A `200 OK` Response should have `application/json` content-type and body with the following structure:

```json
{
    "user": <string>,
    "maxValiditySeconds": <integer>,
    "claims": <key-value-pairs>
}
```

| Parameter Name     | Value Type                              | Purpose                                                |

[Prometheus](https://prometheus.io) is a cloud-native monitoring platform. Prometheus offers a multi-dimensional data model with time series data identified by metric name and key/value pairs. The data collection happens via a pull model over HTTP/HTTPS. Users looking to monitor their MinIO instances can point Prometheus configuration to scrape data from following endpoints. 

package cmd

import (
	"errors"
	"fmt"

	"github.com/tinylib/msgp/msgp"
)

// xlMetaInlineData is serialized data in [string][]byte pairs.
type xlMetaInlineData []byte

// xlMetaInlineDataVer indicates the version of the inline data structure.
const xlMetaInlineDataVer = 1

// versionOK returns whether the version is ok.

				// Log and continue error - perhaps it'll work the next time.
				iamLogIf(GlobalContext, err)
			}
		}
	}
}

// NormalizeLDAPAccessKeypairs - normalize the access key pairs (service
// accounts) for LDAP users. This normalizes the parent user and the group names
// whenever the parent user parses validly as a DN.

// along with this program.  If not, see <http://www.gnu.org/licenses/>.

package kms

import (
	"bytes"
	"sort"
	"unicode/utf8"
)

// Context is a set of key-value pairs that
// are associated with a generate data encryption
// key (DEK).
//
// A KMS implementation may bind the context to the
// generated DEK such that the same context must be
// provided when decrypting an encrypted DEK.

### **4.2 WordCount**

WordCount is a simple program that counts how often a word occurs in a text file. The code builds a dataset of (String, Int) pairs called counts, and saves the dataset to a file.

The following example submits WordCount code to the Scala shell. Select an input file for the Spark WordCount example. We can use any text file as input.

	return mg
}

// AddExtraLabels - adds extra (constant) label KV pairs to the metrics group.
// This is a helper to initialize the `ExtraLabels` field. The argument is a
// list of ordered label name and value pairs.
func (mg *MetricsGroup) AddExtraLabels(labels ...string) {
	if len(labels)%2 != 0 {
		panic("Labels must be an ordered list of name value pairs")
	}
	if mg.ExtraLabels == nil {

	Replicate       bool
	ResetID         string
	ResetBeforeDate time.Time
}

var errInvalidReplicateDecisionFormat = fmt.Errorf("ReplicateDecision has invalid format")

// parse k-v pairs of target ARN to stringified ReplicateTargetDecision delimited by ',' into a
// ReplicateDecision struct
func parseReplicateDecision(ctx context.Context, bucket, s string) (r ReplicateDecision, err error) {
	r = ReplicateDecision{

	}
	if a.Index == "" {
		return errors.New("empty index value")
	}

	if (a.Username == "" && a.Password != "") || (a.Username != "" && a.Password == "") {
		return errors.New("username and password should be set in pairs")
	}

	return nil
}

// ElasticsearchTarget - Elasticsearch target.
type ElasticsearchTarget struct {
	initOnce once.Init

	id         event.TargetID
	args       ElasticsearchArgs