* When we need a new thread to run tasks, we call [Backend.execute]. A few microseconds later we
   * expect a newly-started thread to call [Runnable.run]. We shouldn't request new threads until
   * the already-requested ones are in service, otherwise we might create more threads than we need.
   *
   * We use [executeCallCount] and [runCallCount] to defend against starting more threads than we
   * need. Both fields are guarded by [lock].
   */

  login credentials.

- Allows authentication and access for all
  - Built-in IDP users and their respective service accounts
  - LDAP/AD users and their respective service accounts
  - OpenID/OIDC service accounts

- On versioned buckets, FTP/SFTP only operates on latest objects, if you need to retrieve

    - `istio-cni-config` configmap with CNI plugin config to add to CNI plugin chained config
    - creates service-account `istio-cni` with `ClusterRoleBinding` to allow gets on pods' info and delete/modifications for recovery.

- `install-cni` container
    - copies `istio-cni` and `istio-iptables` to `/opt/cni/bin`
    - creates kubeconfig for the service account the pod runs under

      throw AssertionError("Thread ${Thread.currentThread().name} MUST NOT hold lock on $this")
    }
  }

  val logger = Logger.getLogger("TaskFaker." + instance++)

  /** Though this executor service may hold many threads, they are not executed concurrently. */
  private val tasksExecutor = Executors.newCachedThreadPool(threadFactory("TaskFaker"))

  /**

| `minio_cluster_iam_plugin_authn_service_failed_requests_minute` | `counter` | When plugin authentication is configured, returns failed requests count in the last full minute                          |        |
| `minio_cluster_iam_plugin_authn_service_last_fail_seconds`      | `counter` | When plugin authentication is configured, returns time (in seconds) since the last failed request to the service         |        |

* **Cloud services** that handle this for you
    * The cloud service will probably **handle replication for you**. It would possibly let you define **a process to run**, or a **container image** to use, in any case, it would most probably be **a single Uvicorn process**, and the cloud service would be in charge of replicating it.

!!! tip

    *   Added support for cross-trainer data caching in tf.data service. This
        saves computation resources when concurrent training jobs train from the
        same dataset. See
        (https://www.tensorflow.org/api_docs/python/tf/data/experimental/service#sharing_tfdata_service_with_concurrent_trainers)
        for more details.
    *   Added `dataset_id` to `tf.data.experimental.service.register_dataset`.

Alternatively, HTTPS could be handled by a cloud provider as one of their services (while still running the application in a container).

## Running on Startup and Restarts

There is normally another tool in charge of **starting and running** your container.

It could be **Docker** directly, **Docker Compose**, **Kubernetes**, a **cloud service**, etc.

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