Every Android developer knows the frustration: Your launch times are trending up, your ANR rate is spiking, and your Play Store rating is at risk. Your observability tools tell you what broke but not why. Android's ProfilingManager API opens the door to collecting production profiling data like stack samples, traces, and heap dumps directly on user devices. But, raw Perfetto traces can be overwhelming The real challenge is turning that data into something actionable. In this talk, we'll share how Datadog built a production profiling pipeline on top of the ProfilingManager API in collaboration with Google's Android team. From collecting traces at scale, to tying profiling data to real user sessions, to surfacing the exact methods behind a slow launch or ANR spike. We'll walk through real debugging examples and share what's coming next for Android profiling. You'll leave with a clear picture of what it takes to collect raw profiling data, identify the root cause of performance issues, and how to apply Android profiling to your own debugging workflow.