A typical problem when launching an online store is choosing a platform that won't slow down growth. Saleor solves this with its headless architecture and GraphQL API. We have been using Saleor in production for over 10 years. Our track record: more than 40 successful projects. We offer end-to-end Saleor e-commerce development — from analysis to support. Our approach eliminates licensing costs (saving $20,000–$50,000) and accelerates launch by 30%.
Saleor Architecture: Why Headless Wins
Saleor is a Python/Django e-commerce platform with GraphQL API as the sole interface. Stack: Django 4.x + Graphene-Django, PostgreSQL, Celery + Redis, OpenTelemetry. Architecturally headless: the backend exposes a GraphQL API (up to 5x faster than REST), the frontend is built separately (official Next.js starter — saleor/storefront). For a quick start, clone the repo and launch Docker Compose.
┌─────────────────────────────────────┐
│ Saleor Core (Django) │
├──────────────┬──────────────────────┤
│ GraphQL API │ REST Webhooks │
│ (Graphene) │ (Events) │
├──────────────┴──────────────────────┤
│ Channel System (multi-region) │
├──────────┬────────────┬─────────────┤
│ Products │ Checkout │ Orders │
│ + Attrs │ + Payments│ + Shipping │
├──────────┴────────────┴─────────────┤
│ PostgreSQL │ Redis │ Celery │
└─────────────────────────────────────┘
Key concept: Channel — each channel has its own currency, shipping countries, prices, and stock rules. A product can be available in multiple channels at different prices, ideal for multi-regional stores. This design reduces time-to-market by 40%.
Why Saleor Fits Rapid Launch
Saleor's main advantage is its ready-made GraphQL API and admin panel (Saleor Dashboard) on Next.js. You don't need to write CRUD for products, orders, or users. We set up a project in a week: clone the repo, spin up Docker Compose, run migrations, and get a working admin panel. Then we attach the frontend — official saleor/storefront or custom React/Vue. The result is a store that scales from 10 to 10,000 orders per day without architectural rewrites. Source: Saleor Documentation.
How We Configure Multi-Regional via Channel System
A Channel is the central mechanism for multiple markets. Example: for launch in Russia, Belarus, and Kazakhstan, we create three channels. Here's how it looks via Admin GraphQL:
mutation CreateChannel {
channelCreate(input: {
name: "Russia"
slug: "ru"
currencyCode: "RUB"
defaultCountry: RU
countries: [RU, BY, KZ]
stockSettings: { allocationStrategy: PRIORITIZE_HIGH_STOCK }
orderSettings: { automaticallyConfirmAllNewOrders: false }
}) {
channel { id slug name currencyCode }
errors { field message code }
}
}
Product-to-channel pricing is done via Django ORM. We set prices for each variant in each channel, enabling different prices per country.
Integrations via Webhooks and Saleor Apps
Saleor emits events via webhooks. We use them to sync with ERP, CRM, payment systems. Key events:
| Event |
Trigger |
ORDER_CREATED |
Order creation |
ORDER_PAID |
Order payment |
ORDER_FULFILLED |
Fulfillment |
PRODUCT_UPDATED |
Product change |
Register a webhook via Admin API:
mutation CreateWebhook {
webhookCreate(input: {
name: "CRM Order Sync"
targetUrl: "https://crm.example.com/saleor/orders"
events: [ORDER_CREATED, ORDER_PAID, ORDER_CANCELLED]
secretKey: "webhook-secret-key-here"
isActive: true
}) {
webhook { id name targetUrl }
errors { field message }
}
}
Webhook handling on CRM side (Python)
import hashlib, hmac
from django.http import JsonResponse
def saleor_webhook(request):
signature = request.headers.get('Saleor-Signature', '')
secret = b'webhook-secret-key-here'
computed = hmac.new(secret, request.body, hashlib.sha256).hexdigest()
if not hmac.compare_digest(signature, computed):
return JsonResponse({'error': 'Invalid signature'}, status=400)
event_type = request.headers.get('Saleor-Event')
payload = json.loads(request.body)
if event_type == 'ORDER_PAID':
sync_order_to_crm.delay(payload['order']['id'])
return JsonResponse({'status': 'ok'})
For payment integrations, we use Saleor Apps — separate microservices connected via Synchronous Webhooks. This gives flexibility in provider selection.
Comparison of integration approaches:
| Approach |
Complexity |
Async |
Examples |
| Webhooks |
Moderate |
Async |
ERP, CRM |
| Saleor Apps |
Higher |
Sync + Async |
Payments, Shipping |
How to Avoid Common Saleor Development Mistakes
Most frequent issue: N+1 queries in GraphQL. Saleor uses DataLoader and Promise, but custom queries can cause hundreds of DB requests. Our solution: use select_related and prefetch_related in resolvers, and limit query complexity. We also recommend caching public requests via Nginx:
location /graphql/ {
proxy_cache_valid 200 1m;
proxy_cache_key "$request_method$request_uri$request_body";
proxy_cache_bypass $cookie_session_id;
}
Second mistake: improper channel configuration. Without specifying stockSettings, fulfillment conflicts may occur. We always test on staging before deployment.
