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.

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.

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...

![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"'
```

cluster_deadline                (duration)  set the deadline for cluster readiness check (default: '10s')
cors_allow_origin               (csv)       set comma separated list of origins allowed for CORS requests (default: '*')
remote_transport_deadline       (duration)  set the deadline for API requests on remote transports while proxying between federated instances e.g. "2h" (default: '2h')

		for i := range cpus {
			cpuMap[cpus[i].PhysicalID] = struct{}{}
			coreMap[cpus[i].CoreID] = struct{}{}
		}
		cpu := cpus[0]
		uaAppend(" CPU ", fmt.Sprintf("(total_cpus:%d, total_cores:%d; vendor:%s; family:%s; model:%s; stepping:%d; model_name:%s)",
			len(cpuMap), len(coreMap), cpu.VendorID, cpu.Family, cpu.Model, cpu.Stepping, cpu.ModelName))
	}
	uaAppend(")", "")

### 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.

Por exemplo:

* **Processamento de áudio** ou **imagem**
* **Visão do Computador**: uma imagem é composta por milhões de pixels, cada pixel tem 3 valores (cores, processamento que normalmente exige alguma computação em todos esses pixels ao mesmo tempo)

  - [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)

### 简单请求

任何带有 `Origin` 请求头的请求。在这种情况下，中间件将像平常一样传递请求，但是在响应中包含适当的 CORS headers。

## 更多信息

更多关于 <abbr title="Cross-Origin Resource Sharing">CORS</abbr> 的信息，请查看 <a href="https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS" class="external-link" target="_blank">Mozilla CORS 文档</a>。

!!! note "技术细节"
    你也可以使用 `from starlette.middleware.cors import CORSMiddleware`。