Epic Traffic Bot is a cloud-native automation tool designed to simulate intelligent web traffic and analyze user behavior using AI. By combining Puppeteer automation with AI-driven decision-making, the platform identifies traffic patterns, adjusts simulations accordingly, and ensures organic-like behavior. Oodles built a scalable infrastructure on AWS to support real-time traffic generation, monitoring, and automated optimization.

The client engaged Oodles to create a robust backend system using AWS services and AI modules to automate and manage large-scale traffic simulations. The project required setting up EC2 for task execution, integrating SES and SQS for messaging, using RDS for data storage, and deploying the app via Elastic Beanstalk. The client also needed GitHub-based CI/CD and real-time AI analytics to adjust traffic patterns and detect anomalies.

To fulfill the project goals, Oodles implemented an AI-enhanced DevOps infrastructure:

• Automated Traffic Intelligence: We integrated AI modules to analyze browsing behavior, generate pattern-based traffic, and adapt interactions dynamically in Puppeteer simulations.
• Cloud Infrastructure: We deployed EC2 instances and AWS RDS to host and store traffic data, integrated AWS SES for communication, and managed asynchronous tasks using AWS SQS.
• CI/CD and Deployment: We configured a GitHub-based CI/CD pipeline for continuous testing, deployment, and environment management using AWS Elastic Beanstalk.
• AI-Powered Anomaly Detection: We implemented basic AI algorithms to detect traffic spikes, recognize unusual patterns, and trigger auto-scaling or security alerts accordingly.
• Monitoring & Security: We used AWS WAF for traffic filtering, CloudTrail for audit logging, and CloudWatch for real-time insights.