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Service Uptime Daily Sum Series + IQR Outlier Flags
x402
Service Uptime Daily Sum Series + IQR Outlier Flags is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-30).
Computes daily sum time series and IQR-based outlier flags for service uptime records (available_minutes, observed_minutes) across up to 200 rows, delivering two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Service uptime — Daily sum series + IQR outlier flags: Daily sum series + IQR outlier flags for supplied service uptime records (available_minutes, observed_minutes). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns two analytical reports: (1) a daily sum time series aggregating the selected field (available_minutes or observed_minutes) across components by date, and (2) IQR-based outlier flags identifying which rows or dates fall outside the interquartile range. All computation is performed locally on the supplied data with no external lookups.
Example use cases
SLA breach investigation for cloud services
“I have uptime logs for my cloud components over the past quarter — each row has a date, component name, available_minutes, and observed_minutes. Can you build a daily sum series and flag any days with outlier values using IQR on the available_minutes field?”
Weekly infrastructure health review
“Run a daily aggregation and IQR outlier analysis on these 150 rows of server uptime data — I want to see total observed_minutes per day and know which dates are statistical anomalies.”
Multi-component uptime anomaly detection
“I've got uptime records for three service components spanning two months, up to 200 rows. Analyze the available_minutes field — give me the daily sum series and highlight any outlier days using the IQR method.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-software-16-140?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular service uptime data (available_minutes and observed_minutes per component per day) and need both a daily aggregated time series and statistical outlier detection in a single low-cost call. It is ideal for SLA monitoring, infrastructure health checks, and anomaly detection workflows where you supply your own data and need fast, local analytical results without any live data fetching or external API dependencies. Best for datasets up to 200 rows.
Side effects
- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, component, date, available_minutes, observed_minutes) on any row — validation error
- Date field does not match YYYY-MM-DD pattern — schema validation failure
- Insufficient data variance for meaningful IQR calculation — may return trivial or empty outlier flags
- Null values in numeric fields may affect aggregation accuracy
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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