​
Definition

The 90th latency percentile test ensures that the 90th percentile latency for the data is within a given range.

​
Taxonomy

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

​
Why it matters

  • The 90th percentile latency provides insight into the performance experienced by the majority of users, excluding the worst 10% of cases.
  • This metric helps identify performance issues that affect a significant portion of users while being less sensitive to extreme outliers than maximum latency.
  • Monitoring the 90th percentile is crucial for maintaining consistent user experience and meeting SLA requirements.

​
Test configuration examples

If you are writing a tests.json, here are a few valid configurations for the 90th latency percentile test: 
[
  {
    "name": "90th percentile latency below 6000 msec",
    "description": "Make sure that the 90th percentile latency is below 6000 msec",
    "type": "performance",
    "subtype": "metricThreshold",
    "thresholds": [
      {
        "insightName": "metrics",
        "insightParameters": null,
        "measurement": "p90Latency",
        "operator": "<",
        "value": 6000
      }
    ],
    "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
  }
]