Se você executar **múltiplos processos por contêiner**, deve garantir que o número de processos iniciados não **consuma mais memória** do que o disponível.

## Passos anteriores antes de iniciar e contêineres { #previous-steps-before-starting-and-containers }

Se você estiver usando contêineres (por exemplo, Docker, Kubernetes), existem duas abordagens principais que você pode usar.

### Contêineres Múltiplos { #multiple-containers }

AppType = TypeVar("AppType", bound="FastAPI")


class FastAPI(Starlette):
    """
    `FastAPI` app class, the main entrypoint to use FastAPI.

    Read more in the
    [FastAPI docs for First Steps](https://fastapi.tiangolo.com/tutorial/first-steps/).

    ## Example

    ```python
    from fastapi import FastAPI

    app = FastAPI()
    ```
    """

    def __init__(
        self: AppType,
        *,

* PetSet has been renamed to StatefulSet.
  If you have existing PetSets, **you must perform extra migration steps** both

performing the TLS Bootstrap properly. Earlier, `kubeadm join` only did the discovery part and exited successfully without checking that the kubelet actually started properly and performed the TLS bootstrap correctly. Now, as kubeadm runs some post-join steps (for example, annotating the Node API object with the CRISocket), `kubeadm join` is now waiting for the kubelet to perform the TLS Bootstrap, and then uses that credential to perform further actions. This also improves the UX, as `kubeadm` will exit...

		cache.iamGroupPolicyMap.Delete(group)

		cache.updatedAt = time.Now()
		return nil
	}

	gi := cache.iamGroupsMap[group]

	// Updating the group memberships cache happens in two steps:
	//
	// 1. Remove the group from each user's list of memberships.
	// 2. Add the group to each member's list of memberships.
	//
	// This ensures that regardless of members being added or

*   Multiple C++ API updates.
*   Multiple TensorBoard updates including:
    *   Users can now view image summaries at various sampled steps (instead of
        just the last step).
    *   Bugs involving switching runs as well as the image dashboard are fixed.
    *   Removed data download links from TensorBoard.

- [migration phase 1] PodMatchNodeSelector/NodAffinity as filter plugin ([#83660](https://github.com/kubernetes/kubernetes/pull/83660), [@wgliang](https://github.com/wgliang))
- Add more tracing steps in generic_scheduler ([#83539](https://github.com/kubernetes/kubernetes/pull/83539), [@wgliang](https://github.com/wgliang))

//
// Scanning stops if the function returns an error, in which case some of
// the input may be discarded. If that error is [ErrFinalToken], scanning
// stops with no error. A non-nil token delivered with [ErrFinalToken]
// will be the last token, and a nil token with [ErrFinalToken]
// immediately stops the scanning.
//

	The fields are compared in source order, and comparison stops as
	soon as two field values differ (or all fields have been compared).
	</li>

	<li>
	Array types are comparable if their array element types are comparable.
	Two array values are equal if their corresponding element values are equal.
	The elements are compared in ascending index order, and comparison stops

In v1.9 SIG AWS has improved stability of EBS support across the board. If a Volume is “stuck” in the attaching state to a node for too long a unschedulable taint will be applied to the node, so a Kubernetes admin can [take manual steps to correct the error](http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ebs-attaching-volume.html). Users are encouraged to ensure they are monitoring for the taint, and should consider automatically terminating instances in this state.