Composable headless commerce stack: Next.js App Router with React Server Components and ISR on Vercel Edge for sub-100ms TTFB, Supabase/PostgreSQL with connection pooling and read replicas for catalog and order management, Stripe for payment processing. Monorepo structure (Turborepo) separates customer storefront and admin dashboard with shared API contracts. Load tested to 300K RPM with k6 against graduated traffic profiles.
Where enterprise projects fail
We've seen $50M revenue sites buckle under peak load, TTFB climbing past 200ms when it should stay well under. And that's not just a technical embarrassment. Every 100ms of added latency costs roughly 1% in conversions. Do the math: at $50M annual revenue, you're watching $500K walk out the door. Not hypothetically. Actually.
It's not dramatic -- it just quietly consumes 60%+ of your engineering team's week. Suddenly you're shipping features monthly while competitors in Austin or Amsterdam are pushing updates every Tuesday. The real kicker? Your team isn't slow. They're just buried in glue code nobody planned for.
It won't happen. That expansion -- whether it's new markets, enterprise accounts, or regional infrastructure -- gets pushed 12 to 18 months out. And by then, the deal's cold.
Flash sales, holiday peaks, influencer drops -- those are the moments that matter most. But without any load testing discipline, that's exactly when platforms fall over. You lose the revenue, obviously. But the brand damage from a checkout that won't load during a viral moment? That sticks around longer.
What we deliver
Why Enterprise Ecommerce Demands a Different Architecture
Most ecommerce platforms weren't built for the load profiles enterprise businesses actually face. Black Friday surges, flash sales, multi-region catalog syndication, complex pricing rules across B2B and B2C channels — these aren't edge cases. They're Tuesday.
Monolithic platforms like Magento, Salesforce Commerce Cloud, and even Shopify Plus hit architectural ceilings when you need sub-100ms TTFB at 300,000 requests per minute across global edge nodes. The frontend's coupled to the backend. The database is a single point of failure. Every feature addition slows the whole system down.
Headless commerce decouples the storefront from the commerce engine. Your Next.js frontend talks to your commerce backend through APIs. Your catalog lives in PostgreSQL. Your payments route through Stripe. Your CDN serves from the edge. Each layer scales independently.
That's not a buzzword. It's the architecture that lets brands report 20-50% page load improvements and 15% average revenue lifts in year one after migrating to headless.
How In-House Teams Get Stuck
We've audited dozens of enterprise ecommerce codebases before engagement. The patterns repeat:
Integration Sprawl
Search, reviews, loyalty, tax calculation, shipping, analytics, CMS, subscriptions, translations — each is a separate API integration requiring versioning, monitoring, error handling, and independent billing. In-house teams end up spending 60% of their time maintaining integration glue instead of building features.
Performance Regression
Without rigorous architectural discipline, client-side JavaScript balloons. Third-party scripts accumulate. Server response times creep from 80ms to 800ms over 18 months. Nobody notices until conversion rates drop and the SEO team flags Core Web Vitals failures.
Scaling Blind Spots
Most teams load test at 10x normal traffic. Enterprise flash sales hit 50-100x. Without edge caching strategies, connection pooling, and database read replica architecture, the platform buckles exactly when revenue matters most.
Deployment Fear
Tightly coupled codebases mean every deployment risks the entire storefront. Teams slow their release cadence to biweekly or monthly. Feature velocity dies. Competitors ship faster.
Our Architecture: Next.js + Supabase + Edge
We build enterprise ecommerce platforms as composable systems where every layer is independently deployable, testable, and scalable.
Storefront Layer: Next.js on Vercel Edge
The customer-facing storefront runs on Next.js App Router with React Server Components. Product detail pages, category listings, and landing pages render server-side at the edge — no client-side data fetching waterfall, no layout shift, no blank screens.
