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Definition

The min latency test ensures that the minimum 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 minimum latency represents the best-case performance of your model, indicating the fastest possible response time.
  • This metric helps identify the baseline performance capability and can reveal issues with caching, connection overhead, or model optimization.
  • Monitoring minimum latency is useful for understanding the lower bound of your system’s performance and ensuring it meets expectations for optimal conditions.

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Test configuration examples

If you are writing a tests.json, here are a few valid configurations for the min latency test: 
[
  {
    "name": "Min latency above 100 msec",
    "description": "Make sure that the minimum latency is above 100 msec to ensure realistic measurements",
    "type": "performance",
    "subtype": "metricThreshold",
    "thresholds": [
      {
        "insightName": "metrics",
        "insightParameters": null,
        "measurement": "minLatency",
        "operator": ">",
        "value": 100
      }
    ],
    "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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