Dev
Générateur de métriques Prometheus fictives
A mock Prometheus metric generator produces example metrics in the Prometheus exposition format for testing and dashboards. Prometheus scrapes plain-text metrics with a specific shape — HELP and TYPE comments followed by named samples with labels — and a realistic sample is the fastest way to test a scraper, a dashboard, or an alert rule. This tool emits counters, a histogram, and a gauge with labels and HELP text, following the real format. Click generate and copy the output into a test or a metrics endpoint. It is ideal for testing Prometheus scraping, building Grafana dashboards, and learning the metric format. The output follows the exposition format conventions, including the three core metric types, so it parses correctly and shows how counters, histograms, and gauges differ. Adapt the metric names and labels to your own service when you instrument it for real.
How to use
- Choose your options above
- Click Generate
- Copy your result
Detailed instructions
- Click Generate to produce metrics.
- Copy the output into a test or endpoint.
- Use it to test scraping or dashboards.
- Adapt the names to your own service.
Use Cases
- •Testing a Prometheus scraper
- •Building a Grafana dashboard
- •Learning the metric format
- •Seeding sample metrics
- •Demoing observability tooling
Tips
- →Counters only increase.
- →Gauges go up and down.
- →Histograms use le buckets.
- →Adapt names to your service.
FAQ
what is the Prometheus exposition format
It is the plain-text format Prometheus scrapes: optional HELP and TYPE comment lines, then metric samples as a name, optional labels in braces, and a value. This tool generates samples in that format so you can test tooling against it.
what are the metric types
The core types are counter (only goes up, like total requests), gauge (goes up and down, like memory usage), and histogram (buckets of observations, like request latency). The sample here includes all three so you can see how they differ.
are these metrics real
No. The values are random and the metric names are illustrative, so they are safe for testing and demos. They follow the real exposition format, which is what matters for exercising a scraper, dashboard, or alert rule.
What is a label in Prometheus metrics?
Labels are key-value pairs attached to a metric (like method="GET", status="200") that let you slice the same metric along dimensions and query subsets of it. They are powerful but multiply the time series, so keep cardinality sane. The generator includes realistic labels in its output, so your scraper, parser, and dashboard tests handle labelled metrics the way a real exporter emits them.
What is the difference between a counter and a gauge?
A counter only ever increases (or resets to zero on restart) — good for totals like requests served — while a gauge can go up and down, suited to values like memory usage or queue length. Choosing the wrong type breaks your queries (rate() expects a counter). The generator produces both types with correct TYPE annotations, so you can verify your tooling treats each appropriately.
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