At 11:00 AM, the system detects that site_b's active-user count is below its normal range.
The system records the alert evidence and sends an on-call notification through SNS.
The on-call engineer begins investigating, and the incident moves to Investigating.
At 1:00 PM, the business team sees the decline and asks: Why did today's user count fall so much?
The assistant compares today's 124 users with the 30-day average of 177, then explains that an alert fired at 11:00 and engineers are investigating.
When asked whether usage will recover tomorrow, the assistant says there is no validated forecast model and does not speculate.
Managers can monitor every experiment's progress, health, traffic, and configuration in one view.
If a predefined SRM or guardrail stop condition is triggered, the system automatically stops the experiment and disables its traffic allocation.
The partner pastes the complete Token API request and its 400 error response.
Using the documentation, the assistant identifies an incorrect Content-Type and a missing grant_type.
Exhibition details are outside the integration knowledge base, so the system does not invent an answer and directs the partner to a sales contact.