!!! tip
    Don't worry if some of these items about **containers**, Docker, or Kubernetes don't make a lot of sense yet.

    I'll tell you more about container images, Docker, Kubernetes, etc. in a future chapter: [FastAPI in Containers - Docker](docker.md){.internal-link target=_blank}.

## Previous Steps Before Starting

In those cases, you can use the **official Docker image** that includes **Gunicorn** as a process manager running multiple **Uvicorn worker processes**, and some default settings to adjust the number of workers based on the current CPU cores automatically. I'll tell you more about it below in [Official Docker Image with Gunicorn - Uvicorn](#official-docker-image-with-gunicorn-uvicorn).

```console
$ pip install "hypercorn[trio]"
---> 100%
```

</div>

### Run with Trio

Then you can pass the command line option `--worker-class` with the value `trio`:

<div class="termy">

```console
$ hypercorn main:app --worker-class trio
```

</div>

And that will start Hypercorn with your app using Trio as the backend.

  istioctl x ztunnel-config workload

  # Retrieve summary of workloads on node XXXX for a given Ztunnel instance.
  istioctl x ztunnel-config workload <ztunnel-name[.namespace]> --node ambient-worker

  # Retrieve full workload dump of workloads with address XXXX for a given Ztunnel instance.
  istioctl x ztunnel-config workload <ztunnel-name[.namespace]> --address 0.0.0.0 -o json

					"security",
					"input-tracking",
					"base-ide-plugins"
				]
			},
			{
				"parallelizationMethod":{
					"name":"TestDistribution"
				},
				"subprojects":[
					"testing-jvm",
					"worker-processes",
					"files",
					"java-language-extensions",
					"build-cache-packaging",
					"build-operations",
					"precondition-tester",
					"tooling-api-builders",
					"hashing",

import okhttp3.internal.assertHeld
import okhttp3.internal.concurrent.TaskRunner.Companion.INSTANCE
import okhttp3.internal.okHttpName
import okhttp3.internal.threadFactory

/**
 * A set of worker threads that are shared among a set of task queues.
 *
 * Use [INSTANCE] for a task runner that uses daemon threads. There is not currently a shared
 * instance for non-daemon threads.
 *

*   `tf.data`:

    *   Added `target_workers` param to `data_service_ops.from_dataset_id` and
        `data_service_ops.distribute`. Users can specify `"AUTO"`, `"ANY"`, or
        `"LOCAL"` (case insensitive). If `"AUTO"`, tf.data service runtime
        decides which workers to read from. If `"ANY"`, TF workers read from any
        tf.data service workers. If `"LOCAL"`, TF workers will only read from

    font-family: 'Roboto Mono', 'Fira Mono', Consolas, Menlo, Monaco, 'Courier New', Courier, monospace;
    border-radius: 4px;
    padding: 75px 45px 35px;
    position: relative;
    -webkit-box-sizing: border-box;
            box-sizing: border-box;
    line-height: 1.2;
}

[data-termynal]:before {
    content: '';
    position: absolute;
    top: 15px;
    left: 15px;

func (e ErasureInfo) ShardSize() int64 {
	return ceilFrac(e.BlockSize, int64(e.DataBlocks))
}

// IsValid - tells if erasure info fields are valid.
func (fi FileInfo) IsValid() bool {
	if fi.Deleted {
		// Delete marker has no data, no need to check
		// for erasure coding information
		return true
	}
	dataBlocks := fi.Erasure.DataBlocks
	parityBlocks := fi.Erasure.ParityBlocks
	correctIndexes := (fi.Erasure.Index > 0 &&

				// Bucket is versioned and no version was explicitly
				// mentioned for deletes, create a delete marker instead.
				vr.ModTime = UTCNow()
				vr.Deleted = true
				// Versioning suspended means that we add a `null` version
				// delete marker, if not add a new version for this delete
				// marker.
				if versioned {
					vr.VersionID = mustGetUUID()
				}
			}
		}