When deploying applications you will probably want to have some **replication of processes** to take advantage of **multiple cores** and to be able to handle more requests.

As you saw in the previous chapter about [Deployment Concepts](concepts.md){.internal-link target=_blank}, there are multiple strategies you can use.

{* ../../docs_src/configure_swagger_ui/tutorial002.py hl[3] *}

Essa configuração alteraria o tema de cores de destaque de sintaxe:

<img src="/img/tutorial/extending-openapi/image04.png">

## Alterar parâmetros de UI padrão do Swagger

streaming compression due to its stability and performance.

This algorithm is specifically optimized for machine generated content.
Write throughput is typically at least 500MB/s per CPU core,
and scales with the number of available CPU cores.
Decompression speed is typically at least 1GB/s.

This means that in cases where raw IO is below these numbers
compression will not only reduce disk usage but also help increase system throughput.

`max_sleep` to a *lower* value and setting `max_io` to a *higher* value would make heal go faster.

Each node is responsible of healing its local drives; Each drive will have multiple heal workers which is the quarter of the number of CPU cores of the node or the quarter of the configured nr_requests of the drive (https://www.kernel.org/doc/Documentation/block/queue-sysfs.txt). It is also possible to provide a custom number of workers by using this command: `mc admin config set alias/ heal...

![hdfs-configs](https://github.com/minio/minio/blob/master/docs/bigdata/images/image2.png?raw=true "hdfs advanced configs")

Navigate to **Custom core-site** to configure MinIO parameters for `_s3a_` connector

![s3a-config](https://github.com/minio/minio/blob/master/docs/bigdata/images/image5.png?raw=true "custom core-site")

```
sudo pip install yq
alias kv-pairify='yq ".configuration[]" | jq ".[]" | jq -r ".name + \"=\" + .value"'
```

    /**
     * ProjectBuilder parallelism.
     *
     * @since 4.0.0
     */
    @Config(type = "java.lang.Integer", defaultValue = "cores/2 + 1")
    public static final String MAVEN_MODEL_BUILDER_PARALLELISM = "maven.modelBuilder.parallelism";

    /**
     * User property for enabling/disabling the consumer POM feature.
     *
     * @since 4.0.0

Por exemplo:

* **Processamento de áudio** ou **imagem**
* **Visão Computacional**: uma imagem é composta por milhões de pixels, cada pixel tem 3 valores / cores, processar isso normalmente exige alguma computação em todos esses pixels ao mesmo tempo

### Multiple Processes - Workers { #multiple-processes-workers }

If you have more clients than what a single process can handle (for example if the virtual machine is not too big) and you have **multiple cores** in the server's CPU, then you could have **multiple processes** running with the same application at the same time, and distribute all the requests among them.

process** (e.g. a Uvicorn process running your FastAPI application). They would all be **identical containers**, running the same thing, but each with its own process, memory, etc. That way you would take advantage of **parallelization** in **different cores** of the CPU, or even in **different machines**.

And the distributed container system with the **load balancer** would **distribute the requests** to each one of the containers with your app **in turns**. So, each request could be handled...

  - [Known Issues and Important Steps before Upgrading](#known-issues-and-important-steps-before-upgrading)
      - [ThirdPartyResource](#thirdpartyresource)
      - [kubectl](#kubectl)
      - [kubernetes Core Known Issues](#kubernetes-core-known-issues)
      - [Docker runtime Known Issues](#docker-runtime-known-issues)
      - [Rkt runtime Known Issues](#rkt-runtime-known-issues)
  - [Provider-specific Notes](#provider-specific-notes)