# Visualize Utilization

## Understanding the summary view

The collapsed view shows a quick overview of peak resource utilization.

![Resource utilization summary as displayed on the execution page. Click the ▼ to expand.](/files/7FsCuXYj8QBuNzBsHXBl)

### Reading the colored bars

Four colored bars represent utilization ranges for each resource:

* **Black line:** Peak utilization of the resource.
* **Green (1–70%):** Low to moderate utilization.
* **Orange (70–90%):** High utilization.
* **Red (90–100%):** Maximum utilization.

> 💡 *For GPU-intensive workloads, you want to see red—that means you're using the full capacity you're paying for.*

## Detailed charts

Click the ▼ to expand the full hardware statistics view.

![Expanded hardware statistics](/files/X8VGjtZAoZn0xE7U4aVP)

### Chart layout

* **Left chart:** Computational resources (CPU and GPU processing power).
* **Right chart:** Memory resources (system memory and GPU memory).

### Understanding the visualizations

* **Gray areas:** Min-max range of values over each 2-minute interval.
* **Colored lines:** Average values over each interval.

Hover over the lines to see exact values at specific timestamps.

Click legend items to hide the corresponding metric for clearer comparison.

### Chart actions

* **Navigate:** Use chart controls to zoom in on specific time periods.
* **Download:** Export statistics as a JSON file for further analysis.
* **API access:** Statistics are also available through the Valohai API for programmatic analysis.

## What good utilization looks like

### CPU-intensive training

Expect CPU usage in the red zone (90–100%) during data preprocessing or single-threaded training.

### GPU-intensive training

Look for GPU processor usage consistently in the red zone. GPU memory should be high but may not hit 100% depending on batch size.

### Data loading bottlenecks

If GPU utilization drops while CPU usage spikes, you may have a data loading bottleneck. Consider increasing data loader workers or using faster storage.

### Memory leaks

If memory usage steadily climbs without plateauing, you may have a memory leak in your training code.

## What's next

[**Track underutilization**](/observability/resource-monitoring/track-underutilization.md) to automatically identify executions with low resource usage and get recommendations for cheaper instances.

[**Hardware statistics overview**](/observability/resource-monitoring/hardware-statistics.md) to understand what metrics Valohai collects and how they're stored.


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