Interface ExponentialHistogram

📊 ExponentialHistogram represents a metric calculated by aggregating as an ExponentialHistogram.

Exponential histograms provide more efficient storage for wide value ranges by using exponentially-sized buckets. Great for metrics with large dynamic ranges.

Example

const memoryUsageExpHistogram: ExponentialHistogram = {
  dataPoints: [
    {
      attributes: [
        { key: "process.type", value: { stringValue: "turtle" } }
      ],
      startTimeUnixNano: "1640995200000000000",
      timeUnixNano: "1640995260000000000",
      count: 1000,
      sum: 524288000,
      scale: 2,
      zeroCount: 5,
      positive: {
        offset: 0,
        bucketCounts: [10, 20, 30, 25, 15]
      },
      negative: {
        offset: 0,
        bucketCounts: []
      },
      flags: 0,
      exemplars: [],
      zeroThreshold: 0.001
    }
  ],
  aggregationTemporality: AggregationTemporality.CUMULATIVE
};
interface ExponentialHistogram {
    aggregationTemporality: AggregationTemporality;
    dataPoints: ExponentialHistogramDataPoint[];
}

Properties

aggregationTemporality dataPoints

Properties

aggregationTemporality

aggregationTemporality: AggregationTemporality

How the aggregation is performed over time

dataPoints

dataPoints: ExponentialHistogramDataPoint[]

Array of exponential histogram data points

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