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).

)

// For windows our files have .exe additionally.
var minioReleaseWindowsInfoURL = MinioReleaseURL + "minio.exe.sha256sum"

// minioVersionToReleaseTime - parses a standard official release
// MinIO version string.
//
// An official binary's version string is the release time formatted
// with RFC3339 (in UTC) - e.g. `2017-09-29T19:16:56Z`
func minioVersionToReleaseTime(version string) (releaseTime time.Time, err error) {

else
  SHA=$(grep "istio.io/api" go.mod | head -n1 | awk '{ print $2 }')
  if [[ ${SHA} == *"-"* && ! ${SHA} =~ -rc.[0-9]$ && ! ${SHA} =~ -beta.[0-9]$ && ! ${SHA} =~ -alpha.[0-9]$ ]]; then
    # not an official release or release candidate, so get the commit sha
    SHA=$(echo "${SHA}" | awk -F '-' '{ print $NF }')
  fi
fi

if [ -z "${SHA}" ]; then

build:cuda_clang_official --config=cuda_clang
build:cuda_clang_official --action_env=TF_CUDA_VERSION="12"
build:cuda_clang_official --action_env=TF_CUDNN_VERSION="8"
build:cuda_clang_official --action_env=CUDA_TOOLKIT_PATH="/usr/local/cuda-12.3"
build:cuda_clang_official --action_env=GCC_HOST_COMPILER_PATH="/dt9/usr/bin/gcc"
build:cuda_clang_official --action_env=CLANG_CUDA_COMPILER_PATH="/usr/lib/llvm-17/bin/clang"

That demonstrates how the Proxy (Traefik) uses the path prefix and how the server (Uvicorn) uses the `root_path` from the option `--root-path`.

### Check the docs UI

But here's the fun part. ✨

## Opinions

"_[...] I'm using **FastAPI** a ton these days. [...] I'm actually planning to use it for all of my team's **ML services at Microsoft**. Some of them are getting integrated into the core **Windows** product and some **Office** products._"

<div style="text-align: right; margin-right: 10%;">Kabir Khan - <strong>Microsoft</strong> <a href="https://github.com/tiangolo/fastapi/pull/26" target="_blank"><small>(ref)</small></a></div>

---

## Meinungen

„_[...] Ich verwende **FastAPI** heutzutage sehr oft. [...] Ich habe tatsächlich vor, es für alle **ML-Dienste meines Teams bei Microsoft** zu verwenden. Einige davon werden in das Kernprodukt **Windows** und einige **Office**-Produkte integriert._“

<div style="text-align: right; margin-right: 10%;">Kabir Khan - <strong>Microsoft</strong> <a href="https://github.com/tiangolo/fastapi/pull/26" target="_blank"><small>(Ref)</small></a></div>

---

"*[...] Estou usando **FastAPI** muito esses dias. [...] Estou na verdade planejando utilizar ele em todos os times de **serviços _Machine Learning_ na Microsoft**. Alguns deles estão sendo integrados no _core_ do produto **Windows** e alguns produtos **Office**.*"

<div style="text-align: right; margin-right: 10%;">Kabir Khan - <strong>Microsoft</strong> <a href="https://github.com/tiangolo/fastapi/pull/26" target="_blank"><small>(ref)</small></a></div>

---

## Görüşler

"_[...] Bugünlerde **FastAPI**'ı çok fazla kullanıyorum. [...] Aslında bunu ekibimin **Microsoft'taki Machine Learning servislerinin** tamamında kullanmayı planlıyorum. Bunlardan bazıları **Windows**'un ana ürünlerine ve **Office** ürünlerine entegre ediliyor._"

<div style="text-align: right; margin-right: 10%;">Kabir Khan - <strong>Microsoft</strong> <a href="https://github.com/tiangolo/fastapi/pull/26" target="_blank"><small>(ref)</small></a></div>

## Враження

"_[...] I'm using **FastAPI** a ton these days. [...] I'm actually planning to use it for all of my team's **ML services at Microsoft**. Some of them are getting integrated into the core **Windows** product and some **Office** products._"

<div style="text-align: right; margin-right: 10%;">Kabir Khan - <strong>Microsoft</strong> <a href="https://github.com/tiangolo/fastapi/pull/26" target="_blank"><small>(ref)</small></a></div>

---