Analytics
Time-bucketed metrics for your serverless app endpoints, including request counts,
success/error rates, and latency percentiles across all inbound traffic.
prepare_duration reflects queue/prepare time before execution;
duration is request execution time.
This endpoint shows all inbound requests to endpoints you own — not just your own calls. This is ideal for monitoring your deployed apps, tracking SLAs, and exporting data to tools like BigQuery or Grafana. You must own all requested endpoints; returns 403 otherwise.
Metric Selection:
You must specify which metrics to include using the expand query
parameter. Only requested metrics will be populated in the response,
allowing you to optimize query performance and data transfer.
Available Metrics:
The expand parameter accepts these values, grouped by category:
Volume
request_count: Total number of requests in the time bucketsuccess_count: Successful requests (2xx responses)user_error_count: User errors (4xx responses)error_count: Server errors (5xx responses)
Error type breakdown
startup_error_count: Startup errors (startup timeout, scheduling failure)connection_error_count: Connection errors (timeout, disconnected, refused)timeout_error_count: Request timeout errorsruntime_error_count: Runtime errors (internal error, server error)
Queue / prepare latency
p50_prepare_duration,p75_prepare_duration,p90_prepare_duration,p95_prepare_duration,p99_prepare_duration: Time from request submission until execution starts
Request execution latency
p25_duration,p50_duration,p75_duration,p90_duration,p95_duration,p99_duration: Time spent processing the request
Cold boot
cold_boot_count: Requests with cold boot (startup > 1s)p50_cold_boot_duration,p75_cold_boot_duration,p90_cold_boot_duration: Cold boot duration percentiles
Billing
total_billable_duration: Aggregate billed execution time
Key Features:
- See all traffic to your apps across all callers
- Selective metric inclusion via expand parameter
- Performance metrics (latency percentiles, duration stats)
- Reliability metrics (success/error rates, request counts)
- Error type breakdown (startup, connection, timeout, runtime)
- Cold boot metrics (count, latency percentiles)
- Billing duration tracking
- Time-bucketed data for trend analysis
- Flexible date range and timeframe options
Common Use Cases:
- Monitor your serverless app performance and reliability
- Export analytics to your own observability tools
- Analyze latency trends across all callers
- Track error rates and SLA compliance
Authorizations
API key must be prefixed with "Key ", e.g. Authorization: Key YOUR_API_KEY
Query Parameters
Maximum number of items to return. Actual maximum depends on query type and expansion parameters.
x >= 150
Pagination cursor from previous response. Encodes the page number.
"Mg=="
Start date in ISO8601 format (e.g., '2025-01-01T00:00:00Z' or '2025-01-01'). Defaults to 24 hours ago.
"2025-01-01T00:00:00Z"
End date in ISO8601 format, exclusive (e.g., '2025-02-01T00:00:00Z' or '2025-02-01'). Data up to but not including this timestamp is returned. Defaults to current time.
"2025-02-01T00:00:00Z"
Timezone for date aggregation and boundaries. All timestamps in responses are in UTC, but this controls how dates are bucketed.
"UTC"
Aggregation timeframe for timeseries data (auto-detected from date range if not specified). Auto-detection uses: minute (<2h), hour (<2d), day (<64d), week (<183d), month (>=183d).
minute, hour, day, week, month "day"
Whether to adjust start/end dates to align with timeframe boundaries and use exclusive end. Defaults to true. When true, dates are aligned to the start of the timeframe period (e.g., start of day) and end is made exclusive (e.g., start of next day). When false, uses exact dates provided.
true, false "true"
Filter by specific endpoint ID(s). Accepts 1-50 endpoint IDs. Supports comma-separated values: ?endpoint_id=model1,model2 or array syntax: ?endpoint_id=model1&endpoint_id=model2
["fal-ai/flux/dev"]Data and metrics to include in the response. Use 'time_series' for time-bucketed data, metric names for specific metrics in time series, and 'summary' for aggregate statistics. At least one of 'time_series' or 'summary' and at least one metric are required.
["request_count", "success_count"]Response
Analytics data retrieved successfully
Response containing performance analytics with pagination support
Cursor for the next page of results, null if no more pages
Boolean indicating if more results are available (convenience field derived from next_cursor)
Time series analytics data grouped by time bucket (when expand includes 'time_series'). Each bucket contains all analytics records for that time period.
Aggregate statistics (when expand includes 'summary')