1
00:00:00,000 --> 00:00:09,000
At 11:00 AM, the system detects that site_b's active-user count is below its normal range.

2
00:00:09,000 --> 00:00:17,000
The system records the alert evidence and sends an on-call notification through SNS.

3
00:00:17,000 --> 00:00:25,000
The on-call engineer begins investigating, and the incident moves to Investigating.

4
00:00:25,000 --> 00:00:35,000
At 1:00 PM, the business team sees the decline and asks: Why did today's user count fall so much?

5
00:00:35,000 --> 00:00:50,000
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.

6
00:00:50,000 --> 00:01:00,000
When asked whether usage will recover tomorrow, the assistant says there is no validated forecast model and does not speculate.

7
00:01:00,000 --> 00:01:15,000
Managers can monitor every experiment's progress, health, traffic, and configuration in one view.

8
00:01:15,000 --> 00:01:30,000
If a predefined SRM or guardrail stop condition is triggered, the system automatically stops the experiment and disables its traffic allocation.

9
00:01:30,000 --> 00:01:40,000
The partner pastes the complete Token API request and its 400 error response.

10
00:01:40,000 --> 00:01:50,000
Using the documentation, the assistant identifies an incorrect Content-Type and a missing grant_type.

11
00:01:50,000 --> 00:02:00,000
Exhibition details are outside the integration knowledge base, so the system does not invent an answer and directs the partner to a sales contact.