Professional Saleor Installation and Setup: Django + GraphQL

What Problems Does Professional Saleor Installation Solve?

After deploying Saleor following the official documentation, many encounter migration errors, unstable Celery behavior, and sluggish GraphQL queries. These issues are not accidental—they stem from typical configuration mistakes. We solve them daily by tuning Saleor for production.

How to Tackle N+1 Queries in GraphQL?

Saleor's GraphQL resolvers without ORM optimization generate dozens of SQL queries for each product list request. For example, a products(first:10) query results in 11 database calls: one for products and one for each category. This is the classic N+1 problem. The solution is using select_related and prefetch_related in resolvers. For pagination, we recommend keyset pagination, which is offset-independent and significantly faster on large catalogs.

Why Does Celery Work Unreliably and How to Fix It?

The default Celery configuration is not designed for peak loads. Without setting worker concurrency and task acknowledgement, some messages are lost on restart. We configure --concurrency=4, enable CELERY_TASK_ACKS_LATE, and use Flower monitoring to prevent task loss.

How to Speed Up the Database?

PostgreSQL without indexes on frequently filtered fields (price, date, category) becomes a bottleneck. We analyze query plans via EXPLAIN ANALYZE and add composite indexes. For example, for filtering by category and price—index (category_id, price). As stated in Saleor documentation, such optimization is critical for performance.

How We Configure Saleor for Production

We use the latest stable Saleor version on Django with Python 3. Database: PostgreSQL with configured indexes. Cache: Redis. Background tasks: Celery with Redis broker. Web server: Gunicorn with gevent workers. Nginx handles static files and proxying. S3 (MinIO or AWS) for media files. Monitoring via Sentry.

Case Study: How We Accelerated a Store with 200,000 Products 10x

Standard offset pagination on the catalog caused slowdowns beyond 50 pages. We replaced it with keyset pagination using cursor based on ID. Keyset pagination is 10x faster than offset-page on catalogs over 10,000 products. Additionally, we cached categories in Redis. Response time dropped from 2 seconds to 200 ms. For Celery, we set the number of workers according to load and added retry on failed tasks. Infrastructure cost savings reached up to 40%.

Comparison of Installation Methods

Work Process

1. Audit – analyze current infrastructure and load requirements.
2. Design – choose architecture (Docker or bare-metal), DB schema, component configuration.
3. Installation – deploy Saleor, configure PostgreSQL, Redis, Celery, Nginx, SSL.
4. Integration – connect S3, set up Dashboard and Storefront, payment gateways.
5. Testing – load testing, N+1 check, optimization.
6. Handover – documentation, credentials, team training.

What's Included

• Fully configured Saleor (backend, Dashboard, Storefront).
• Server access, admin panel, Storefront.
• Operation manual.
• Performance optimization (indexes, cache, pagination).
• Support for 2 weeks after delivery.

Timelines

Common Saleor Installation Mistakes

• Forgetting to set ALLOWED_HOSTS and ALLOWED_CLIENT_HOSTS – Dashboard won't connect to API.
• Using default SECRET_KEY – security risk; must change.
• Not configuring S3 bucket policy – media files won't display.
• Not setting Celery timeouts – tasks get lost on long execution.

Why Trust Saleor Installation to Professionals?

Our team has 7 years of experience in Django and e-commerce. We have successfully installed Saleor for 20+ projects, including catalogs with millions of products. According to GitHub, Saleor is the most popular open-source e-commerce platform on Django. We guarantee stable operation under load and optimization for your specifics. Get a free consultation and technical audit of your current infrastructure. Order turnkey Saleor installation—we'll do it quickly and reliably.

Additional resources: GraphQL.