• Industry Healthcare
  • Use case Real-time Lightrun Logs & Snapshots to enhance MTTR (Mean Time to Resolution).
  • Results A dev tailored solution for troubleshooting directly from the developer’s IDE (IntelliJ), without the need to edit code or produce new builds just to add observability
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How InsideTracker Improved MTTR by 50% and Saved Dozens of Developer Hours a Month Using Lightrun Logs and Snapshots

Using Lightrun platform, InsideTracker developers improved MTTR by 50% and saved dozens of hours a month 

Prior to using Lightrun, InsideTracker developers were unable to troubleshoot or access the remote kubernetes environments from their local machine, causing debugging sessions to be long and inefficient. Such sessions used to involve hotfixes and redeployments that lasted hours. 

Upon the adoption of Lightrun, the engineering group reduced troubleshooting time from hours to minutes by adding logs and snapshots dynamically and on-demand directly from the IntelliJ IDE.

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

The Challenge

InsideTracker  is a personalized health analysis and data-driven wellness guide, designed to help you live healthier longer. The development team is using Java runtime technology in a cloud based environment. They have 2 kubernetes clusters, one for production and one for development and testing purposes. 

The app consists of dozens of services across multiple pods that developers do not have access to. When an incident is being reported, the developers have to go through an iterative and time consuming process to troubleshoot the problem and add more static logs and telemetry, which slows down the resolution of customer facing issues. 

Specifically, there are cases where InsideTracker developers receive a partner incident that involves API calls that returns responses that could not be parsed and therefore troubleshooted and understood by the engineers. In addition, analyzing issues that are attributed to 3rd party data providers like smart watch devices and other health tracking solutions is an additional challenge to troubleshoot and parse within the development environment. 

As a personalized health and wellness technology company, it is critical for InsiderTracker to troubleshoot and resolve production issues quickly. With that in mind, the developers needed an efficient and highly secure troubleshooting solution for their services.

Proposed Solution & Architecture

Lightrun helped the InsideTracker developers by allowing them to troubleshoot the apps whether they were running in the pre-production environment or in production during runtime, without stopping the app, directly from the development IDEs. This saved the engineering team the long and iterative cycles of debugging that used to take hours to complete. 

By using Lightrun, over a dozen InsideTracker developers were able to add logs and snapshots without hotfixing, redeploying or changing the state of the app in runtime, all through a top-notch customer privacy and security platform.

By using Lightrun, our development team was able to figure out an extremely complex incident that was hard to parse and reproduce locally and with the standard debugging solutions. The team was able to use Lightrun to quickly add logs and snapshots around the area of the incident, reproduce and fix it Yan Dyshkalps, Director of Technology Research, Architecture and Infrastructure,  InsideTracker

The Results

Using Lightrun platform, InsideTracker developers improved MTTR by 50% and saved dozens of hours a month 

Prior to using Lightrun, InsideTracker developers were unable to troubleshoot or access the remote kubernetes environments from their local machine, causing debugging sessions to be long and inefficient. Such sessions used to involve hotfixes and redeployments that lasted hours. 

Upon the adoption of Lightrun, the engineering group reduced troubleshooting time from hours to minutes by adding logs and snapshots dynamically and on-demand directly from the IntelliJ IDE.

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