As a dominant player in the intimate apparel industry, it’s no surprise that Victoria's Secret retail systems experience significant traffic surges during major holidays like Black Friday and Christmas.
So, how does Victoria’s Secret ensure they can meet those peak-season demands as well as create personalized customer experiences at scale?
Harikumar Venkatesan, Platform Engineering Lead at Victoria’s Secret, will tell you it calls for a scalable, real-time data architecture powered by a data streaming platform.
To this end, Venkatesan’s team decided to move away from the limitations of a self-managed data streaming infrastructure and quickly pivoted to Confluent’s cloud-native data streaming platform for delivering the real-time data insights the organization needed.
Victoria’s Secret Powers Smarter, Faster Business Decisions With Real-Time Data
Today, Confluent is instrumental in helping Victoria’s Secret reliably integrate data from a wide range of operational and analytical systems, and making it available in real-time for teams to power endless use cases.
Prior to moving to Confluent, Victoria’s Secret had a complex data environment that resulted in data silos. This led to delays in retrieving and analyzing data, which impacted their ability to make timely business decisions and meet service level agreements.
“At Victoria’s Secret, data is key for empowering agile decision making,” Venkatesan said. “We receive data from various systems including logistics, stores, and digital systems.”
But instead of projecting business decisions quickly, the team encountered delays due to latency or the need to clean up incomplete information.
It was also hampering their ability to scale for peak season traffic. “Based on the business forecasting [capability we had], we didn't know if we would be able to scale up our systems.”
Today, Confluent is pivotal to helping his team build a resilient, scalable, and secure real-time data architecture—ultimately helping the business make faster, more informed decisions.
“Confluent enables us to project our business decisions pretty quickly rather than having to wait on data or deal with data inconsistencies,” he said.
Use Cases Galore With Confluent’s Resilient, Secure, and Scalable Data Streaming Platform
Venkatesan’s team drives several key business use cases, including real-time data analytics, real-time monitoring, and metrics, with Confluent.
Confluent’s multi-cloud and multi-region replication allows the platform engineers to seamlessly replicate data across multiple cloud providers and regions. This also significantly enhances disaster recovery. “When anything happens to our [data] consumers or producers, we are able to easily shift focus from one region to another region.”
Confluent also ensures data is consistent across all systems.
“We can ensure data consistency so that when a finance team, for example, is trying to get a forecast report on the data, they are able to fetch that report immediately. There is no downtime for them,” Venkatesan said.
The Result? Increase In Operational Efficiency
Confluent has also allowed for adopting a data products mindset, so teams across the organization can start viewing the data as reusable assets that are easily discoverable by data consumers and can be used to build out infinite valuable use cases.
“We can tap into real-time data and build a matrix out of it so that the other teams can then feed into that data to provide financial metrics, customer metrics, marketing preferences, and personalized recommendations to the customers,” he said.
With streamlined scalability enabled by Confluent, the platform and site reliability engineering teams can effortlessly handle fluctuating demands during peak seasons.
Prior to moving to Confluent, his team had to worry about the number of brokers they would need to scale their architecture for high traffic events. But that’s one less thing to worry about now, Venkatesan said, because of Confluent. “With Confluent, we can just click a few buttons to scale our architecture.”
Additionally, Confluent’s comprehensive security features, including role-based access control and encryption of data at rest—including SSL/TLS encryption—provides a secure way to access and manage sensitive customer data.
With Confluent, the team implemented a shift left approach to data security by encrypting ingress and egress traffic early in the process, to prevent issues and improve response times.
“We have multiple data sources chiming into our system that get data in and out. Implementing data security earlier in the process or ‘shifting left’, ensures that all incoming and outgoing data is encrypted right from the start,” Venkatesan said.
This ensures data integrity and security are already built into the flow, reducing the need for reactive fixes later.
With encryption and seamless scaling capabilities, Victoria's Secret can now manage high-volume events effortlessly while maintaining data integrity across their systems.
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