json5.3 KB

OTLP 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.

Observability Time-series data Time-series data

Preview — first 50 linesjson

{
  "resourceMetrics": [
    {
      "resource": {
        "attributes": [
          {
            "key": "service.name",
            "value": {
              "stringValue": "cart-api"
            }
          },
          {
            "key": "service.namespace",
            "value": {
              "stringValue": "shop"
            }
          },
          {
            "key": "service.version",
            "value": {
              "stringValue": "0.9.7"
            }
          },
          {
            "key": "service.instance.id",
            "value": {
              "stringValue": "cart-api-58bd21-9qh"
            }
          },
          {
            "key": "deployment.environment.name",
            "value": {
              "stringValue": "staging"
            }
          },
          {
            "key": "host.name",
            "value": {
              "stringValue": "node-a2"
            }
          },
          {
            "key": "host.ip",
            "value": {
              "stringValue": "192.0.2.12"
            }
          },
          {
            "key": "cloud.region",
            "value": {

… 194 lines total — download for the full file.

Specifications

Data Points: 6
Reset After Point: 3
Value Before Reset: 94880
Value After Reset: 1120
Start Time Changes At Reset: true
Naive Delta Would Be: -93760

Testing contract

Expected to pass

Scenario: Compute a per-second rate across all six points.
Expected result: The reset between points 3 and 4 is detected from the changed startTimeUnixNano and the rate stays positive, rather than reporting the naive -93760 delta.

What is a .json file?

JSON (JavaScript Object Notation) is a lightweight, text-based data-interchange format representing objects, arrays, strings, numbers, booleans, and null. It is language-independent, human-readable, and the dominant format for web APIs and configuration. It requires a single well-formed root value.

How to use this file

Use an example JSON file to test parsers and serializers, schema validation, Unicode and number-precision handling, and API request or response processing.

How to use this file for testing

“OTLP Metrics — Counter Reset on Process Restart (json)” 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: JSON · 5,443 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.

Code examples

import json

with open("otlp-metrics-counter-reset.json") as f:
    data = json.load(f)
print(type(data), len(data))

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