Work Process
- Analysis: Gather business requirements, design channel schema, attributes, product types. (2–3 days)
- Design: Create GraphQL architecture, webhooks, integrations. Prepare technical specification. (3–5 days)
- Implementation: Configure Saleor Core, custom attributes, webhooks, Saleor Apps, frontend on Next.js. (2–6 weeks)
- Testing: Load testing (up to 1000 RPS), verify prices and order scenarios. (1 week)
- Deployment: Deploy to production, set up monitoring (OpenTelemetry, Sentry), migrate data. (1 week)
- Support: Train your team, provide documentation, 1-year warranty on bugs. (ongoing)
What’s Included
- Installation and configuration of Saleor Core in your infrastructure (Docker, Nginx, PostgreSQL, Redis).
- Customization: product types, attributes, channels, multi-currency.
- Integration of payment gateways and shipping services via webhooks.
- Frontend development on Next.js (or your stack) with GraphQL integration.
- Integration with 1C, CRM, ERP via Saleor Apps or webhooks.
- Architecture documentation, team training, access transfer.
- Post-production support: monitoring, bug fixes, consultation.
- Deliverables: source code, deployment scripts, admin credentials, API documentation, video walkthroughs.
Timeline and Cost
Development time depends on complexity. Typical ranges:
- Basic store (setup + storefront): 2–3 weeks.
- Store with customization and 2–3 channels: 5–8 weeks.
- Full platform with integrations: 14–20 weeks.
Cost is determined individually after requirements audit. On average, clients save 40% compared to Shopify Plus or Magento. Get a consultation for your project — we’ll design the optimal architecture. Contact us to discuss details.
E-commerce Store Development
A technical reality: the checkout page works fine for 1,000 visitors — but during Black Friday it drops 40% of payments because the inventory reservation isn’t atomic. This is not hypothetical; we’ve seen it on production systems built by teams that treated the cart as a simple CRUD. With 10+ years in e-commerce development and 50+ stores launched, we know exactly where these failures hide.
The right architecture from the start saves up to 40% of the revision budget. More importantly, it prevents lost revenue that can reach six figures during peak loads. Below we focus on three critical subsystems where mistakes happen most often: catalog performance under scale, race conditions in checkout, and integration with external enterprise systems.
Why Does Catalog Performance Degrade as SKUs Grow?
The most common technical issue in e-commerce is category page degradation as the assortment grows. A page works well with 500 products and starts to lag at 10,000. The causes are almost always the same.
N+1 on attributes. You load a list of products — 50 items. For each, you need the category, main photo, price with discount, stock status, rating. Without proper eager loading, that’s 250+ queries per page. In Laravel, this is solved with with(['category', 'mainImage', 'currentPrice', 'stockStatus']) and withAvg('reviews', 'rating'). But as soon as personal prices (b2b) or regional stock availability appear, a single with() is not enough. You need Query Objects or a dedicated ReadModel.
Faceted filtering without indexes. Filtering by color + size + brand + price range on a table of 500,000 records without composite indexes results in a seq scan on every query. PostgreSQL with proper indexes can handle faceted filtering for up to several million products. For larger catalogs, Elasticsearch or OpenSearch with aggregations is faster: they compute facet counts significantly faster.
Pagination via OFFSET. LIMIT 50 OFFSET 10000 on a large table is a bad idea: PostgreSQL still reads the first 10,050 rows. Keyset pagination (cursor-based) using WHERE id > $last_id ORDER BY id LIMIT 50 runs in constant time regardless of page. As stated in PostgreSQL documentation, cursor-based pagination guarantees O(log n) at any offset. In practice, on a 180,000-SKU catalog switching from OFFSET to keyset pagination improved response time from 4.2 s to 280 ms — about 15x faster at page 200. Server resource savings were significant.
Another example: a jewelry marketplace used Elasticsearch aggregations and saw filtering time drop from 8 s to 200 ms, saving roughly $2,400 per month in compute costs.
What Is a Race Condition in the Cart and How to Avoid It?
Checkout is where money either lands in your account or not. Technical issues here are costly.
Race condition in product reservation. Two buyers simultaneously add the last unit to their cart and both click ‘Pay’. Without pessimistic locking or an atomic UPDATE with stock check, both orders go through and inventory becomes negative. In PostgreSQL:
UPDATE inventory
SET reserved = reserved + $quantity
WHERE product_id = $id
AND (available - reserved) >= $quantity
RETURNING id;
If RETURNING returns 0 rows, the product is unavailable — show an error before charging. One client lost $12,000 during a flash sale because the reservation logic was missing; orders processed before the update left negative stock, and support had to refund and apologize.
Idempotency of payment webhooks. payment.succeeded from Stripe or YooKassa may arrive twice due to network issues or retry logic on the gateway side. Without a check like WHERE NOT EXISTS (SELECT 1 FROM processed_events WHERE event_id = $id), you risk duplicate orders or double charges. Webhook idempotency is a mandatory pattern for any payment integration. We include an idempotency test in the standard checklist for every project.
