Perforator is a website load testing platform that simulates user actions across thousands of browsers to provide accurate performance analytics during high traffic scenarios. It identifies bottlenecks by analyzing all HTTP requests and dynamic content, enabling businesses to pinpoint issues and enhance their website's responsiveness without extensive preparation costs.
Funding
$500K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Traditional website load testing often relies on synthetic load generation, which may not accurately reflect real-world user behavior and can miss critical performance bottlenecks. Identifying the root cause of slowdowns under heavy traffic requires deep analysis of all website components, including dynamic content and third-party resources. Existing solutions can be complex to set up and require significant time and resources for test preparation and analysis.
Solution
Perforator is a website load testing platform that simulates real user actions across thousands of browsers to provide accurate performance analytics under high traffic conditions. By thoroughly examining all HTTP requests, JavaScript evaluations, CSS stylesheets, and embedded images, Perforator automatically identifies the precise causes of slowdowns or failures. The platform allows users to reuse existing QA automation Selenium logic or describe user actions using YAML, significantly reducing test preparation time. Perforator provides comprehensive data, including raw data, aggregated data, and dynamic and static request data, to pinpoint bottlenecks and improve website responsiveness.
Target Audience
Perforator targets businesses in IT consulting, e-commerce, marketing agencies, and e-learning that need to ensure website performance under anticipated traffic spikes.
Features
- Simulation of user actions in thousands of browsers in the cloud
- Comprehensive analysis of all HTTP requests, JavaScript evaluations, CSS stylesheets, and embedded images
- Automatic identification of performance bottlenecks under heavy website traffic
- Support for reusing existing QA automation Selenium logic or describing user actions using YAML
- Collection of 100% raw data, aggregated data, and dynamic and static requests data
- Core Web Vitals (LCP, FID, INP, CLS, TTFB) metrics