A client calls you to troubleshoot possible interference with your wireless network.

In the Juniper Mist AI ecosystem, Service Level Expectations (SLEs) provide a proactive way to monitor the health of a wireless network from the perspective of the end-user. When investigating potential interference—whether it is from neighboring Wi-Fi networks or non-Wi-Fi sources like microwaves or motion sensors—the Capacity SLE is the primary metric to analyze. While interference certainly impacts the overall Throughput SLE, Mist categorizes the specific environmental factors that limit airtime availability under the "Capacity" umbrella.

The Capacity SLE tracks "user minutes" during which a client experiences a drop in available RF channel capacity. It is specifically designed to identify why a client might be struggling to transmit data despite having a strong signal. Within the Capacity SLE block, Mist provides granular classifiers that pinpoint the root cause of the capacity degradation. These classifiers include:

Wi-Fi Interference: This identifies airtime contention caused by other 802.11 networks (Co-Channel Interference or Adjacent Channel Interference).

Non-Wi-Fi Interference: This identifies energy from non-802.11 sources detected by the AP's dedicated scanning radio.

Client Count: High density leading to contention.

Client Usage: A single "bandwidth hog" consuming the available airtime.

By checking the Capacity SLE in the Mist dashboard before heading to a site, an administrator can see a historical timeline of interference events. If the "Wi-Fi Interference" or "Non-Wi-Fi Interference" classifiers show a high percentage of "Bad User Minutes," the administrator can confirm that the client's complaint is indeed valid. This allows for remote troubleshooting and may even enable the admin to resolve the issue by adjusting Radio Resource Management (RRM) settings or identifying a specific rogue device, potentially saving an unnecessary truck roll.