default            reviews-v3-5b9bd44f4-z9ms4                           10.244.1.43 ambient-worker        None                                HBONE
default            sleep-7656cf8794-lxcmx                               10.244.2.58 ambient-worker2       None                                HBONE

default   details-v1-698d88b-krdw7       10.244.2.55 ambient-worker2 None     HBONE
default   httpbin-7447985f87-t8hv7       10.244.1.40 ambient-worker  None     TCP
default   productpage-v1-675fc69cf-kkrm2 10.244.2.56 ambient-worker2 None     HBONE
default   ratings-v1-6484c4d9bb-8xc2r    10.244.2.57 ambient-worker2 None     HBONE
default   reviews-v1-5b5d6494f4-c7z5w    10.244.1.41 ambient-worker  None     HBONE

        daemon["Gradle daemon"]
        gradle --> daemon
        gradlew --> daemon
        tapi --> daemon
        
        worker["Worker process"]
        daemon --> worker

        worker2["Worker process"]
        daemon --> worker2

        worker3["Worker process"]
        daemon --> worker3
    
```

These are all Java processes. Each process has a corresponding "runtime".

```console
$ gunicorn main:app --workers 4 --worker-class uvicorn.workers.UvicornWorker --bind 0.0.0.0:80

[19499] [INFO] Starting gunicorn 20.1.0
[19499] [INFO] Listening at: http://0.0.0.0:80 (19499)
[19499] [INFO] Using worker: uvicorn.workers.UvicornWorker
[19511] [INFO] Booting worker with pid: 19511
[19513] [INFO] Booting worker with pid: 19513
[19514] [INFO] Booting worker with pid: 19514

[19499] [INFO] Starting gunicorn 20.1.0
[19499] [INFO] Listening at: http://0.0.0.0:80 (19499)
[19499] [INFO] Using worker: uvicorn.workers.UvicornWorker
[19511] [INFO] Booting worker with pid: 19511
[19513] [INFO] Booting worker with pid: 19513
[19514] [INFO] Booting worker with pid: 19514
[19515] [INFO] Booting worker with pid: 19515

In particular, when running on **Kubernetes** you will probably **not** want to use workers and instead run **a single Uvicorn process per container**, but I'll tell you about it later in that chapter.

///

## Multiple Workers

You can start multiple workers with the `--workers` command line option:

//// tab | `fastapi`

If you use the `fastapi` command:

<div class="termy">

///

## Vários trabalhadores

Você pode iniciar vários trabalhadores com a opção de linha de comando `--workers`:

//// tab | `fastapi`

Se você usar o comando `fastapi`:

<div class="termy">

```console
$ <pre> <font color="#4E9A06">fastapi</font> run --workers 4 <u style="text-decoration-style:single">main.py</u>
<font color="#3465A4">INFO    </font> Using path <font color="#3465A4">main.py</font>

      int64_t init_timeout_in_ms, int retries,
      bool clear_existing_contexts = false) = 0;

  // Initializes context for the local worker and no contexts will be created
  // for remote workers. Currently this only works for resetting context.
  // TODO(b/289445025): Consider removing this when we find a proper fix.
  virtual absl::Status InitializeLocalOnlyContext(const ServerDef& server_def,

	current     []jstream.KVS   // current block of results to be returned
	recordsRead int             // number of records read in current slice
	input       chan *queueItem // input for workers
	queue       chan *queueItem // output from workers in order
	err         error           // global error state, only touched by Reader.Read
	bufferPool  sync.Pool       // pool of []byte objects for input

	current      [][]string       // current block of results to be returned
	recordsRead  int              // number of records read in current slice
	input        chan *queueItem  // input for workers
	queue        chan *queueItem  // output from workers in order
	err          error            // global error state, only touched by Reader.Read
	bufferPool   sync.Pool        // pool of []byte objects for input