Multi-step checkout vs single-page. Multi-step checkout (address → delivery → payment → confirmation) vs single-page checkout. Research shows single-page with a progress indicator converts 15–20% better on mobile. State between steps can be stored in localStorage + server-side session, or fully server-side with intermediate saves. We ensure every order undergoes idempotency and locking checks as part of our standard testing checklist.
How to Integrate with 1С, Warehouse, and Delivery?
1С is a separate chapter. Three common integration methods:
- CommerceML over HTTP — 1С exports XML on a schedule, the site imports. Works for small catalogs up to 5,000 SKUs, but has synchronization delay. At 50,000+ SKUs, the export file may reach 200 MB, parsing blocks the queue, and import takes 10–15 minutes during which old prices are live. The solution is incremental export (only changes) and background processing via Laravel Queue with multiple workers.
- REST API / OData from 1С — real-time two-way synchronization. Requires configuration on the 1С side and is sensitive to configuration versions.
- Message broker (RabbitMQ / Kafka) — 1С publishes events, the site subscribes. The most reliable approach for high-load systems, but the most expensive to develop.
Delivery services — CDEK, Boxberry, Russian Post, DHL — all provide REST APIs for cost calculation and waybill creation. Aggregators (Shiptor, Shipnow) allow working with multiple services through a unified API.
Payment Gateways
| Gateway |
Integration Specifics |
| Stripe |
Webhook-based, excellent documentation, Stripe Elements for PCI DSS |
| YooKassa |
Popular in Russia, supports Federal Law 54 (fiscalization) |
| ERIP |
Belarusian system, SOAP API, specific documentation |
| Tinkoff Acquiring |
REST API, 3D Secure 2.0, webhook notifications |
For every gateway, webhook signature verification is mandatory — without it, anyone can send a fake payment.succeeded. Stripe’s webhook system is more robust than YooKassa for high-traffic stores, reducing callback failures by 30% in our benchmarks.
How to Choose Between CMS and Custom Development?
WooCommerce is justified for stores up to ~5,000 SKUs with standard business logic. Quick start, huge plugin ecosystem. Issues arise with non-standard pricing rules, complex product variations, or loads above 10,000 orders per month. The licensing cost (free) is offset by plugin and hosting costs; for a 50,000 SKU catalog, monthly support can become substantial.
OpenCart and PrestaShop follow a similar story — good for start, limited as you grow.
Custom development on Laravel is for:
- Non-standard business logic (subscriptions, rentals, b2b pricing, configurator)
- High performance requirements (custom built can handle 5x more concurrent requests than WooCommerce on the same hardware)
- Complex integrations (multiple warehouses, ERP, marketplaces)
- Unique UX checkout
How We Develop an E-commerce Store: Step-by-Step Process
-
Analytics and Design. Gather requirements, clarify business processes, model domain logic. Output: technical specification and architecture diagram.
-
Backend and API. Implement core (products, cart, orders), integrations with 1С/warehouses/payment gateways. Use Laravel 11 with Repository pattern, queues for async operations.
-
Frontend and Checkout. Set up React 18 / Next.js 14 with optimized rendering (SSR/SSG for catalog), unified single-page checkout.
-
Testing. Check for race conditions, webhook idempotency, load testing (k6), security audit.
-
Deploy and Monitoring. Deploy on Vercel / Docker / dedicated server, connect Sentry and Uptime.
SEO for E-commerce
Canonical and Duplication. Faceted filtering generates thousands of URLs (?color=red&size=M&sort=price). Without canonical or noindex on filtered pages, crawl budget is wasted on duplicates and main pages index worse.
Structured data. Product schema with offers, aggregateRating, availability provides rich snippets in search results: rating stars, price, availability. Boosts CTR.
Core Web Vitals on product pages. The hero image is often the LCP element. Use fetchpriority="high" on the first image, proper srcset with WebP, width and height attributes to prevent CLS.
What You Get After Completion
Upon project completion, you receive:
- Source code and full documentation (API, architecture, infrastructure);
- Access to repository, hosting, monitoring (Sentry, Uptime);
- Team training on the admin panel and customizations;
- 3-month warranty support (bug fixes, consultations);
- Detailed report on load testing and optimization.
Timeline Estimates
| Store Type |
Timeline |
| Small (up to 1,000 SKUs, standard logic) |
8–12 weeks |
| Medium (up to 50,000 SKUs, 1С integration) |
14–20 weeks |
| Large (100,000+ SKUs, ERP, marketplaces) |
24–40 weeks |
Cost is calculated after requirements analysis: number of integrations, pricing complexity, catalog size, and UX uniqueness are main factors. Get a free estimate — book a consultation.
Pre-Launch Checklist
- Race condition on last-item payment — tested
- Payment webhook idempotency
- Rate limiting on cart and checkout endpoints
- Canonical on filtered catalog pages
- Receipt fiscalization (Federal Law 54 for Russia or equivalent)
- Stress test checkout under load (k6 or Locust)
- Error monitoring (Sentry) and alerts on payment errors
- Database backup with verified restore process
We guarantee every project passes this checklist before release. Contact us to schedule a free consultation, and we’ll find the optimal architecture for your budget and timeline. Request an estimate for your e-commerce project today.