Mem-build image container multi-arsitektur untuk Dataflow
Tetap teratur dengan koleksi
Simpan dan kategorikan konten berdasarkan preferensi Anda.
Jika Anda menggunakan container kustom di Dataflow, container harus cocok dengan arsitektur VM pekerja. Dokumen ini menjelaskan cara membuat
penampung multi-arsitektur yang kompatibel dengan VM x86 dan Arm.
Anda dapat menggunakan Docker CLI atau Cloud Build untuk membangun image container.
Gunakan Docker untuk membangun image
Buat Dockerfile. Gunakan petunjuk FROM untuk menentukan
image dasar multi-arsitektur.
FROM apache/beam_python3.10_sdk:2.50.0
# Make your customizations here, for example:
ENV FOO=/bar
COPY path/to/myfile ./
Instal alat
Buildx. Untuk memeriksa apakah alat sudah diinstal, jalankan perintah berikut:
dockerbuildxversion
Jalankan perintah berikut untuk membuat instance builder yang menggunakan driver
docker-container. Driver ini diperlukan untuk membuat image multi-arsitektur.
dockerbuildxcreate--driver=docker-container--use
Flag --use menetapkan instance builder baru sebagai builder saat ini.
Jalankan perintah berikut untuk mengonfigurasi Docker agar mengautentikasi permintaan ke Artifact Registry.
gcloudauthconfigure-dockerREGION-docker.pkg.dev
Ganti REGION dengan region repositori Artifact Registry.
Jalankan perintah berikut untuk membangun dan mengirim image container ke
Artifact Registry:
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],["Terakhir diperbarui pada 2025-09-04 UTC."],[[["\u003cp\u003eThis document provides instructions on creating multi-architecture container images compatible with both x86 and Arm virtual machines (VMs) for use with Dataflow custom containers.\u003c/p\u003e\n"],["\u003cp\u003eYou can build these multi-architecture images using either the Docker CLI with Buildx or Google Cloud Build, and they should specify a multi-architecture base image within their Dockerfile.\u003c/p\u003e\n"],["\u003cp\u003eWhen using the Docker CLI, the \u003ccode\u003edocker buildx\u003c/code\u003e tool is necessary, employing the \u003ccode\u003edocker-container\u003c/code\u003e driver to build the multi-architecture images.\u003c/p\u003e\n"],["\u003cp\u003eCloud Build utilizes a \u003ccode\u003edocker_buildx.yaml\u003c/code\u003e configuration file to define the build process, which includes creating a builder instance and specifying the target platforms.\u003c/p\u003e\n"],["\u003cp\u003eTo verify that a container image is multi-architecture, check its manifest file in Artifact Registry for \u003ccode\u003earm64\u003c/code\u003e and \u003ccode\u003eamd64\u003c/code\u003e entries within the \u003ccode\u003eplatform\u003c/code\u003e section.\u003c/p\u003e\n"]]],[],null,["# Build multi-architecture container images for Dataflow\n\nIf you use a custom container in Dataflow, the container must\nmatch the architecture of the worker VMs. This document describes how to create\nmulti-architecture containers that are compatible with both x86 and Arm VMs.\n\nYou can use the Docker CLI or [Cloud Build](/build/docs/overview) to build\nthe container image.\n\nUse Docker to build the image\n-----------------------------\n\n1. Create a Dockerfile. Use the `FROM` instruction to specify a\n multi-architecture base image.\n\n FROM apache/beam_python3.10_sdk:2.50.0\n\n # Make your customizations here, for example:\n ENV FOO=/bar\n COPY path/to/myfile ./\n\n2. Install the\n [Buildx](https://docs.docker.com/build/architecture/)\n tool. To check whether the tool is installed, run the following command:\n\n docker buildx version\n\n3. Run the following command to create a builder instance that uses the\n `docker-container` driver. This driver is required to build\n multi-architecture images.\n\n docker buildx create --driver=docker-container --use\n\n The `--use` flag sets the new builder instance as the current builder.