Application Observability: Add support for Python runtime metrics

<!-- Please only use this template for submitting feature requests --> **Why is this needed**: Monitoring and identifying root cause issues in Python applications is difficult due to limited sophistication of tools like Pyroscope/pyspy, which currently only support CPU profiling ([ref](https://grafana.com/docs/pyroscope/latest/configure-client/profile-types/#instrumentation-with-sdks)). Problems like thread/eventloop/GIL blocking/contention seem like a long way away from the capabilities within other languages like Go. Additionally, there is no built-in support for even basic Python runtime metrics in the Application Observability (AO) platform, so users would need to build and navigate to custom dashboards to check these vitals. Currently, AO supports runtime metrics for Go, Java and .Net as per the [docs](https://grafana.com/docs/grafana-cloud/monitor-applications/application-observability/setup/metrics-labels/#runtime-metrics) (but one of our apps does show a currently empty Node.js tab in AO, so maybe thats a fourth). I hope introducing support for runtime metrics in Grafana Cloud / AO would help reassure that these issues are moving forward and make improvements to tooling across Pyroscope/OTEL more visible. Right now the situation in Python feels very bleak! **What would you like to be added**: Add a built-in dashboard tab in AO for Python runtime metrics: cpu/memory usage, garbage collection metrics, thread count, context switch metrics (voluntary/involuntary). **Who is this feature for?** This feature is for teams using Application Observability to monitor and diagnose runtime problems in their Python applications. Thank you