The text discusses the development of a heatmap visualization tool for analyzing unaggregated data from multiple hosts in an infrastructure. The tool, powered by DDSketch, aggregates data during a flush interval and enables users to analyze statistical distributions across their entire infrastructure. The authors explore how they used DDSketch to build the Datadog heatmap visualization, including decisions on graphing distributions over time at an endless scale. They discuss the advantages of seeing unaggregated data, including the ability to visualize distinct modes without aggregation. The tool uses a color interpolation that aligns with the data's cumulative distribution curve and improves the overall contrast. Rendering is done by drawing rectangles on an HTML canvas, with performance improvements achieved by rendering per pixel instead of per data bin. The heatmap provides unique insights into system behavior, such as identifying changes in percentile values over time and unveiling seasonality and patterns in data that aggregations can hide. The tool's design and development process demonstrate the importance of a first-principles approach to building effective data visualizations at scale.