We use Incremental Static Regeneration (ISR) for catalog pages. A 50,000-SKU catalog doesn't need 50,000 build-time renders. Pages regenerate on demand with stale-while-revalidate semantics. First visit triggers a server render cached at the edge. Subsequent visits serve from CDN in under 50ms.
For dynamic pages — cart, checkout, account — we use streaming SSR with Suspense boundaries. The shell renders instantly while personalized data streams in. TTFB stays under 100ms regardless of data complexity.
Data Layer: Supabase + PostgreSQL
Product catalog, inventory, orders, customers, and pricing rules live in PostgreSQL managed through Supabase. We get auto-generated REST and GraphQL APIs, real-time subscriptions for inventory updates, Row Level Security for multi-tenant B2B scenarios, and Edge Functions for server-side business logic.
For high-volume read patterns, we implement materialized views for complex product queries, connection pooling through Supabase's built-in PgBouncer, and read replicas for geographic distribution. Write operations route to primary. Read operations route to the nearest replica.
Database migrations run through Supabase CLI with version-controlled migration files. No manual SQL in production. Ever.
Payment Processing: Stripe
Stripe handles all payment logic — checkout sessions, subscription billing, multi-currency processing, tax calculation, fraud detection. We never store payment credentials. Stripe's server-side SDK runs in Edge Functions or Vercel Serverless Functions, keeping PCI compliance scope minimal.
For high-volume scenarios, we implement webhook idempotency, retry logic with exponential backoff, and event deduplication. A failed webhook doesn't mean a lost order.
Admin Layer: Internal Dashboard
A separate Next.js application for internal teams handles product CRUD, order management, inventory tracking, customer service queues, and analytics dashboards. It shares the same Supabase backend but deploys independently. Marketing can update product descriptions without touching the storefront deployment pipeline.
Edge CDN and Global Distribution
Vercel's Edge Network serves the storefront from 30+ global points of presence. Static assets, ISR pages, and API responses cache at the edge. We configure cache headers per route — immutable for hashed assets, short TTL for inventory-sensitive pages, no-cache for checkout flows.
For API routes that can't be cached, Edge Functions execute within 50ms of the user. A customer in Singapore hits a Singapore edge node, not a US-East server.
Load Testing: 300K RPM Validated
We don't ship without load testing. Every enterprise ecommerce platform we build goes through graduated load testing:
- Baseline: 10K RPM sustained for 30 minutes. Validate response times, error rates, database connection utilization.
- Peak: 100K RPM sustained for 15 minutes. Identify bottlenecks in connection pooling, edge cache hit rates, and serverless function cold starts.
- Surge: 300K RPM burst for 5 minutes. Simulate flash sale conditions. Verify auto-scaling behavior, queue backpressure, and graceful degradation.
We use k6 for scripted load tests, Vercel Analytics for edge performance monitoring, and Supabase observability for database-level metrics. Every test generates a report with p50, p95, and p99 latency distributions.
Production-Proven at Scale
This isn't theoretical architecture. We've built systems handling 137,000+ managed listings with complex search and filtering, 91,000+ dynamically generated pages indexed by Google, real-time bidding platforms with sub-200ms latency requirements, and multi-language platforms deployed across 30 locales.
The same architectural principles — edge-first rendering, decoupled data layers, ISR for catalog scale, connection pooling for database throughput — apply whether you're selling industrial equipment B2B or running a DTC fashion brand.
Delivery Model and SLAs
Enterprise ecommerce engagements follow a structured delivery cadence:
Discovery (2-3 weeks)
Architecture review, integration audit, performance benchmarking of existing platform, data migration planning.
Foundation Sprint (4-6 weeks)
Core storefront, product catalog, cart/checkout flow, Stripe integration, admin dashboard MVP. Deployed to staging with CI/CD pipeline.
Feature Sprints (8-12 weeks)
Search and filtering, personalization, loyalty integrations, analytics instrumentation, SEO optimization, accessibility compliance. Biweekly demos with stakeholder sign-off.
