* until a nonzero result is found; imposes "dictionary order." If the end of one iterable is
   * reached, but not the other, the shorter iterable is considered to be less than the longer one.
   * For example, a lexicographical natural ordering over integers considers {@code [] < [1] < [1,
   * 1] < [1, 2] < [2]}.
   *

}

// ObjectTooSmall error returned when the size of the object < what is expected.
type ObjectTooSmall GenericError

func (e ObjectTooSmall) Error() string {
	return "size of the object less than what is expected"
}

// OperationTimedOut - a timeout occurred.
type OperationTimedOut struct{}

func (e OperationTimedOut) Error() string {
	return "Operation timed out"
}

* **Intuitive**: Great editor support. <abbr title="also known as auto-complete, autocompletion, IntelliSense">Completion</abbr> everywhere. Less time debugging.
* **Easy**: Designed to be easy to use and learn. Less time reading docs.
* **Short**: Minimize code duplication. Multiple features from each parameter declaration. Fewer bugs.

// sort.Sort call, can be used to prepare arbitrary inputs for use as sets.
func uniq(data sort.Interface) (size int) {
	p, l := 0, data.Len()
	if l <= 1 {
		return l
	}
	for i := 1; i < l; i++ {
		if !data.Less(p, i) {
			continue
		}
		p++
		if p < i {
			data.Swap(p, i)
		}
	}
	return p + 1
}

// Remove any duplicates and return unique entries.
func uniqueEntries(paths []string) []string {

* Running on startup
* Restarts
* Replication (the number of processes running)
* Memory
* Previous steps before starting

## Memory

If you run **a single process per container** you will have a more or less well-defined, stable, and limited amount of memory consumed by each of those containers (more than one if they are replicated).

* **Intuitive**: Great editor support. <abbr title="also known as auto-complete, autocompletion, IntelliSense">Completion</abbr> everywhere. Less time debugging.
* **Easy**: Designed to be easy to use and learn. Less time reading docs.
* **Short**: Minimize code duplication. Multiple features from each parameter declaration. Fewer bugs.

An interesting detail is that the percentage of the **CPU used** by each process can **vary** a lot over time, but the **memory (RAM)** normally stays more or less **stable**.

If you have an API that does a comparable amount of computations every time and you have a lot of clients, then the **CPU utilization** will probably *also be stable* (instead of constantly going up and down quickly).

	dataUsageUpdateDirCycles         = 16                               // Visit all folders every n cycles.
	dataScannerCompactLeastObject    = 500                              // Compact when there is less than this many objects in a branch.
	dataScannerCompactAtChildren     = 10000                            // Compact when there are this many children in a branch.

		// clients detect malformed certificates during testing instead of e.g.
		// a self-signed certificate that works while a comparable certificate
		// issued by a trusted CA fails due to the MinIO server being less strict
		// w.r.t. key usage verification.
		//
		// Basically, MinIO is more consistent (from a client perspective) when
		// we verify the key usage all the time.
		var validKeyUsage bool

				}, w)
			}

			// fallback only when set.
			for {
				fd := fallback(werr)
				if fd == nil {
					break
				}
				// This fallback is only set when
				// askDisks is less than total
				// number of disks per set.
				werr = fd.WalkDir(ctx, WalkDirOptions{
					Limit:          opts.perDiskLimit,
					Bucket:         opts.bucket,
					BaseDir:        opts.path,