transformation results in complex cloud-centric infrastructure that depends on reliable, low latency retail store connectivity across hybrid and SD WAN networks. Performance issues impact retail store performance, employee productivity and digital experience using SaaS, cloud and hybrid retail apps.
This video provides a short overview of how Kadiska helped Leroy Merlin—a European market leader retailer in home renovation, decor and gardening—to optimize SD WAN performance between stores, Google Cloud Platform (GCP), their private cloud and retail apps. Key benefits realized include enhanced same-store performance, more efficient operations, improved employee retention and the reduction of performance issue resolution time (MTTR) from weeks to hours. Retail apps are now more reliable, responsive and offer staff and customers a better user experience.
Let’s look at a concrete use case, which comes from Leroy Merlin, a market leading home improvement retailer in Europe. They have over 250 retail stores in 15 countries and have over 30,000 employees.
They are going through a massive transformation at multiple levels. They’ve been rehosting a lot of what used to be in the data center to a mix of SaaS and cloud applications hosted in GCP. All the new applications are developed straight for the cloud to become more efficient.
And the structure of the connectivity between the store and those different applications has also changed from MPLS to an SD WAN, bringing more redundancy, lower latency, and of course better cost. Every store has two different underlays from different operators.
Obviously the WiFi is modern and up to date. They still have some telco hubs where traffic is distributed, which allows on one end access to the old data center, and on the other end access to GCP, which is their core cloud. They are still in the process of changing things when it comes to endpoints, when it comes to applications.
A lot of applications are moving to mobile applications. In the store they’re transforming their endpoint strategy from classical endpoints to mobile devices as well.
What was the first challenge faced? Improving their SD WAN and SaaS application performance. I’ll give you two examples of things they struggled with to illustrate the challenge.
For example, when latency increases from the store to GCP they struggle with one thing. Their SD WAN was actually doing a good job, but they did not know exactly where the latency would be created between GCP, inside GCP, the operator between GCP and the telco hub, what security process is happening , which operator they would go through as an underlay, and what impact.
So, the first thing was understanding where latency was created. They wanted to have better store connectivity, be able to optimize the SD WAN configuration. They wanted to reduce the incident impact on MTTR, and one of the first ways to do that was to know exactly, in which segment, in the scope of which operator, or vendor, or team the problem would occur, and effectively work with vendors. For example, they found that, when they had some underlay issues that would be a brown out- not a case of inavailability – operators would benefit from knowing precisely which router is adding latency which is impacting their in- store operations and their SD WAN performance.
The way they did that was by using the two hands of our solution: the User-Watcher, which is a real user monitoring extension placed on the browser that monitors the actual performance experience their users are getting when they connect to SaaS applications, or when they connect to their own applications.