should be reported by email to ******@****.***. Your email will be acknowledged within 48 hours,
and you'll receive a more detailed response to your email within 72 hours indicating the next steps
in handling your report.

Please, provide a detailed explanation of the issue. In particular, outline the type of the security

  workflow_dispatch:

permissions:
  contents: read
  id-token: write

jobs:
  cleanup-stale-performance-data:
    runs-on: ubuntu-latest

    if: github.repository == 'gradle/gradle'

    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
      
      - name: Configure AWS credentials
        uses: aws-actions/configure-aws-credentials@v6
        with:

  contents: read

jobs:
  build:
    if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks
    runs-on: [self-hosted, linux, ARM64]
    strategy:
      matrix:
        pyver: ['3.10']
    steps:
      - name: Stop old running containers (if any)
        shell: bash
        run: |
          running_containers=$(docker ps -q) && \
          if [[ $running_containers == "" ]]; then

 * scopes and their associated implied scopes, so that the user can filter apply a series of implication rules in a
 * single step. This should be a more efficient implementation of multiple standard {@link ScopeArtifactFilter}
 * instances ORed together.
 *
 */
public class CumulativeScopeArtifactFilter extends AbstractScopeArtifactFilter {

      # Notify homer
      - postbuildscript:
          builders:
            - role: SLAVE
              build-on:
                - SUCCESS
                - FAILURE
                - UNSTABLE
              build-steps:
                - http-request:
                    url: https://homer.app.elstc.co/webhook/jenkins/build-finished
                    mode: GET
                    custom-headers:

        applyPerformanceTestSettings()
        setArtifactRules(INDIVIDUAL_PERFORAMCE_TEST_ARTIFACT_RULES)

        steps {
            killProcessStep(buildTypeThis, KILL_ALL_GRADLE_PROCESSES, os)
            adHocPerformanceTest(
                listOf(

                subst p: "%teamcity.build.checkoutDir%"
                """.trimIndent()
            skipConditionally()
        }
    }
}

fun BuildType.cleanUpGitUntrackedFilesAndDirectories() {
    steps {
        script {
            name = "CLEAN_UP_GIT_UNTRACKED_FILES_AND_DIRECTORIES"
            executionMode = BuildStep.ExecutionMode.RUN_ONLY_ON_FAILURE

Let's check back those deployment concepts from before:

* Security - HTTPS
* Running on startup
* Restarts
* **Replication (the number of processes running)**
* Memory
* Previous steps before starting

Up to this point, with all the tutorials in the docs, you have probably been running a **server program**, for example, using the `fastapi` command, that runs Uvicorn, running a **single process**.

    if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks
    runs-on: [self-hosted, linux, ARM64]
    strategy:
      fail-fast: false
      matrix:
        pyver: ['3.9', '3.10', '3.11', '3.12']
    steps:
      - name: Stop old running containers (if any)
        shell: bash
        run: |
          running_containers=$(docker ps -q) && \
          if [[ $running_containers == "" ]]; then

Обычно это называется вебхуком.

## Шаги вебхуков { #webhooks-steps }

Обычно процесс таков: вы определяете в своем коде, какое сообщение вы будете отправлять, то есть тело запроса.

Вы также определяете, в какие моменты (при каких событиях) ваше приложение будет отправлять эти запросы.