Case Study: Glassdoor achieves accurate web metrics and 99.9% human ad traffic with Distil Networks

Glassdoor Blocks Bots with Distil Appliance

Glassdoor, the job and employer review site with millions of company reviews and salary reports, faced growing unwanted bot activity that skewed web metrics, threatened the integrity of its advertising platform, consumed infrastructure resources, and harmed site performance. Their in‑house and CDN tools were reactive and manual, leaving engineering unable to proactively identify or block malicious crawlers and protect their data.

Glassdoor deployed the Distil Appliance in a high‑availability configuration behind their CDN and F5 load balancers, leveraging Distil’s network‑wide intelligence to stop bad bots before traffic reached application servers. As a result, bots are proactively blocked, advertising traffic is 99.9% real human traffic, web metrics are accurate, infrastructure costs are controlled, and the engineering team has restored confidence and control over their data.

Glassdoor

Ryan Aylward

SVP, Engineering and CTO