Vipan Kumar
All case studies

Lenskart

From 300–500 to 8,000+ orders a day with the same small team

I was part of Lenskart's early 10-person tech team. The company later listed on NSE/BSE on 10 Nov 2025 (IPO about US$830M, valuation nearly US$8B), after my tenure.

Role
Senior Software Engineer, then Technology Lead (from Sept 2014)
When
Jun 2013 – Feb 2016
Where
Lenskart (Valyoo Technologies), Faridabad / Delhi NCR, India
Team
Early 10-person tech team: 5 B2C (my team), 5 B2B and supply chain; 2 engineers reported functionally

Challenge

Order volume was outgrowing a Magento monolith, and Magento re-indexing was causing downtime at scale. The team stayed small, so the platform had to keep getting more capable while staying stable and cost-efficient.

Approach

Monolith to microservices

I led the migration from the Magento monolith to Java microservices with Redis, Kafka and MongoDB flattened tables, which removed the re-indexing downtime.

One catalog, several storefronts

I designed a multi-store backend where one catalog team ran a single catalog powering Lenskart, Bagskart, Watchkart and Jewelskart, before the company focused on Lenskart.

Home Eye Check-Up

I initiated and led the tech. It grew from a 2-person team to a national network of optometrists and field staff. I built its field-ops app (lead capture, day planning, route optimization, attendance, on-ground tracking and customer feedback), first as a responsive web app and then as a PWA, replacing spreadsheet tracking.

Virtual Try-On

I built it as sole engineer using 2D JavaScript Canvas.

Customer website and admin portal

Built with the 5-person B2C team.

  1. Magento monolithRe-indexing caused downtime at scale
  2. Java microservicesServices split out of the monolith
  3. Redis, Kafka, MongoDBFlattened tables in MongoDB
  4. ResultRe-indexing downtime removed
The migration, in order.
Start (upper figure)
500 orders/day
By end of tenure
8,000+ orders/day
Orders per day, drawn to scale. The starting range was 300–500.

Results

  • Scaled the platform from 300–500 to 8,000+ orders a day with the same small team, keeping it stable and cost-efficient.
  • Removed the downtime caused by Magento re-indexing at scale.
  • Grew Home Eye Check-Up from 5 to 500 checkups a day over three years.
  • Virtual Try-On: customers typically used it about 5 times per session (data from my tenure).

Stack

  • Magento (PHP)
  • jQuery
  • Java microservices
  • Redis
  • Kafka
  • MongoDB (flattened tables)
  • JavaScript Canvas
  • PWA

Public references

  • Lenskart IPO: NSE/BSE listing, 10 Nov 2025