• Industry Online Retail
  • Use case Real-time Lightrun Logs & Snapshots to enhance faster issue resolution – MTTR (Mean Time to Resolution).
  • Results A dev tailored solution for troubleshooting directly from the developer’s IDE, without the need to edit code or produce new builds just to add observability
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Reducing MTTR for Critical Incidents with Lightrun at Inditex

Overall, Lightrun has become an essential debugging tool for me and my team. Its ability to capture snapshots during runtime, plus its  speed, efficiency, and user-friendly features significantly improve our development workflow and ultimately, our ability to deliver a positive customer experience

  • Industry Online Retail
  • Use case Real-time Lightrun Logs & Snapshots to enhance faster issue resolution – MTTR (Mean Time to Resolution).
  • Results A dev tailored solution for troubleshooting directly from the developer’s IDE, without the need to edit code or produce new builds just to add observability

Introduction

As a developer working for Softtek, I often find myself being tasked with solving issues that are time sensitive and business critical. Inditex is a massive retail enterprise that comprises seven brands: Zara, Pull&Bear, Massimo Dutti, Bershka, Stradivarius, Oysho and Zara Home. The brand sells in 213 markets through both online platforms and over 5.800 stores. Such a complex and ebullient business requires top notch engineering skills and the abilities to respond fast to unexpected issues. In this post, I would like to share one of my recent experiences illustrating how the Lightrun developer observability platform enabled me and my team to quickly and easily resolve critical issues directly from our development environment.

How Lightrun’s Live Debugging Improves Our Development Process

As an engineer that maintains multiple applications for Inditex warehouses around the world, I work a lot with IntelliJ IDE and Java. Our server is deployed on a Linux environment and there are 2 clients – a Tomcat server with the web application for the warehouse operations app, and a thick client in SWT for the automation systems that manages the warehouse.

In a recent incident where blocks of garments were incorrectly formed, I initially analyzed the issue using standard logs but quickly realized this approach was ineffective. I then turned to the Lightrun platform. By leveraging Lightrun’s dynamic logs and snapshots, I searched for specific labels related to the warehouse names connected to the problem area. After creating several snapshots around the affected store to assess block quantities and other variables, I identified that the block quantity was being rounded up incorrectly, resulting in one less item being recorded during clothing movement. I resolved the issue by applying Math.floor to prevent rounding in cases with many decimal places, ensuring the block size calculation matched the actual picked quantity. This helped solve the issues fast, efficiently and allowed me to move on to my next tasks without further delays.

 

Conclusion: Lightrun -Simplifying Debugging Workflows and Reducing MTTR

Overall, Lightrun has become an essential debugging tool for me and my team. Its ability to capture snapshots during runtime, plus its  speed, efficiency, and user-friendly features significantly improve our development workflow and ultimately, our ability to deliver a positive customer experience.

This post was originally published on LinkedIn by Pablo Grela Palleiro from Inditex.

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