Glassdoor Blocks Bots with Distil Appliance | Glassdoor Case Study

September 24, 2015

“None of the other solutions was able to block bots as well as Distil does. Distil leverages a strong network effect, which is really powerful.” 

-- Ryan Aylward, SVP, Engineering and CTO, Glassdoor

Overview

Glassdoor, headquartered in Mill Valley, California, was founded in 2007 to change the way people find jobs and companies recruit talent.

Glassdoor holds a growing database of 6 million company reviews, CEO approval ratings, salary reports, benefits reviews and more. The information and data published by Glassdoor is gathered from and shared by employees of each company. In addition, Glassdoor advertises job openings. Website visitors can research which employers are hiring, what it's like to work or interview there, and potential salaries, based on information posted by employees.

For employers, Glassdoor offers recruiting and employer branding solutions via Glassdoor for Employers. Over 2,000 companies promote their employer brand to candidates, and advertise their jobs using the Glassdoor for Employers platform. 

Challenges

  • Unwanted bots were crawling the site and muddying web metrics
  • Advertising platform traffic lacked integrity, impacting customers 
  • Home grown solution could not proactively block bad bots 
  • Malicious traffic consumed resources, drove up infrastructure costs and hurt performance
  • Engineering lacked control over the data set 

Deployment

Distil Appliance

Results

  • Bad bots are blocked from crawling, and web metrics are accurate
  • Advertising platform traffic is 99.9% real human traffic
  • Bad bots are blocked proactively, not after-the-fact
  • Infrastructure costs are not driven up artificially by bots
  • Engineering has restored confidence and control over the data set 
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