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Novus Examples
prom213 B

Prometheus Exposition — Empty but Valid Scrape (prom)

A scrape body with metadata but no samples, which is what a freshly started process returns before it has recorded anything. Valid, and routinely mistaken for a failed scrape by code that treats an empty result as an error.

Preview — first 5 linesprom
# A valid scrape that exposes no samples at all.
# HELP shop_orders_total Orders accepted since process start.
# TYPE shop_orders_total counter
# The process has served no orders yet, so the family has no series.

Specifications

Series
0
Families
1
Comment Lines
4
Valid
true
Cause
no observations recorded yet

Testing contract

Expected to pass
Scenario
Scrape the endpoint body and record the result.
Expected result
The scrape succeeds with zero samples and up stays 1; treating an empty body as a scrape failure is the bug this fixture catches.

What is a .prom file?

A .prom file holds metrics in the Prometheus text exposition format, the same body a `/metrics` endpoint returns. Each metric family is introduced by `# HELP` and `# TYPE` comments and followed by one sample per line: a metric name, an optional brace-delimited label set, a value, and an optional millisecond timestamp. Counters, gauges, histograms (with `_bucket`, `_sum`, `_count` series and a `+Inf` bucket), and summaries with quantile labels all use this one grammar.

How to use this file

Use an example .prom file to test exposition-format parsers, scrapers, and the node_exporter textfile collector — checking label escaping, histogram bucket ordering and cumulative counts, and the handling of `NaN` and `+Inf` values.

How to use this file for testing

“Prometheus Exposition — Empty but Valid Scrape (prom)” is a deterministic Novus Examples fixture for Observability, Error handling, Config parsing. Structured and plain-text telemetry with known timestamps, levels, request identifiers, and error states for testing log ingestion, correlation, dashboards, and alert pipelines.

Documented properties for this file: PROM · 213 bytes. Compare results against paired or grouped companions on this page when present (clean↔damaged, searchable↔scanned, or format twins) so scores stay reproducible across runs.

Download the file once, keep the path stable in CI or local scripts, and treat the spec table as the contract: dimensions, seeds, field lists, and roles are intentional. Corrupt or invalid samples are labelled as such — expect parsers to fail loudly rather than silently accept them.

Telemetry fixtures use fixed trace IDs, span IDs, and timestamps so ingestion is reproducible run to run. Point your collector, parser, or query layer at the file and assert the documented span tree, metric families, or severity mix; service and host names are invented.

Generated by generation/observability.py. Free for any use, no attribution required — license.