Launch and Hardening (2-3 weeks)
Load testing, security audit, performance optimization, DNS cutover, monitoring setup, runbook documentation.
Post-Launch Support
99.9% uptime SLA. 4-hour response time for P1 incidents. Monthly performance reviews with Lighthouse scoring and Core Web Vitals tracking.
Total timeline: 16-24 weeks from kickoff to production. We staff engagements with a dedicated senior architect, two frontend engineers, one backend engineer, and a QA engineer.
When This Is the Right Fit
You need this architecture if you're processing more than $10M annually through your storefront, your current platform can't maintain sub-200ms TTFB under load, you're expanding to multiple regions or languages, your development team spends more time on platform maintenance than feature development, or your monolithic platform is blocking business agility.
If you're running a 500-SKU Shopify store doing $2M a year, this is overkill. We'll tell you that upfront.
See this capability in action
Frequently asked
How do you achieve sub-100ms TTFB on ecommerce pages with dynamic pricing and inventory?
We use React Server Components with ISR on Vercel's Edge Network. Product pages render server-side at the nearest edge node with stale-while-revalidate caching. Dynamic data -- inventory counts, pricing -- streams in via Suspense boundaries after the initial shell renders. So you're not blocking the whole page on a database query. In practice, TTFB stays under 100ms while real-time data surfaces within 200ms of page load. That combination is hard to beat.
Can this architecture handle Black Friday or flash sale traffic spikes?
Yes. We load test every platform to 300K RPM burst conditions using k6 -- that's not a number we picked arbitrarily, it reflects realistic surge scenarios we've seen on high-volume launches. Vercel's serverless infrastructure scales horizontally without manual intervention. Supabase connection pooling via PgBouncer keeps the database from saturating under concurrent load. Edge caching absorbs the bulk of read traffic before it even hits origin. And we've validated graceful degradation patterns specifically so checkout stays functional even when ancillary services slow down.
Why Supabase instead of a dedicated commerce backend like Medusa or Saleor?
Supabase gives us full PostgreSQL control without the abstraction tax you get from commerce-specific ORMs. Catalog, inventory, orders, pricing -- all modeled directly in relational tables. Row Level Security handles multi-tenant B2B without application-layer hacks. Real-time subscriptions manage inventory sync. Edge Functions handle business logic. But honestly, the biggest advantage is this: you own your data layer completely. There's no commerce platform's proprietary schema sitting between you and your own database.
How do you handle PCI compliance with Stripe integration?
We never touch or store payment credentials -- full stop. Stripe Checkout Sessions and Payment Intents handle all sensitive card data on Stripe's infrastructure. Server-side Stripe SDK calls run in Vercel Serverless Functions with encrypted environment variables. The result is PCI scope at SAQ-A level, which is the lightest compliance burden available and genuinely what you want. Webhook handlers use idempotency keys and signature verification to block replay attacks before they become a problem.
What does migration from a monolithic platform like Magento or Salesforce Commerce Cloud look like?
We run a parallel deployment during discovery -- the new headless storefront launches alongside the existing platform with traffic splitting by route. Product data migrates to PostgreSQL via ETL scripts validated against source systems. Then we cut over route-by-route: category pages first, then PDPs, then checkout. Each step is independently reversible, which limits the blast radius if anything unexpected surfaces. Full migration typically lands somewhere between 16 and 24 weeks depending on catalog complexity and existing technical debt.
How do you handle multi-region and multi-currency requirements?
Vercel's Edge Network serves from 30+ global PoPs automatically -- you don't configure that manually. We implement locale-aware routing through Next.js middleware that detects region and serves localized content without redirects. Stripe handles multi-currency pricing natively, so you're not building currency conversion logic yourself. Supabase read replicas can deploy regionally for data locality where latency really matters. Product catalogs support per-region pricing, availability, and content through PostgreSQL views -- no content duplication required.
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