Every capture passes through several stages before the result is ready: files are transferred from the cameras or nodes, datasets are prepared, processing tasks run, outputs are rendered, and the result is written for review or delivery. Optimize the slowest stage instead of changing several settings at once.

Use these guides to choose a camera connection architecture and keep large capture transfers responsive:

• USB hubs vs Raspberry Pis
• Windows Defender exceptions for capture folders

Find the slow stage

Measure the same representative capture several times and identify where the delay appears:

1. Capture and transfer: cameras or nodes take too long to finish sending files.
2. Dataset preparation: files arrive, but analysis or organization is slow.
3. Processing: an enabled process task consumes most of the time.
4. Rendering and output: resizing, codec work, watermarking, or other output tasks are slow.
5. Storage or delivery: the destination drive, network, or backup path has low throughput.

Watch CPU, memory, GPU, disk activity, disk throughput, and network throughput while the job runs. High disk activity with very low throughput points to a storage bottleneck, not necessarily a CPU problem. Check Known issues for SSD write-bottleneck symptoms.

Change one variable at a time, record the result, and keep the settings that improve the full event workflow rather than only one isolated stage. Always run a complete multi-camera test before relying on a faster configuration at an event.