```
trustedCertsSecret: "minio-trusted-certs"

or

--set trustedCertsSecret=minio-trusted-certs
```

### Create buckets after install

Install the chart, specifying the buckets you want to create after install:

```bash
helm install --set buckets[0].name=bucket1,buckets[0].policy=none,buckets[0].purge=false minio/minio
```

Description of the configuration parameters used above -

test-root-disable: install-race
	@echo "Running minio root lockdown tests"
	@env bash $(PWD)/buildscripts/disable-root.sh

test-ilm: install-race
	@echo "Running ILM tests"
	@env bash $(PWD)/docs/bucket/replication/setup_ilm_expiry_replication.sh

test-ilm-transition: install-race
	@echo "Running ILM tiering tests with healing"

If you don't want to have those optional dependencies, you can instead install `pip install fastapi`.

	<property name="opensearch.version" value="3.4.0" />

	<target name="install.modules">
		<mkdir dir="${target.dir}" />
		<delete dir="${modules.dir}" />
		<mkdir dir="${modules.dir}" />

		<!-- analysis-common -->
		<antcall target="install.module">
			<param name="repo.url" value="${maven.release.repo.url}" />

	<property name="maven.release.repo.url" value="https://repo1.maven.org/maven2" />

	<target name="install.plugins">
		<mkdir dir="${target.dir}" />
		<delete dir="${plugins.dir}" />
		<mkdir dir="${plugins.dir}" />
		<!-- analysis-extension -->
		<antcall target="install.plugin">
			<param name="repo.url" value="${maven.release.repo.url}" />
			<param name="plugin.groupId" value="org/codelibs/opensearch" />

    "$python" -m pip install numpy==1.26.4
  else
    "$python" -m pip install numpy==1.26.0
  fi
fi
if [[ "$TFCI_BAZEL_COMMON_ARGS" =~ gpu|cuda ]]; then
  echo "Checking to make sure tensorflow[and-cuda] is installable..."
  "$python" -m pip install "$(echo *.whl)[and-cuda]" $TFCI_PYTHON_VERIFY_PIP_INSTALL_ARGS
else
  "$python" -m pip install *.whl $TFCI_PYTHON_VERIFY_PIP_INSTALL_ARGS
fi

     * @throws IllegalArgumentException in case {@code request} is {@code null}
     */
    void install(@Nonnull ArtifactInstallerRequest request);

    /**
     * @param session the repository session
     * @param artifact the {@link ProducedArtifact} to install
     * @throws ArtifactInstallerException in case of an error which can be a given artifact cannot be found or the

    tar zxf - google-cloud-sdk && \
    google-cloud-sdk/install.sh --quiet && \
    ln -s /google-cloud-sdk/bin/gcloud /usr/bin/gcloud
ENV PATH="$PATH:/google-cloud-sdk/bin/:/usr/local/cuda/bin/"

# Download and install patchelf v0.18.0 from GitHub. The default Ubuntu focal
# packages only provide the "0.10-2build1" version. We use patchelf to manipulate

       * Refer [windows setup guide](https://www.tensorflow.org/install/gpu#windows_setup).
     * If you have above configuration and using _**Ubuntu/Linux**_ platform -
       * Try adding the CUDA, CUPTI, and cuDNN installation directories to the $LD_LIBRARY_PATH environment variable.
       * Refer [linux setup guide](https://www.tensorflow.org/install/gpu#linux_setup).

        with:
          version: "0.4.15"
          enable-cache: true
          cache-dependency-glob: |
            requirements**.txt
            pyproject.toml
      - name: Install docs extras
        run: uv pip install -r requirements-docs.txt
      - name: Export Language Codes
        id: show-langs
        run: |
          echo "langs=$(python ./scripts/docs.py langs-json)" >> $GITHUB_OUTPUT

  build-docs: