Prometheus Exposition — Explicit and Skewed Timestamps (prom)
Samples with explicit millisecond timestamps alongside samples without any, including one an hour stale and one an hour in the future. Optional timestamps are the part of the exposition format most parsers get wrong, and out-of-window samples are what a scraper must reject rather than backfill.
# HELP scraped_with_timestamps Samples carrying explicit millisecond timestamps.
# TYPE scraped_with_timestamps gauge
scraped_with_timestamps{shard="s0"} 8.0167 1773738872850
scraped_with_timestamps{shard="s1"} 6.106 1773738887850
scraped_with_timestamps{shard="s2"} 6.1211 1773738902850
scraped_with_timestamps{shard="s3"} 6.1223 1773738917850
scraped_with_timestamps{shard="s4"} 5.9652 1773738932850
scraped_with_timestamps{shard="s5"} 2.3764 1773738947850
scraped_with_timestamps{shard="s6"} 6.8134 1773738962850
scraped_with_timestamps{shard="s7"} 2.5244 1773738977850
# HELP mixed_timestamps Some samples carry a timestamp and some do not.
# TYPE mixed_timestamps gauge
mixed_timestamps{case="explicit"} 1 1773738872850
mixed_timestamps{case="implicit"} 2
mixed_timestamps{case="stale_by_one_hour"} 3 1773735272850
mixed_timestamps{case="one_hour_in_the_future"} 4 1773742472850
Specifications
- Series
- 12
- Timestamp Unit
- milliseconds since epoch
- Base Timestamp Ms
- 1773738872850
- Stale Sample Offset Min
- -60
- Future Sample Offset Min
- 60
- Seed
- 7301
Testing contract
Expected to pass- Scenario
- Scrape the file and apply the ingestion window rules.
- Expected result
- Timestamp-less samples take the scrape time, the hour-stale and hour-future samples are flagged or rejected against the ingestion window, and no sample is parsed as a second value on the same line.
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 — Explicit and Skewed Timestamps (prom)” is a deterministic Novus Examples fixture for Observability, Time-series data, Time-series data. 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: seed 7301. 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.
Related files
- jsonOTLP Metrics — Counter Reset on Process Restart (json)A monotonic counter that drops from 94,880 to 1,120 when its process restarts, with startTimeUnixNano changing at exactly that point to mark the reset. Rate calculations that subtract consecutive values without checking the start timestamp produce a large negative rate here.
- csvMetric Range Export — Long (Tidy) CSV (csv)The same 90 samples as the query_range response, exported one row per observation with both epoch and ISO 8601 timestamps. The long layout every dataframe library prefers, and half of a reshaping pair.
- csvMetric Range Export — Wide (Pivoted) CSV (csv)The same 90 samples pivoted to one column per service and one row per timestamp — the layout a spreadsheet chart expects. Paired with the long-format export so a reshape can be scored in both directions.
- promOpenMetrics — Full Document with UNIT, info and stateset (prom)A complete OpenMetrics document — the _total and _created series a counter really has, UNIT metadata, an info metric carrying build metadata and a stateset with exactly one active state — terminated by the mandatory # EOF. This is what the exposition format became once it was standardised.
- promOpenMetrics — Histogram Exemplars Linking to the Trace Fixtures (prom)Histogram buckets carrying exemplars whose trace_id and span_id resolve against the OTLP trace fixtures in this category — the exact-to-example link that turns a latency spike on a graph into a specific request. Five exemplars, each with its own observed value and timestamp.
- jsonOTLP Metrics — Base-2 Exponential Histogram (json)An exponential histogram at scale 3 — eight buckets per power of two — with a negative offset, a zero bucket and its threshold. Bucket i covers (base^(offset+i), base^(offset+i+1)], and getting that indexing wrong silently shifts every percentile, which is what this fixture is for.
Generated by generation/observability.py. Free for any use, no attribution required — license.