$ cd fess-14.17.x
    $ ./bin/fess

詳細については、[インストールガイド](https://fess.codelibs.org/14.17/install/index.html)を参照してください。

### Docker

[ghcr.io](https://github.com/orgs/codelibs/packages)にDockerイメージを提供しています。また、このリポジトリにはDocker Compose（YAML）ファイルも用意されています。[こちらのリポジトリ](https://github.com/codelibs/docker-fess/tree/master/compose)で確認できます。

### ブラウザUI

- 検索UI: http://localhost:8080/

- Additional memory overhead per container in docker v1.11 ([#21737](https://github.com/docker/docker/issues/21737))
- [List of upstream fixes](https://github.com/docker/docker/compare/v1.10.3...runcom:docker-1.10.3-stable) for docker v1.10 identified by RedHat

#### Rkt runtime Known Issues

- A detailed list of known issues can be found [here](https://github.com/kubernetes/kubernetes.github.io/blob/release-1.3/docs/getting-started-guides/rkt/notes.md)

### 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.

  },
  "features": {
    "ghcr.io/devcontainers/features/docker-outside-of-docker:1": {},
    "ghcr.io/mpriscella/features/kind:1": {}
  },
  "customizations": {
    "vscode": {
      "extensions": [
        "golang.go",
        "rust-lang.rust-analyzer",
        "eamodio.gitlens",
        "zxh404.vscode-proto3",
        "ms-azuretools.vscode-docker",
        "redhat.vscode-yaml",
        "IBM.output-colorizer"

spec:
  initContainers:
    - name: istio-init
      image: docker.io/istio/proxy_init:unittest-{{.Values.global.tag}}
  containers:
    - name: istio-proxy

spec:
  initContainers:
  - name: istio-init
    image: docker.io/istio/proxy_init:unittest-{{.Values.global.suffix}}
  containers:
  - name: istio-proxy

ics-vidhya/deploy-machine-learning-models-with-keras-fastapi-redis-and-docker-4940df614ece title: Deploy Machine Learning Models with Keras, FastAPI, Redis and Docker - author: Mandy Gu author_link: https://towardsdatascience.com/@mandygu link: https://towardsdatascience.com/deploying-iris-classifications-with-fastapi-and-docker-7c9b83fdec3a title: 'Towards Data Science: Deploying Iris Classifications with FastAPI and Docker' - author: Michael Herman author_link: https://testdriven.io/authors/herman...

# Perform S3 operations in a ZIP content[![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/)

## Overview

# Bucket Versioning Design 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/)

## Description of `xl.meta`

`xl.meta` is a new self describing backend format used by MinIO to support AWS S3 compatible versioning.
This file is the source of truth for each `version` at rest. `xl.meta` is a msgpack file serialized from a

        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