WebInterpret: Optimizing e-commerce automation to cut incidents by 99.97%

Introduction

Webinterpret adapts customers’ e-commerce products and pages for international markets, handling translation of language and product sizing across Amazon, eBay, and Rakuten.

By 2014, their platform was struggling. The system was overwhelmed with errors. Inventory processing that should take hours was taking weeks. The infrastructure couldn’t scale, and the underlying technology was falling behind.

Pragmatic Coders joined as a technology partner, eventually becoming a core part of the R&D team over a three-year engagement.

Technologies

• Python with Flask for backend services
• MySQL and MongoDB for data storage
• RabbitMQ for message queuing
• Elasticsearch for search functionality
• Sentry for incident tracking and monitoring
• Jenkins for CI/CD pipelines
• AWS for cloud infrastructure

Challenges

No Visibility Into System Errors

The platform was generating 1.5 million incidents per day. The lack of system observability meant the team had no visibility into what was failing or why. Production issues were discovered through user complaints rather than proactive monitoring.

Inventory Processing Bottlenecks

Fetching and processing user inventory data took weeks instead of hours. Sellers couldn’t get their products listed on international markets quickly enough.

Database Performance Driving Up Costs

Excessive queries and poor index usage created bottlenecks. The architecture wasn’t designed to scale with the growing user base, so costs kept climbing.

Deprecated Technology Stack

The system was built on Python 2.6 and MySQL 5.5, technologies approaching end of support. Security patches would stop. Community support would disappear. The system faced technical death if not migrated—but migration carried risks with a system this fragile.

Solutions

Gaining Visibility with Incident Tracking

We integrated Sentry, giving the team visibility into errors across the platform. With proper tracking, we could identify patterns, prioritize fixes, and measure progress.

Daily incidents dropped from 1.5 million to around 500—a 99.97% reduction.

Redesigning Core Processes

We redesigned and rewrote core system processes with efficiency in mind, focusing on processing speed without sacrificing data consistency.

Inventory processing time dropped from weeks to hours.

Database Optimization and Infrastructure Savings

We optimized queries, fixed index usage, and restructured how the application interacted with the database layer.

Infrastructure costs decreased by 60%, while the user base increased by 800% on the leaner infrastructure.

Technology Migration

We migrated the system from Python 2.6 and MySQL 5.5 to current stable versions. The upgrade brought performance improvements, security patches, and reduced maintenance burden.

Expanding the Platform

With the core platform stabilized, we developed new capabilities:

• A buyer-seller international communication tool
• Proof-of-concept for a new marketplace e-commerce tool
• A solution connecting various e-commerce platforms to enable small sellers to enter foreign markets
• Improvements to the internal messaging tool that reduced server count by 20%

Conclusion

What started as a rescue mission became a three-year partnership. We turned a platform generating 1.5 million daily incidents into a stable, scalable system. Infrastructure costs dropped while the user base grew eightfold. We modernized the technology, creating a solid foundation for new products.