E-Commerce Platform
This engagement replaced a legacy storefront that had grown far beyond what its original architecture could support. The client sells thousands of products across dozens of categories, and as the catalogue grew the platform slowed to a crawl — pages took seconds to render, search returned stale results, and the operations team had no reliable way to manage inventory. We were brought in to rebuild the platform end to end: a fast, scalable storefront, a secure checkout, and an admin system that gives the business full control of its catalogue, orders, and promotions.
Client
Ali Raza
Industry
Retail / E-Commerce
Timeline
9 weeks
Team
4 engineers + 1 designer
What we set out to build
This engagement replaced a legacy storefront that had grown far beyond what its original architecture could support. The client sells thousands of products across dozens of categories, and as the catalogue grew the platform slowed to a crawl — pages took seconds to render, search returned stale results, and the operations team had no reliable way to manage inventory. We were brought in to rebuild the platform end to end: a fast, scalable storefront, a secure checkout, and an admin system that gives the business full control of its catalogue, orders, and promotions.
Where things stood
By the time we were engaged, the system was actively costing the business sales. The original build coupled rendering, business logic, and data access tightly together, so every new feature made the next one harder to ship. Database queries ran unindexed and synchronously, meaning a single heavy category page could degrade the entire site. There was no caching, no monitoring, and no separation between the customer storefront and back-office operations.
- Category and search pages took 4–6 seconds to load under normal traffic.
- No back-office system — inventory was managed in spreadsheets and manual database edits.
- High cart abandonment driven by a slow, multi-step checkout.
- Frequent slowdowns and occasional downtime during traffic spikes.
- No analytics or monitoring to catch issues before customers reported them.
How we delivered it
- 1
Discovery & technical audit
Profiled the live site, instrumented the slowest endpoints, and mapped the real operational workflows the team used day to day — so we knew what to keep, what to rebuild, and where performance was actually being lost.
- 2
Architecture & data modelling
Designed a clean, indexed data model and a modular API layer, deciding upfront where caching and pagination would live so performance wasn't an afterthought.
- 3
Storefront & checkout
Built a responsive React storefront with fast faceted search and filtering, and reduced checkout to a single frictionless step wired to a PCI-compliant payment gateway.
- 4
Admin dashboard
Delivered a role-based panel for products, orders, stock, and promotions — retiring the spreadsheet workflow entirely.
- 5
Hardening, launch & handover
Load-tested against realistic peak traffic, added monitoring and alerting, migrated production data, deployed to AWS, and handed over with full documentation and a maintenance plan.
The architecture we shipped
The platform runs on a MERN stack with a deliberate separation of concerns. A React storefront talks to a stateless Express/Node API, which reads from MongoDB and sits behind a Redis cache for the highest-traffic queries — product detail, category listings, and search facets. Images are served from S3 via CloudFront so they load quickly worldwide and never touch the application servers. The admin dashboard is a separate authenticated surface on the same API, with role-based access. The result stays fast under load and is genuinely maintainable — new features ship without destabilising what already works.
React
Component-driven storefront with fast client-side navigation.
Node.js + Express
Lightweight, non-blocking API that shares one language with the frontend.
MongoDB
Flexible document model for a catalogue with widely varying product attributes.
Redis
In-memory cache for hot product, category, and search queries.
AWS (EC2, S3, CloudFront)
Scalable hosting, asset storage, and a global image CDN.
The trade-offs we made — and why
Custom MERN build over a hosted platform (Shopify / Magento)
Pros
- +Full control over UX, performance, and data — no platform limits or per-transaction fees.
- +One language across the whole stack, simplifying hiring and context-switching.
- +Freedom to model bespoke business logic that off-the-shelf platforms can't express.
Cons / Trade-offs
- –More upfront engineering — payments, tax, and shipping had to be integrated deliberately.
- –The client owns maintenance, security patching, and scaling instead of offloading it to a vendor.
- –Longer time-to-first-sale than dropping in a templated store.
MongoDB over a relational database (PostgreSQL)
Pros
- +The document model maps naturally to products with very different attribute sets.
- +Schema flexibility let the catalogue evolve without painful migrations.
- +Read replicas and horizontal scaling are straightforward for a read-heavy storefront.
Cons / Trade-offs
- –Weaker multi-document transaction guarantees — order and payment flows needed careful design.
- –Ad-hoc reporting and analytics are less ergonomic than SQL.
- –Easy to model data poorly without discipline; we enforced schemas at the application layer.
Redis caching layer in front of the database
Pros
- +Cut database load sharply — repeat reads are served from memory in sub-millisecond time.
- +Smoothed out the traffic spikes that previously caused downtime.
- +Cheap to run relative to the database capacity it saves.
Cons / Trade-offs
- –Cache invalidation is hard — stale prices or stock are worse than slow pages, so we invalidate on every write.
- –Adds a moving part to operate and monitor.
- –Introduces eventual-consistency windows the UI must account for.
Modular monolith over microservices
Pros
- +Far simpler to build, deploy, and reason about for a 4-person team on a 9-week timeline.
- +No network overhead or distributed-tracing complexity between internal modules.
- +Clean module boundaries make a future split into services straightforward.
Cons / Trade-offs
- –Modules scale together — you can't independently scale just search, for example.
- –A bad deploy affects the whole application rather than one service.
- –Boundaries need discipline to keep from eroding over time.
The outcome
3×
faster category & search page loads
50%
lift in checkout conversion
40%
lower hosting costs
99.9%
uptime since launch
Sheraian rebuilt our store in nine weeks and it has been rock-solid since. The admin panel alone saves my team hours every week, and we can finally ship changes without holding our breath.
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