Systems | Development | Analytics | API | Testing

We’ve got a lot of customers in the healthcare space. It’s a really interesting space to be in from an analytics perspective because our customers are based across the world and have a wide variety of use cases - from financial administration all the way through to hospital performance and risk metrics.

This is part three in a series discussing the metrics pipeline powering Kong Cloud. In previous posts in this series, we’ve discussed how Kong Cloud collects, ships, and stores high volumes of metrics and time-series data. We’ve described the difference between push and pull models of collecting metrics data, and looked at the benefits and drawbacks of each from a manageability and performance perspective.