public class DockerElasticsearchDistributionType implements ElasticsearchDistributionType {

    DockerElasticsearchDistributionType() {}

    @Override
    public String getName() {
        return "docker";
    }

    @Override
    public boolean isDocker() {
        return true;
    }

        // javascript: protocol should be blocked
        assertFalse(result.contains("javascript:"));
    }

    @Test
    public void test_render_xss_dataProtocol() {
        String malicious = "[Click me](data:text/html,<script>alert('XSS')</script>)";
        String result = markdownRenderer.render(malicious);
        // data: protocol should be blocked
        assertFalse(result.contains("data:text/html"));

* **보안 - HTTPS**
* **서버 시작 시 실행**
* ***재시작***
* 복제(실행 중인 프로세스 수)
* **메모리**
* **시작하기 전의 이전 단계**

## 컨테이너와 도커 { #containers-and-docker }

다음 장인 [컨테이너에서의 FastAPI - 도커](docker.md)에서는 다른 **배포 개념들**을 처리하기 위해 사용할 수 있는 몇 가지 전략을 설명하겠습니다.

단일 Uvicorn 프로세스를 실행하기 위해, **처음부터 여러분만의 이미지를 직접 빌드**하는 방법을 보여드리겠습니다. 이는 간단한 과정이며, **Kubernetes** 같은 분산 컨테이너 관리 시스템을 사용할 때 아마도 이렇게 하고 싶을 것입니다.

  private static final long SMALL_TIMEOUT_MILLIS = 10;

  /** How long to wait when determining that a thread is blocked if we expect it to be blocked. */
  private static final long EXPECTED_HANG_DELAY_MILLIS = 75;

  /**
   * How long to wait when determining that a thread is blocked if we DON'T expect it to be blocked.
   */
  private static final long UNEXPECTED_HANG_DELAY_MILLIS = 10000;

  /**

    @Test
    public void testClearBlacklist() throws Exception {
        validator.addToBlacklist("\\share\\blocked");
        validator.clearBlacklist();

        // Should allow previously blacklisted path
        String allowed = validator.validatePath("\\share\\blocked\\file.txt");
        assertEquals("\\share\\blocked\\file.txt", allowed);
    }

    @Test
    public void testClearWhitelist() throws Exception {

							endpoints[i].Hostname()), endpoints[i].Hostname(), logger.ErrorKind)
					}

					continue
				}

				// return err if not Docker or Kubernetes
				// We use IsDocker() to check for Docker environment
				// We use IsKubernetes() to check for Kubernetes environment
				isLocal, err := isLocalHost(endpoints[i].Hostname(),
					endpoints[i].Port(),
					globalMinioPort,
				)

WIP ML Build Docker container for ML repositories (Tensorflow, JAX and XLA).

This container branches off from
/tensorflow/tools/tf_sig_build_dockerfiles/. However, since
hermetic CUDA and hermetic Python is now available for Tensorflow, a lot of the
requirements installed on the original container can be removed to reduce the
footprint of the container and make it more reusable across different ML

TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_cpu
TFCI_BUILD_PIP_PACKAGE_WHEEL_NAME_ARG="--repo_env=WHEEL_NAME=tensorflow_cpu"
TFCI_DOCKER_ENABLE=1
TFCI_DOCKER_IMAGE=us-docker.pkg.dev/ml-oss-artifacts-published/ml-public-container/ml-build:latest
TFCI_DOCKER_PULL_ENABLE=1
TFCI_DOCKER_REBUILD_ARGS="--target=devel ci/official/containers/ml_build"
TFCI_INDEX_HTML_ENABLE=1

        uses: astral-sh/setup-uv@v7
        with:
          enable-cache: true
          cache-dependency-glob: |
            pyproject.toml
            uv.lock
      - name: Install Dependencies
        run: uv sync --locked --no-dev --group github-actions
      # Allow debugging with tmate
      - name: Setup tmate session
        uses: mxschmitt/action-tmate@v3

        uses: astral-sh/setup-uv@v7
        with:
          enable-cache: true
          cache-dependency-glob: |
            pyproject.toml
            uv.lock
      - name: Install Dependencies
        run: uv sync --locked --no-dev --group github-actions
      # Allow debugging with tmate
      - name: Setup tmate session
        uses: mxschmitt/action-tmate@v3