/**
   * Returns a hash function implementing the Message Authentication Code (MAC) algorithm, using the
   * MD5 (128 hash bits) hash function and the given secret key.
   *
   * <p>If you are designing a new system that needs HMAC, prefer {@link #hmacSha256} or other
   * future-proof algorithms <a
   * href="https://datatracker.ietf.org/doc/html/rfc6151#section-2.3">over {@code hmacMd5}</a>.
   *
   * @param key the secret key

  metrics_path: /minio/v2/metrics/bucket
  scheme: http
  static_configs:
  - targets: ['localhost:9000']
```

##### Node (optional)

Optionally you can also collect per node metrics. This needs to be done on a per server instance.
The scrape configurations should use all the servers under `targets` so that graphing systems like
grafana can visualize them for all the nodes

```yaml
scrape_configs:

					if mv.ValueType == jstream.Object {
						// This is a JSON object type (that preserves key
						// order)
						kvs = mv.Value.(jstream.KVS)
					} else {
						// To be AWS S3 compatible Select for JSON needs to
						// output non-object JSON as single column value
						// i.e. a map with `_1` as key and value as the
						// non-object.
						kvs = jstream.KVS{jstream.KV{Key: "_1", Value: mv.Value}}
					}

For instance, given that TLS is enabled and you need to add trust for MinIO's own CA and for the CA of a Keycloak server, a Kubernetes secret can be created from the certificate files using `kubectl`:

```

MinIO is intended for early development and evaluation. For production clusters, deploy a [Distributed](https://min.io/docs/minio/container/operations/install-deploy-manage/deploy-minio-single-node-multi-drive.html) MinIO deployment.

MinIO needs a persistent volume to store configuration and application data. For testing purposes, you can launch MinIO by simply passing a directory (`/data` in the example below). This directory gets created in the container filesystem at the time of container...

      </execution>
    </executions>
  </plugin>
  .
  .
  .
</plugins>

 *       MoreExecutors.listeningDecorator}.
 *   <li>If you manually call {@link java.util.concurrent.FutureTask#set} or a similar method,
 *       create a {@link SettableFuture} instead. (If your needs are more complex, you may prefer
 *       {@link AbstractFuture}.)
 * </ul>
 *
 * <p><b>Test doubles</b>: If you need a {@code ListenableFuture} for your test, try a {@link

 *       MoreExecutors.listeningDecorator}.
 *   <li>If you manually call {@link java.util.concurrent.FutureTask#set} or a similar method,
 *       create a {@link SettableFuture} instead. (If your needs are more complex, you may prefer
 *       {@link AbstractFuture}.)
 * </ul>
 *
 * <p><b>Test doubles</b>: If you need a {@code ListenableFuture} for your test, try a {@link

# Extra Models

Continuing with the previous example, it will be common to have more than one related model.

This is especially the case for user models, because:

* The **input model** needs to be able to have a password.
* The **output model** should not have a password.
* The **database model** would probably need to have a hashed password.

/// danger

Never store user's plaintext passwords. Always store a "secure hash" that you can then verify.

/**
 * This class provides a skeletal implementation of the {@code Cache} interface to minimize the
 * effort required to implement this interface.
 *
 * <p>To implement a cache, the programmer needs only to extend this class and provide an
 * implementation for the {@link #put} and {@link #getIfPresent} methods. {@link #getAllPresent} is