metrics.LinearBuckets(1, 1, 59),      // 1s, 2s, 3s, ... 59s
				metrics.LinearBuckets(60, 5, 12),     // 60s, 65s, 70s, ... 115s
				metrics.LinearBuckets(120, 30, 7),    // 2min, 2.5min, 3min, ..., 5min
			),
			StabilityLevel: metrics.ALPHA,
		},
	)

	// EndpointChangesPending is the number of pending endpoint changes that
	// have not yet been synced to the proxy.

| `minio_node_cpu_avg_load5`           | CPU load average 5min.                     |
| `minio_node_cpu_avg_load5_avg`       | CPU load average 5min (avg).               |
| `minio_node_cpu_avg_load5_max`       | CPU load average 5min (max).               |
| `minio_node_cpu_avg_load5_perc`      | CPU load average 5min (percentage).        |

		cpuSteal:          "CPU steal time",
		cpuNice:           "CPU nice time",
		cpuLoad1:          "CPU load average 1min",
		cpuLoad5:          "CPU load average 5min",
		cpuLoad15:         "CPU load average 15min",
		cpuLoad1Perc:      "CPU load average 1min (perentage)",
		cpuLoad5Perc:      "CPU load average 5min (percentage)",
		cpuLoad15Perc:     "CPU load average 15min (percentage)",
	}
	resourceMetricsGroups = []*MetricsGroupV2{

		// become normal. Check again.
		if e < emin {
			// denormal number: recompute precision
			// Since rounding may have at best increased precision
			// and we have eliminated p <= 0 early, we know p > 0.
			// bexp == 0 for denormals
			p = mbits + 1 - emin + int(e)
			mant = msb32(r.mant) >> uint(fbits-p)
		} else {
			// normal number: emin <= e <= emax
			bexp = uint32(e+bias) << mbits

  // Only qint8 and quint8 are considered here.
  double qmin, qmax;
  if (type == DT_QUINT8) {
    qmin = 0.0;
    qmax = 255.0;
  } else if (type == DT_QINT8) {
    qmin = -128.0;
    qmax = 127.0;
  } else {
    return absl::InvalidArgumentError("Only int8 and uint8 are considered.");
  }
  return std::make_pair((qmin - mean) / std, (qmax - mean) / std);
}

// TEMPORARY until bootstrap version catches up.
func imin(i, j int) int {
	if i < j {
		return i
	}
	return j
}

// TEMPORARY until bootstrap version catches up.
func imax(i, j int) int {
	if i > j {
		return i
	}
	return j
}

// Overlaps returns true if here is any overlap between i and i2.
func (i Interval) Overlaps(i2 Interval) bool {
	return (imin(i.en, i2.en) - imax(i.st, i2.st)) > 0
}

## Pydantic

Tüm veri doğrulamaları <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> tarafından arka planda gerçekleştirilir, bu sayede tüm avantajlardan faydalanabilirsiniz. Böylece, emin ellerde olduğunuzu hissedebilirsiniz.

Aynı tip tanımlamalarını `str`, `float`, `bool` ve diğer karmaşık veri tipleri ile kullanma imkanınız vardır.

Bunlardan birkaçı, bu eğitimin ileriki bölümlerinde irdelenmiştir.

		// longer lasting concerns which will eventually be retried on 1min interval.
		// Unlike the mutating webhook controller, we do not use NewItemFastSlowRateLimiter. This is because
		// the validation controller waits for its own service to be ready, so typically this takes a few seconds
		// before we are ready; using FastSlow means we tend to always take the Slow time (1min).

               "options": {
                  "calculate": true,
                  "calculation": {
                     "xBuckets": {
                        "mode": "size",
                        "value": "1min"
                     }
                  },
                  "cellGap": 2,
                  "color": {
                     "mode": "scheme",
                     "scheme": "Spectral",

         },
         "id": 13,
         "interval": "1m",
         "options": {
            "calculation": {
               "xBuckets": {
                  "mode": "size",
                  "value": "1min"
               }
            },
            "cellGap": 0,
            "color": {
               "mode": "scheme",
               "scheme": "Spectral",
               "steps": 128
            },