How to Design API Analytics Data Collection for High Volume APIs
Blog post from Moesif
API analytics platforms are crucial for platform companies seeking insights into API and platform usage to inform strategic decisions. High volumes of API calls present unique challenges in designing scalable analytics systems without impacting service performance or incurring excessive cloud costs. Moesif's API analytics platform addresses these challenges by implementing well-designed agents that collect metrics asynchronously, preventing service disruption. It uses local queuing for data consistency and manages storage costs through intelligent sampling and tiered data roll-ups. The platform also employs probabilistic data structures like HyperLogLog to estimate unique metrics efficiently. Ensuring reliability, Moesif utilizes DNS-based load balancing across data centers and employs a lightweight collector logic with tools like Kafka for efficient data management.
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