Pythian Hadoop services optimize mission-critical user data for a global web application provider

Customer Success

Pythian Hadoop services optimize mission-critical user data for a global web application provider 

A global web application provider turned to Pythian to help them make use of their Hadoop environment to effectively track user metrics and improve customer experience.  

Overview

Tracking user metrics is critical for this company to understand the uptake, prioritize fixes and new features of their main application—and ultimately improve the customer experience. However, their system for processing mission-critical user data and their key application web logs suffered from slow batch processing, and it took too long to see aggregate results. There was also no backup process, which meant they were at risk to lose vital user data.  

The answer was to move the process for tracking metrics and storing data in their Hadoop system—but the client lacked in-house Hadoop expertise. Pythian was there to help. 

What we did

  • Optimized, upgraded, and maintained the Hadoop clusters housing mission-critical user data 
  • Reduced the number of Hadoop nodes from 30 to 20 to enable fast data recovery 
  • Sped up the web log processing of user data in the application’s health report, enabling easier access to critical customer usage information, including crash reports and user locations 
  • Enabled the client’s internal team to continue managing the new environment through an extensive knowledge transfer 

Technologies used

  • Apache
  • Hadoop 
  • Oracle
  • MySQL

Key Outcomes

Pythian offered a wealth of Hadoop expertise to efficiently optimize, upgrade and maintain the Hadoop clusters that housed our mission-critical user data. If we had any questions, we could just ask them! Their breadth of expertise and flexibility also meant they could also help us with our MySQL needs. 

– Manager, Data Team, Global Web Application Provider 


Secured and optimized critical user data 


Saved $100,000 in reduced hardware costs

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