\n4. Run the following command to configure Docker to authenticate requests to Artifact Registry.\n\n gcloud auth configure-docker \u003cvar translate=\"no\"\u003eREGION\u003c/var\u003e-docker.pkg.dev\n\n Replace \u003cvar translate=\"no\"\u003eREGION\u003c/var\u003e with the region of the Artifact Registry repository.\n5. Run the following command to build and push the container image to\n Artifact Registry:\n\n docker buildx build \\\n --platform=linux/amd64,linux/arm64 \\\n -t \u003cvar translate=\"no\"\u003eREGISTRY\u003c/var\u003e/\u003cvar translate=\"no\"\u003eIMAGE\u003c/var\u003e:\u003cvar translate=\"no\"\u003eTAG\u003c/var\u003e \\\n --push .\n\n Replace the following:\n - \u003cvar translate=\"no\"\u003eREGISTRY\u003c/var\u003e: the Docker repository\n - \u003cvar translate=\"no\"\u003eIMAGE\u003c/var\u003e: the image name\n - \u003cvar translate=\"no\"\u003eTAG\u003c/var\u003e: the image tag\n\nUse Cloud Build to build the image\n----------------------------------\n\n1. Create a Dockerfile. Use the `FROM` instruction to specify a\n multi-architecture base image.\n\n FROM apache/beam_python3.10_sdk:2.50.0\n\n # Make your customizations here, for example:\n ENV FOO=/bar\n COPY path/to/myfile ./\n\n2. In the same directory that contains the Dockerfile, create a file named\n `docker_buildx.yaml`. Paste in the following text:\n\n steps:\n - name: 'docker'\n args: ['buildx', 'create', '--driver', 'docker-container', '--name', 'container', '--use']\n - name: 'docker'\n args: ['buildx', 'build', '--platform', 'linux/amd64,linux/arm64', '-t', '\u003cvar translate=\"no\"\u003eREGISTRY\u003c/var\u003e/\u003cvar translate=\"no\"\u003eIMAGE\u003c/var\u003e:\u003cvar translate=\"no\"\u003eTAG\u003c/var\u003e', '--push', '.']\n\n Replace the following:\n - \u003cvar translate=\"no\"\u003eREGISTRY\u003c/var\u003e: the Docker repository\n - \u003cvar translate=\"no\"\u003eIMAGE\u003c/var\u003e: the image name\n - \u003cvar translate=\"no\"\u003eTAG\u003c/var\u003e: the image tag\n3. To build and push the image, run the\n [`gcloud builds submit` command](/sdk/gcloud/reference/builds/submit):\n\n gcloud builds submit --region=\u003cvar translate=\"no\"\u003eREGION\u003c/var\u003e --config docker_buildx.yaml\n\n Replace \u003cvar translate=\"no\"\u003eREGION\u003c/var\u003e with the region of the Cloud Build\n service to use.\n\nFor more information, see\n[Build and push a Docker image with Cloud Build](/build/docs/build-push-docker-image).\n\nVerify the container image\n--------------------------\n\n1. Open the **Repositories** page in the Google Cloud console.\n\n [Open the Repositories page](https://console.cloud.google.com/artifacts)\n2. Click the repository with the container image.\n\n3. Click the image to see its versions.\n\n4. Click a version.\n\n5. Click **Manifest**.\n\n6. In the manifest file, the `platform` section should have entries for\n `arm64` and `amd64`. For example:\n\n {\n \"schemaVersion\": 2,\n \"mediaType\": \"application/vnd.docker.distribution.manifest.list.v2+json\",\n \"manifests\": [\n {\n \"mediaType\": \"application/vnd.docker.distribution.manifest.v2+json\",\n \"digest\": \"sha256:441d5438885049e2b388523a8cb5b77ea829c3c3f53326fb221fe185abd67f07\",\n \"size\": 3074,\n \"platform\": {\n \"architecture\": \"amd64\",\n \"os\": \"linux\"\n }\n },\n {\n \"mediaType\": \"application/vnd.docker.distribution.manifest.v2+json\",\n \"digest\": \"sha256:d3b98b0f8f3f555f5453c79b240bd2b862d4f52d853fe81bae55f01a663de29c\",\n \"size\": 3073,\n \"platform\": {\n \"architecture\": \"arm64\",\n \"os\": \"linux\"\n }\n }\n ]\n }\n\nWhat's next\n-----------\n\n- [Use Arm VMs on Dataflow](/dataflow/docs/guides/use-arm-vms)\n- [Run a Dataflow job in a custom container](/dataflow/docs/guides/run-custom-container)"]]
