Continuous Profiling is emerging as a significant addition to the traditional "three pillars of observability"—logs, metrics, and traces—by offering a more nuanced understanding of resource usage down to the code line level. Unlike traditional profiling, which can be cumbersome and resource-intensive, Continuous Profiling uses statistical profiling through time-based sampling, providing performance insights with minimal overhead. This method, pioneered by Google, allows developers to compare profiles between runs, enhancing the ability to debug and optimize applications effectively. The open-source community, including projects like Parca and Prometheus, is actively exploring how Continuous Profiling can integrate with existing telemetry data, such as metrics and tracing, to provide a more comprehensive observability framework. Efforts are underway to establish open standards for profiling data, as illustrated by the OpenTelemetry Profiling SIG's recent introduction of a profiling data model proposal.