Development of a Real-Time Bidding Platform with Microservices Architecture forEnhanced Advertising Performance

The client faces challenges supporting existing platform functionality due to limited documentation and knowledge transfer from original developers. They require a highly available, low-latency system capable of processing a large volume of requests from SSPs and advertisers within 100 milliseconds, while also enabling scalability and real-time monitoring for performance and error tracking.

A mid to large-sized digital advertising firm specializing in programmatic ad campaigns, seeking to optimize its demand-side platform and real-time bidding capabilities to improve user engagement analytics and system latency.

• Redesign the existing platform into a microservices architecture to ensure scalability and maintainability.
• Achieve request processing latency of less than 100 ms for real-time bidding operations.
• Integrate external SSPs and data management systems to collect and analyze user engagement data.
• Implement comprehensive monitoring and error tracking mechanisms to ensure system stability and performance.
• Enable flexible bidding and audience targeting optimization for advertisers.
• Utilize cloud technologies for infrastructure hosting, data storage, and scalable data processing.
• Facilitate continuous integration and deployment to support ongoing platform enhancement.

• Design and implement a microservices-based architecture to enhance scalability and fault tolerance.
• Support high-volume bid requests with latency below 100 milliseconds.
• Integrate with multiple SSP platforms via standard protocols (e.g., HTTP APIs, cookies).
• Gather and process user engagement data from external sources for targeted retargeting.
• Implement an internal analytics dashboard or report generation system for external and internal data insights.
• Establish real-time monitoring and error tracking systems utilizing cloud-native solutions.
• Automate deployment, build, and continuous integration processes using DevOps best practices.

• External SSP platforms to access impression and bid request data
• Data management systems for user-specific behavioral data
• Analytics and reporting tools for tracking performance metrics
• Error tracking and logging services to ensure stability

• System must process large volumes of bid requests with latency under 100 ms.
• Architecture should support horizontal scaling to handle variable loads.
• System should maintain high availability with minimal downtime.
• Data must be securely transmitted and stored, ensuring user privacy compliance.
• Monitoring systems must provide real-time insight into performance and errors to facilitate rapid issue resolution.

The new platform aims to significantly improve bidding latency, target optimization, and data analytics capabilities. It is expected to enable the client to process up to a large volume of bid requests efficiently, gather valuable insights into external user engagement, reduce system latency below 100 ms, and support scalable growth. This will enhance ad campaign performance, reduce operational costs through optimized infrastructure, and facilitate data-driven decision-making for improved ROI.