Open-Source Ecommerce · rasadov

EcommerceAPI

EcommerceAPI is a sample Go-based microservices platform for e-commerce, featuring a GraphQL gateway, gRPC inter-service communication, Kafka event streaming, and a Python recommendation engine. It demonstrates modern backend architecture patterns with Docker Compose deployment and integrations for PostgreSQL, Elasticsearch, and payment processing.

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Source: GitHub — github.com/rasadov/EcommerceAPI

689

GitHub stars

102

Forks

Primary language

Apache-2.0

License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	rasadov/EcommerceAPI
Owner	rasadov
Primary language	Go
License	Apache-2.0 — OSI-approved
Stars	689
Forks	102
Open issues	1
Latest release	Unknown
Last updated	2026-06-26
Source	https://github.com/rasadov/EcommerceAPI

What EcommerceAPI is

Built on Go microservices (Account, Product, Order, Payment) communicating via gRPC, with a GraphQL API gateway using gqlgen. Data flows through Kafka topics to a Python-based Recommender service. PostgreSQL and Elasticsearch provide persistence; full stack runs in Docker Compose with containerized Kafka and Zookeeper.

Quickstart

Get the EcommerceAPI source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/rasadov/EcommerceAPI.git2cd EcommerceAPI3# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Learning microservices architecture

Well-structured reference implementation demonstrating gRPC, event-driven design, API gateway patterns, and polyglot services (Go + Python) suitable for teams upskilling on distributed systems.

Proof-of-concept e-commerce backend

Provides working templates for account management, product catalog, order processing, and payment integration that can be forked and extended for early-stage e-commerce platforms.

Event-driven architecture showcase

Demonstrates Kafka-based event streaming between services and asynchronous processing patterns, useful for understanding order fulfillment pipelines and real-time recommendation systems.

Implementation considerations

Authenticate and authorize all gRPC calls; samples show JWT token generation but inter-service security policies are not documented.
Configure Kafka topic retention, replication, and consumer group offsets explicitly before production; defaults may cause data loss or replay issues.
Elasticsearch indexing strategy must be tuned for product cardinality and query patterns; no mention of mapping validation or analyzer configuration.
Python Recommender service depends on PostgreSQL replica freshness; replication lag will degrade recommendation quality.
API Gateway GraphQL schema stitching requires careful field resolution and error handling to avoid cascading failures from backend service timeouts.

When to avoid it — and what to weigh

Production use without hardening — No release versions, limited issue tracking (1 open issue suggests minimal active curation), and no security audit history. Requires substantial code review and security testing before production deployment.
Existing monolithic codebase requiring minimal refactoring — This architecture assumes microservices from the ground up. Migration costs and operational overhead (Kubernetes/orchestration not mentioned) may outweigh benefits for teams needing quick feature iteration.
Teams without Docker/containerization experience — Deployment relies entirely on Docker Compose; no Kubernetes manifests or alternative single-server deployment paths. Requires proficiency with container networking and multi-service orchestration.
Small teams with limited DevOps capacity — Managing PostgreSQL, Elasticsearch, Kafka, and five+ services requires monitoring, logging, and troubleshooting infrastructure. Not suitable for teams without dedicated ops or SRE support.

License & commercial use

Licensed under Apache License 2.0, a permissive OSI-approved license allowing commercial use, modification, and distribution with minimal restrictions (attribution and license copy required).

Apache-2.0 permits commercial use and proprietary modifications. However, this is a reference implementation (sample project), not a production-ready platform. Commercial adoption requires security hardening, compliance validation, and your own liability assessment. No commercial support or SLAs are offered by the author.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Adequate
License clarity	Clear
Deployment complexity	High
DEV.co fit	Good
Assessment confidence	High

Security considerations

Authentication via JWT tokens is sketched but inter-service authorization (mTLS, service account tokens) is not addressed. No input validation rules, rate limiting, or CORS policies mentioned. Elasticsearch is likely exposed without authentication. PostgreSQL and Kafka require network isolation. No secrets management (env vars, vault) guidance. Recommend threat modeling and penetration testing before handling real user/payment data.

Alternatives to consider

Medusa (Node.js)

Production-ready e-commerce backend with extensible plugin system, built-in admin API, and larger community. Steeper learning curve but lower maintenance burden.

commercetools (SaaS)

Fully managed, multi-tenant e-commerce platform-as-a-service with battle-tested payment and order workflows. Eliminates infrastructure management but locks in vendor and incurs subscription costs.

Saleor (GraphQL, Python/Django)

Open-source GraphQL-first e-commerce API with built-in headless CMS, webhooks, and plugin architecture. More opinionated than EcommerceAPI but stronger ecosystem support.

Software development agency

Build on EcommerceAPI with DEV.co software developers

EcommerceAPI is a solid reference for modern backend patterns. For production-grade e-commerce, Devco can help you architect, harden, and deploy a customized microservices platform or evaluate commercial alternatives.

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EcommerceAPI FAQ

Can I use this in production?

Not directly. It is a reference implementation suitable for learning. For production, conduct security audit, add monitoring/logging, implement auto-scaling, set up disaster recovery, and engage legal review of Apache-2.0 compliance.

What payment providers are supported?

README mentions 'DodoPayments' but no integration code is provided. You must implement the payment provider adapter yourself or integrate a third-party gateway (Stripe, PayPal, etc.).

How do I scale this beyond Docker Compose?

Migrate to Kubernetes (write Helm charts or use kustomize for manifests), set up managed PostgreSQL/Elasticsearch (AWS RDS, GCP Cloud SQL, Elastic Cloud), and use a managed Kafka service (AWS MSK, Confluent Cloud). Not documented in project.

Is the Python Recommender service required?

No. It consumes Kafka events asynchronously. You can deploy without it or replace with a different recommendation engine; the Order and Product services will continue functioning.

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