### 全栈 FastAPI + PostgreSQL - 功能

* 完整的 **Docker** 集成（基于 Docker）
* Docker Swarm 开发模式
* **Docker Compose** 本地开发集成与优化
* **生产可用**的 Python 网络服务器，使用 Uvicorn 或 Gunicorn
* Python <a href="https://github.com/tiangolo/fastapi" class="external-link" target="_blank">**FastAPI**</a> 后端：

Klaus Post <******@****.***> 1708383286 -0800

        shell: bash
        run: |
          running_containers=$(docker ps -q) && \
          if [[ $running_containers == "" ]]; then
            echo "No running containers";
          else
            echo "Running container(s) found" && \
            docker stop $running_containers;
          fi
          docker container prune -f
          docker image prune -af
      - name: Clean repository
        shell: bash

### Full Stack FastAPI PostgreSQL - Recursos

* Integração completa **Docker**.
* Modo de implantação Docker Swarm.
* Integração e otimização **Docker Compose** para desenvolvimento local.
* **Pronto para Produção** com servidor _web_ usando Uvicorn e Gunicorn.

        track: stable
    spec:
      containers:
      - image: fake.docker.io/google-samples/hello-go-gke:1.0
        name: hello
        ports:
        - containerPort: 80
          name: http
        resources: {}
      - image: docker.io/istio/proxy_debug:unittest
        name: istio-proxy
        resources: {}
      initContainers:
      - image: docker.io/istio/proxy_init:unittest-test
        name: istio-init

# Bucket Quota Configuration Quickstart Guide [![Slack](https://slack.min.io/slack?type=svg)](https://slack.min.io) [![Docker Pulls](https://img.shields.io/docker/pulls/minio/minio.svg?maxAge=604800)](https://hub.docker.com/r/minio/minio/)

![quota](https://raw.githubusercontent.com/minio/minio/master/docs/bucket/quota/bucketquota.png)

Buckets can be configured to have `Hard` quota - it disallows writes to the bucket after configured quota limit is reached.

TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_cpu
TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow_cpu"
TFCI_DOCKER_ENABLE=1
TFCI_DOCKER_IMAGE=tensorflow/build:2.16-python${TFCI_PYTHON_VERSION}
TFCI_DOCKER_PULL_ENABLE=1
TFCI_DOCKER_REBUILD_ARGS="--build-arg PYTHON_VERSION=python$TFCI_PYTHON_VERSION --target=devel tensorflow/tools/tf_sig_build_dockerfiles"
TFCI_INDEX_HTML_ENABLE=1

#   container and start fresh, run "docker rm -f tf". Removing the container
#   destroys some temporary bazel data and causes longer builds.
#
#   You will need the NVIDIA Container Toolkit for GPU testing:
#   https://github.com/NVIDIA/nvidia-container-toolkit
#
#   Note: if you interrupt a bazel command on docker (ctrl-c), you
#   will need to run `docker exec tf pkill bazel` to quit bazel.
#

* **Memory**
* **Previous steps before starting**

## Containers and Docker

In the next chapter about [FastAPI in Containers - Docker](docker.md){.internal-link target=_blank} I'll tell some strategies you could use to handle the other **deployment concepts**.

        shell: bash
        run: |
          running_containers=$(docker ps -q) && \
          if [[ $running_containers == "" ]]; then
            echo "No running containers";
          else
            echo "Running container(s) found" && \
            docker stop $running_containers;
          fi
          docker container prune -f
      - name: Clean repository
        shell: bash