RidgeRun GStreamer Analytics Tool
- ridgerun

- Oct 14
- 2 min read
The power of the Pipeline Analytics Tool comes to life through Grafana dashboards. By turning raw GStreamer tracer data into interactive visualizations, engineers can quickly identify bottlenecks, confirm performance improvements, and monitor systems in development or production.
Here are some of the dashboards included out-of-the-box in the RidgeRun GStreamer Analytics framework and tracers that allows to analyze GStreamer pipelines and applications:
1. CPU and Memory Dashboard
View per-core CPU utilization alongside overall system load by using the RidgeRun GStreamer Analytics System Metrics feature.
Track memory usage in MB and %, ensuring pipelines don’t exceed device capacity.
Ideal for spotting runaway processes or confirming balanced workloads.

Figure 1. Process metrics focused on CPU, Memory and I/O
2. Pipeline Runtime and FPS Dashboard
Track running time of each pipeline instance.
Measure frames per second (FPS) at different points in the graph (e.g., source, encoder, sink).
Compare multiple pipelines side by side.
Explore many other heavy processing monitor through metrics the RidgeRun GStreamer Analytics Tool metrics

Figure 2. Analysis on pipeline: runtime, bitrate and framerate
3. Bitrate and Network Throughput Dashboard
Monitor bitrate (bits/sec) at configurable elements in the pipeline.
Overlay bitrate with network I/O throughput to ensure stability in streaming applications.

Figure 3. Dashboard with process CPU, I/O process memory and bitrate
4. Jetson Hardware Utilization Dashboard
For NVIDIA Jetson users, dedicated panels show:
GPU usage percentage over time.
VIC usage for scaling and composition workloads.
Codec engine usage for hardware-accelerated encoders/decoders.
Additional device-specific stats (e.g., thermal throttling alerts).

Figure 4. Dashboard with Jetson metrics
5. Dashboard with logs and filters
High-level per-process metrics for overall load when multiple pipelines run under a single PID.
Drill down into per-pipeline views for fine-grained optimization.

Figure 5. Text Logs for two Devices presented in the dashboard

Figure 6 Text Logs for a Device and process ID (PID) filtering presented in the dashboard
Cross-Platform Flexibility
While Jetson devices benefit from deep integration with NVIDIA’s hardware accelerators, the Pipeline Analytics Tool is equally powerful on x86 platforms and other platforms. This makes it ideal for:
Development cycles on desktop machines and ARM devices like i.MX6, i.MX8 and others.
Production deployments on embedded Jetson hardware
Benchmarking across heterogeneous environments
With a unified interface, you can develop, test, and deploy without losing visibility into how your pipelines behave under different conditions.
Real-World Applications
Here are just a few RidgeRun GStreamer Analytics Tool examples that provides useful insights for any project:
Video streaming services
Multi-camera systems
AI/ML video pipelines
Performance and debug analysis

Figure 7. Dashboard with system metrics.
Conclusion
Don’t let performance bottlenecks or blind spots slow down your development and project stability. With RidgeRun GStreamer Analytics Tool, you’ll gain the visibility and control needed to optimize, debug, and deploy with confidence.
Contact RidgeRun today to schedule a demo, explore tailored solutions for your project, or start integrating our GStreamer Analytics framework into your workflows.


