Technology Category
- Analytics & Modeling - Robotic Process Automation (RPA)
- Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
- Cement
- Utilities
Applicable Functions
- Sales & Marketing
Use Cases
- Traffic Monitoring
- Transportation Simulation
About The Customer
The customer in this case study is a leading job site that serves as an innovative platform for job seekers and employers. The site allows visitors to research potential employers, gain insights into company cultures, and discover open positions. Thousands of employers use this platform to advertise their vacancies. The site also operates as an advertising platform for employers, making accurate traffic metrics a key aspect of their service. The site's engineering team, led by the SVP, Engineering and CTO, is responsible for maintaining the site's performance and security, including the management of bot activity.
The Challenge
A leading job site was facing several challenges due to unwanted bot activity on their platform. The site was being crawled by malicious bots, which were distorting web metrics and compromising the integrity of the site's traffic. This was particularly problematic as the site operates as an advertising platform for employers, making accurate traffic metrics crucial. The site's existing solutions, including a homegrown solution and utilities from their CDN, were only able to reactively block bots, not proactively prevent them. This meant that the team was unable to identify and block bots before they became a problem. Additionally, the unwanted bot traffic was consuming resources, driving up infrastructure costs, and negatively impacting the site's performance. The engineering team was also concerned about potential data theft by bots, and wanted to ensure they had complete control over their data.
The Solution
In response to these challenges, the job site implemented the Imperva Bot Management Appliance in a high availability configuration. This solution was chosen for its ability to offer redundancy without increasing latency, and its compatibility with the site's existing infrastructure, including a CloudFlare CDN and F5 load balancers. The Imperva appliance works by receiving traffic from the CDN, which is then proxied through the F5 load balancer. The load balancer sends a request to the Imperva appliance, which then decides whether to allow the traffic through. If approved, the traffic is sent back to the load balancer and distributed to the application servers. This system allows the site to proactively block bad bots, preventing them from reaching the application servers and causing problems.
Operational Impact
Quantitative Benefit
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