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E-Commerce – Order Fulfillment & Inventory Sync Automation

Architecture Level 1

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Automation High-Level Overview

Architecture Level 2

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Automation Detailed Workflow

Architecture Level 3

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Automation Component Interaction

E-Commerce Order Fulfillment & Inventory Sync

1. Executive Summary

The E-Commerce Order Fulfillment & Inventory Sync Automation project delivers an automated solution for seamless order processing and inventory management, integrating Shopify API, Google Sheets, and AWS Lambda for instant warehouse syncing, low-stock alerts, and customer tracking emails. It reduces fulfillment time by 60%, eliminates manual errors, handles 1,000+ orders/day, and was completed in 8 weeks from September 25 to November 19, 2025, for scalable e-commerce operations and improved customer satisfaction.

2. Architecture Overview

The architecture employs an event-driven pipeline:

Triggers: Shopify webhooks trigger AWS Lambda functions for real-time processing.

Syncing: Automated order syncing to warehouse systems and inventory reconciliation via Google Sheets.

Alerts: Low-stock threshold checks and automated customer notifications via emails/SMS.

This modular design ensures real-time data flow (<1 min latency), error handling with retries, GDPR compliance, and seamless integration across platforms.

3. Technology Stack

  • Platform APIs: Shopify API, Warehouse APIs (e.g., ShipStation)
  • Compute: AWS Lambda (Serverless Node.js/Python)
  • Storage / Reporting: Google Sheets API
  • Communication: AWS SES, SendGrid, Twilio (SMS)
  • Triggers: Shopify Webhooks
  • Monitoring: AWS CloudWatch
  • Security: HTTPS, Secure Credential Management

4. Automation Model and Features

Order Sync: Webhook-triggered Lambda pushes to warehouse for fulfillment.

Inventory Reconciliation: Periodic comparisons and updates between Shopify and Sheets.

Low-Stock Alerts: Email/SMS notifications sent automatically if inventory falls below defined thresholds.

Tracking: Automated shipment tracking emails sent to customers upon fulfillment. Achieves 99% sync accuracy.

5. Data Processing

Data processing pulls orders/inventory from Shopify API, syncs to Google Sheets for audits, and communicates with warehouse APIs for fulfillment. It applies thresholds for alerts and generates emails with tracking info. The system handles queuing for rate limits and detailed logging for audits, supporting high-volume processing with minimal latency.

6. Project Timeline (8 Weeks)

Dates: Sept 25 – Nov 19, 2025

  • Week 1 (Discovery): Assess setup, define integrations.
  • Weeks 2-3 (Design): Map data flows, design Lambda functions.
  • Weeks 4-6 (Development): Build sync, alerts, and email systems.
  • Week 7 (Testing): Simulate orders, ensure accuracy.
  • Week 8 (Deployment): Launch with monitoring, verify integrations.

7. Testing & Deployment

Testing: Unit tests for Lambda functions; Integration for end-to-end flows; UAT on 200+ test orders (99% accuracy); Tools: AWS X-Ray, Postman.

Deployment: Configured webhooks and API keys; Deployed via AWS CLI; Configured secure credentials with a monitoring-heavy first week; Supports rollback to manual sync and rate-limit queuing.

8. Monitoring & Maintenance

Monitoring: AWS CloudWatch for latency and errors; Audit logs for inconsistencies; Failure alerts.

Maintenance: Performance optimizations, redundant triggers, and quarterly security reviews. Target: >99% uptime with cost controls through serverless design and encrypted data transfers.

9. Roles & Responsibilities

Methodology: Agile Sprints with Jira tracking.

  • 🚀 Project Manager: Oversees sprints, timelines, and risks.
  • ⚙️ Developers (Cloud Specialists): Build Lambda functions and API integrations.
  • 🧪 QA Tester: Handles unit, integration, and UAT.
  • 🏗️ DevOps: Manages deployment, monitoring, and rollbacks.