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Definition

The 99th latency percentile test ensures that the 99th percentile latency for the data is within a given range.

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Taxonomy

  • Task types: LLM, tabular classification, tabular regression, text classification.
  • Availability: .

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Why it matters

  • The 99th percentile latency captures the performance experienced by nearly all users, excluding only the worst 1% of cases.
  • This metric helps identify performance issues that could affect even a small percentage of users, which is important for maintaining high service quality.
  • Monitoring the 99th percentile is crucial for applications where consistent performance is critical, even for edge cases.

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Test configuration examples

If you are writing a tests.json, here are a few valid configurations for the 99th latency percentile test: 
[
  {
    "name": "99th percentile latency below 12000 msec",
    "description": "Make sure that the 99th percentile latency is below 12000 msec",
    "type": "performance",
    "subtype": "metricThreshold",
    "thresholds": [
      {
        "insightName": "metrics",
        "insightParameters": null,
        "measurement": "p99Latency",
        "operator": "<",
        "value": 12000
      }
    ],
    "subpopulationFilters": null,
    "mode": "development",
    "usesValidationDataset": true, // Apply test to the validation set
    "usesTrainingDataset": false,
    "usesMlModel": false,
    "syncId": "b4dee7dc-4f15-48ca-a282-63e2c04e0689" // Some unique id
  }
]
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