}

// Target implements logger.Target and sends the json
// format of a log entry to the configured http endpoint.
// An internal buffer of logs is maintained but when the
// buffer is full, new logs are just ignored and an error
// is returned to the caller.
type Target struct {
	totalMessages  atomic.Int64
	failedMessages atomic.Int64
	status         atomic.Int32

	// Worker control
	workers    atomic.Int64

   * the output future list. (Such races are impossible to solve without global synchronization of
   * all future completions. And they should have little practical impact.)
   *
   * <p>Cancelling a delegate future propagates to input futures once all the delegates complete,
   * either from cancellation or because an input future has completed. If N futures are passed in,

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error rate, and request latency at p50, p90, and p99 percentiles. The
query results are printed to the console, organized by workload name.

All metrics returned are from server-side reports. This means that latencies
and error rates are from the perspective of the service itself and not of an
individual client (or aggregate set of clients). Rates and latencies are
calculated over a time interval of 1 minute.
`,

 *
 * <p>Subclasses are guaranteed that the life cycle methods ({@link #runOneIteration}, {@link
 * #startUp} and {@link #shutDown}) will never run concurrently. Notably, if any execution of {@link
 * #runOneIteration} takes longer than its schedule defines, then subsequent executions may start
 * late. Also, all life cycle methods are executed with a lock held, so subclasses can safely modify

const (
	opPlus     = "+"
	opMinus    = "-"
	opDivide   = "/"
	opMultiply = "*"
	opModulo   = "%"
)

// For arithmetic operations, if both values are numeric then the
// operation shall succeed. If the types are unknown automatic type
// conversion to a number is attempted.
func (v *Value) arithOp(op string, a *Value) error {
	err := inferTypeForArithOp(v)
	if err != nil {
		return err
	}

// Kubernetes, as specified in requests and limits, describing each pod in the
// current scale target (e.g. CPU or memory).  The values will be averaged
// together before being compared to the target.  Such metrics are built in to
// Kubernetes, and have special scaling options on top of those available to
// normal per-pod metrics using the "pods" source.  Only one "target" type
// should be set.
message ContainerResourceMetricSource {

`FastAPI` es una clase que hereda directamente de `Starlette`.

También puedes usar toda la funcionalidad de <a href="https://www.starlette.io/" class="external-link" target="_blank">Starlette</a>.

///

### Paso 2: crea un "instance" de `FastAPI`

```Python hl_lines="3"
{!../../docs_src/first_steps/tutorial001.py!}
```

Aquí la variable `app` será un instance de la clase `FastAPI`.

# How to monitor MinIO server with Grafana [![Slack](https://slack.min.io/slack?type=svg)](https://slack.min.io)

[Grafana](https://grafana.com/) allows you to query, visualize, alert on and understand your metrics no matter where they are stored. Create, explore, and share dashboards with your team and foster a data driven culture.

## Prerequisites