scannerMetricScanBucketDrive // Single bucket on one drive
	scannerMetricCompactFolder   // Folder compacted.

	// Must be last:
	scannerMetricLast
)

// log scanner action.
// Use for s > scannerMetricStartTrace
func (p *scannerMetrics) log(s scannerMetric, paths ...string) func(custom map[string]string) {
	startTime := time.Now()
	return func(custom map[string]string) {

name: OSV-Scanner Scheduled Scan

on:
  schedule:
    - cron: 0 4 * * 1

permissions:
  # Require writing security events to upload SARIF file to security tab
  security-events: write
  # Only need to read contents
  contents: read

jobs:
  scan-scheduled:
    if: github.repository == 'tensorflow/tensorflow'

// This keeps the cache size at a reasonable size for all buckets.
//
// Whenever a branch is scanned, it is assumed that it will be un-compacted
// before it hits any of the above limits.
// This will make the branch rebalance itself when scanned if the distribution of objects has changed.

// scanDataFolder will scanner the basepath+cache.Info.Name and return an updated cache.

usage calculation. The scanner adapts to the system speed and completely pauses when the system is under load. It is possible to adjust the speed of the scanner and thereby the latency of updates being reflected. The delays between each operation of the scanner can be adjusted by the `mc admin config set alias/ delay=15.0`. By default the value is `10.0`. This means the scanner will sleep *10x* the time each operation takes.

In most setups this will keep the scanner slow enough to not impact...

// Scan advances the [Scanner] to the next token, which will then be
// available through the [Scanner.Bytes] or [Scanner.Text] method. It returns false when
// there are no more tokens, either by reaching the end of the input or an error.
// After Scan returns false, the [Scanner.Err] method will return any error that
// occurred during scanning, except that if it was [io.EOF], [Scanner.Err]
// will return nil.

	// Put all buckets into channel.
	bucketCh := make(chan BucketInfo, len(buckets))

	// Shuffle buckets to ensure total randomness of buckets, being scanned.
	// Otherwise same set of buckets get scanned across erasure sets always.
	// at any given point in time. This allows different buckets to be scanned
	// in different order per erasure set, this wider spread is needed when
	// there are lots of buckets with different order of objects in them.

	t.Skip("Unstable test")
	data := []byte("abcdefghijklmnopqrstuvwxyz0123456789")

	var i int
	r := bytes.NewReader(data)
	scanner := newScanner(r)
	for scanner.pos < atomic.LoadInt64(&scanner.end) {
		c := scanner.next()
		if scanner.readerErr != nil {
			t.Fatal(scanner.readerErr)
		}
		if c != data[i] {
			t.Fatalf("expected %s, got %s", string(data[i]), string(c))
		}

	DB.Migrator().DropTable(adaptorSerializerModel(&SerializerStruct{}))
	if err := DB.Migrator().AutoMigrate(adaptorSerializerModel(&SerializerStruct{})); err != nil {
		t.Fatalf("no error should happen when migrate scanner, valuer struct, got error %v", err)
	}

	createdAt := time.Date(2020, 1, 1, 0, 0, 0, 0, time.UTC)
	updatedAt := createdAt.Unix()

	data := SerializerStruct{
		Name:            []byte("jinzhu"),

The scanner now allows retrieving the end position of a token via the new [Scanner.End] method....

## Implementation

ILM tiering takes place when a object placed in the bucket meets lifecycle transition rules and becomes eligible for tiering. MinIO scanner (which runs at one minute intervals, each time scanning one sixteenth of the namespace), picks up the object for tiering. The data is moved to the remote tier in entirety, leaving only the object metadata on MinIO.