CPU Metrics Example

This example shows a common Pond workflow for infrastructure metrics.

import { Sequence, TimeSeries } from 'pond-ts';

const schema = [
  { name: 'time', kind: 'time' },
  { name: 'cpu', kind: 'number' },
  { name: 'requests', kind: 'number' },
  { name: 'host', kind: 'string' },
] as const;

const cpu = TimeSeries.fromJSON({
  name: 'cpu',
  schema,
  rows: [
    ['2025-01-01T00:00:00Z', 0.31, 120, 'api-1'],
    ['2025-01-01T00:01:00Z', 0.44, 135, 'api-1'],
    ['2025-01-01T00:02:00Z', 0.52, 141, 'api-1'],
    ['2025-01-01T00:03:00Z', 0.48, 128, 'api-1'],
    ['2025-01-01T00:04:00Z', 0.63, 166, 'api-1'],
  ],
});

const perMinute = cpu.align(Sequence.every('1m'), {
  method: 'hold',
});

const fiveMinute = cpu.aggregate(Sequence.every('5m'), {
  cpu: 'avg',
  requests: 'sum',
  host: 'last',
});

const rolling = cpu.rolling('3m', {
  cpu: 'avg',
  requests: 'sum',
});

const smoothed = cpu.smooth('cpu', 'ema', {
  alpha: 0.35,
  output: 'cpuTrend',
});

What this gives you

• perMinute: aligned interval data for dashboards and joins
• fiveMinute: bucketed reporting metrics
• rolling: short-term windowed behavior
• smoothed: a derived trend line for charts or alerts